program(1.2) [mldb_token = string("mldb-lvy3nqqgdo")]
{
    func initialFrame<ios18>(tensor<fp16, [1, 64, 32, 32]> hidden_state, pixel_buffer<FMT_32BGRA, shape=[512, 512]> input_image, tensor<fp16, [1, 1, 512, 512]> mask, tensor<fp16, [1, 2048, 1, 64]> prev_key, tensor<fp16, [1, 128, 1, 2048]> prev_value) [E5_FlagsEir = dict<string, string>({{"allowSoftmaxApproximation", "1"}, {"early_arch_extended_reshape", "1"}, {"experimental.ane.early_arch_transposes", "1"}, {"experimental.ane.enable_rsqrt", "1"}, {"experimental.ane.reduce_mean_spatial", "1"}, {"experimental.aot.enable_surface_desc", "1"}})] {
            tensor<fp16, [1, 3, 1, 1]> var_47_to_fp16 = const()[name = string("op_47_to_fp16"), val = tensor<fp16, [1, 3, 1, 1]>([[[[123.6875]], [[116.25]], [[103.5]]]])];
            tensor<uint8, [4, 512, 512]> images_tensor_bgra_uint8 = pixel_buffer_to_tensor(input = input_image);
            tensor<fp16, [4, 512, 512]> images_tensor_bgra_fp16 = cast(dtype = string("fp16"), x = images_tensor_bgra_uint8);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_b = slice_by_index(begin = tensor<int32, [3]>([0, 0, 0]), end = tensor<int32, [3]>([1, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_g = slice_by_index(begin = tensor<int32, [3]>([1, 0, 0]), end = tensor<int32, [3]>([2, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_r = slice_by_index(begin = tensor<int32, [3]>([2, 0, 0]), end = tensor<int32, [3]>([3, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [3, 512, 512]> images_tensor_rgb_fp16 = concat(axis = int32(0), interleave = bool(false), values = (images_tensor_slice_r, images_tensor_slice_g, images_tensor_slice_b));
            tensor<fp16, [1, 3, 512, 512]> images_tensor_tensor = expand_dims(axes = tensor<int32, [1]>([0]), x = images_tensor_rgb_fp16);
            tensor<fp16, [1, 3, 512, 512]> tensor_5_cast_fp16 = sub(x = images_tensor_tensor, y = var_47_to_fp16)[name = string("tensor_5_cast_fp16")];
            tensor<fp16, [1, 3, 1, 1]> _inversed_input_1_y_0_to_fp16 = const()[name = string("_inversed_input_1_y_0_to_fp16"), val = tensor<fp16, [1, 3, 1, 1]>([[[[0.0171203613]], [[0.0175018311]], [[0.0174255371]]]])];
            tensor<fp16, [1, 3, 512, 512]> _inversed_input_1_cast_fp16 = mul(x = tensor_5_cast_fp16, y = _inversed_input_1_y_0_to_fp16)[name = string("_inversed_input_1_cast_fp16")];
            int32 var_86 = const()[name = string("op_86"), val = int32(1)];
            tensor<int32, [8]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [8]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("constant")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0)];
            tensor<fp16, [1, 3, 513, 513]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = _inversed_input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<int32, [2]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [24, 3, 3, 3]> const_95_to_fp16 = const()[name = string("const_95_to_fp16"), val = tensor<fp16, [24, 3, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [24]> const_96_to_fp16 = const()[name = string("const_96_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1728)))];
            tensor<fp16, [1, 24, 256, 256]> input_7_cast_fp16 = conv(bias = const_96_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = const_95_to_fp16, x = input_3_cast_fp16)[name = string("input_7_cast_fp16")];
            tensor<fp16, [1, 24, 256, 256]> input_9_cast_fp16 = relu(x = input_7_cast_fp16)[name = string("input_9_cast_fp16")];
            tensor<int32, [2]> var_2890 = const()[name = string("op_2890"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_2891 = const()[name = string("op_2891"), val = tensor<int32, [2]>([2, 2])];
            string input_11_pad_type_0 = const()[name = string("input_11_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_11_pad_0 = const()[name = string("input_11_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1856)))];
            bool input_11_ceil_mode_0 = const()[name = string("input_11_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 24, 128, 128]> input_11_cast_fp16 = max_pool(ceil_mode = input_11_ceil_mode_0, kernel_sizes = var_2890, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = var_2891, x = input_9_cast_fp16)[name = string("input_11_cast_fp16")];
            string input_17_pad_type_0 = const()[name = string("input_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_17_strides_0 = const()[name = string("input_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1984)))];
            tensor<int32, [2]> input_17_dilations_0 = const()[name = string("input_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_17_groups_0 = const()[name = string("input_17_groups_0"), val = int32(1)];
            tensor<fp16, [144, 24, 1, 1]> const_97_to_fp16 = const()[name = string("const_97_to_fp16"), val = tensor<fp16, [144, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2112)))];
            tensor<fp16, [144]> const_98_to_fp16 = const()[name = string("const_98_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9088)))];
            tensor<fp16, [1, 144, 128, 128]> input_19_cast_fp16 = conv(bias = const_98_to_fp16, dilations = input_17_dilations_0, groups = input_17_groups_0, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = input_17_strides_0, weight = const_97_to_fp16, x = input_11_cast_fp16)[name = string("input_19_cast_fp16")];
            tensor<fp16, [1, 144, 128, 128]> input_21_cast_fp16 = relu(x = input_19_cast_fp16)[name = string("input_21_cast_fp16")];
            string input_23_pad_type_0 = const()[name = string("input_23_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9472)))];
            tensor<int32, [2]> input_23_strides_0 = const()[name = string("input_23_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_23_groups_0 = const()[name = string("input_23_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_23_dilations_0 = const()[name = string("input_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [144, 1, 5, 5]> const_99_to_fp16 = const()[name = string("const_99_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9600)))];
            tensor<fp16, [144]> const_100_to_fp16 = const()[name = string("const_100_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16896)))];
            tensor<fp16, [1, 144, 64, 64]> input_25_cast_fp16 = conv(bias = const_100_to_fp16, dilations = input_23_dilations_0, groups = input_23_groups_0, pad = input_23_pad_0, pad_type = input_23_pad_type_0, strides = input_23_strides_0, weight = const_99_to_fp16, x = input_21_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_27_cast_fp16 = relu(x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_29_pad_type_0 = const()[name = string("input_29_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_29_strides_0 = const()[name = string("input_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_29_pad_0 = const()[name = string("input_29_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17280)))];
            tensor<int32, [2]> input_29_dilations_0 = const()[name = string("input_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_29_groups_0 = const()[name = string("input_29_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_101_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17408))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38208))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38592)))];
            tensor<fp16, [144]> const_102_to_fp16 = const()[name = string("const_102_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38848)))];
            tensor<fp16, [1, 144, 64, 64]> x_1_cast_fp16 = conv(bias = const_102_to_fp16, dilations = input_29_dilations_0, groups = input_29_groups_0, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = input_29_strides_0, weight = const_101_to_fp16, x = input_27_cast_fp16)[name = string("x_1_cast_fp16")];
            tensor<int32, [4]> var_2929_begin_0 = const()[name = string("op_2929_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39232)))];
            tensor<int32, [4]> var_2929_end_0 = const()[name = string("op_2929_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39360)))];
            tensor<bool, [4]> var_2929_end_mask_0 = const()[name = string("op_2929_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2929_cast_fp16 = slice_by_index(begin = var_2929_begin_0, end = var_2929_end_0, end_mask = var_2929_end_mask_0, x = x_1_cast_fp16)[name = string("op_2929_cast_fp16")];
            tensor<int32, [4]> var_2933_begin_0 = const()[name = string("op_2933_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39488)))];
            tensor<int32, [4]> var_2933_end_0 = const()[name = string("op_2933_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39616)))];
            tensor<bool, [4]> var_2933_end_mask_0 = const()[name = string("op_2933_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2933_cast_fp16 = slice_by_index(begin = var_2933_begin_0, end = var_2933_end_0, end_mask = var_2933_end_mask_0, x = x_1_cast_fp16)[name = string("op_2933_cast_fp16")];
            tensor<int32, [4]> var_2937_begin_0 = const()[name = string("op_2937_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39744)))];
            tensor<int32, [4]> var_2937_end_0 = const()[name = string("op_2937_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39872)))];
            tensor<bool, [4]> var_2937_end_mask_0 = const()[name = string("op_2937_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2937_cast_fp16 = slice_by_index(begin = var_2937_begin_0, end = var_2937_end_0, end_mask = var_2937_end_mask_0, x = x_1_cast_fp16)[name = string("op_2937_cast_fp16")];
            tensor<int32, [4]> var_2941_begin_0 = const()[name = string("op_2941_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40000)))];
            tensor<int32, [4]> var_2941_end_0 = const()[name = string("op_2941_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40128)))];
            tensor<bool, [4]> var_2941_end_mask_0 = const()[name = string("op_2941_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2941_cast_fp16 = slice_by_index(begin = var_2941_begin_0, end = var_2941_end_0, end_mask = var_2941_end_mask_0, x = x_1_cast_fp16)[name = string("op_2941_cast_fp16")];
            string input_33_pad_type_0 = const()[name = string("input_33_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_33_strides_0 = const()[name = string("input_33_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40256)))];
            tensor<int32, [2]> input_33_dilations_0 = const()[name = string("input_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_33_groups_0 = const()[name = string("input_33_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_103_to_fp16 = const()[name = string("const_103_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40384)))];
            tensor<fp16, [36]> const_104_to_fp16 = const()[name = string("const_104_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43072)))];
            tensor<fp16, [1, 36, 64, 64]> input_35_cast_fp16 = conv(bias = const_104_to_fp16, dilations = input_33_dilations_0, groups = input_33_groups_0, pad = input_33_pad_0, pad_type = input_33_pad_type_0, strides = input_33_strides_0, weight = const_103_to_fp16, x = var_2933_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_37_cast_fp16 = relu(x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_39_pad_type_0 = const()[name = string("input_39_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_39_pad_0 = const()[name = string("input_39_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43264)))];
            int32 input_39_groups_0 = const()[name = string("input_39_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_39_strides_0 = const()[name = string("input_39_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_39_dilations_0 = const()[name = string("input_39_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_105_to_fp16 = const()[name = string("const_105_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43392)))];
            tensor<fp16, [36]> const_106_to_fp16 = const()[name = string("const_106_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45312)))];
            tensor<fp16, [1, 36, 64, 64]> input_41_cast_fp16 = conv(bias = const_106_to_fp16, dilations = input_39_dilations_0, groups = input_39_groups_0, pad = input_39_pad_0, pad_type = input_39_pad_type_0, strides = input_39_strides_0, weight = const_105_to_fp16, x = input_37_cast_fp16)[name = string("input_41_cast_fp16")];
            string input_43_pad_type_0 = const()[name = string("input_43_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_43_strides_0 = const()[name = string("input_43_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45504)))];
            tensor<int32, [2]> input_43_dilations_0 = const()[name = string("input_43_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_43_groups_0 = const()[name = string("input_43_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45632)))];
            tensor<fp16, [36]> const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48320)))];
            tensor<fp16, [1, 36, 64, 64]> input_45_cast_fp16 = conv(bias = const_108_to_fp16, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_107_to_fp16, x = input_41_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_1_cast_fp16 = relu(x = input_45_cast_fp16)[name = string("out1_1_cast_fp16")];
            string input_49_pad_type_0 = const()[name = string("input_49_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_49_strides_0 = const()[name = string("input_49_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_49_pad_0 = const()[name = string("input_49_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48512)))];
            tensor<int32, [2]> input_49_dilations_0 = const()[name = string("input_49_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_49_groups_0 = const()[name = string("input_49_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_109_to_fp16 = const()[name = string("const_109_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48640)))];
            tensor<fp16, [36]> const_110_to_fp16 = const()[name = string("const_110_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51328)))];
            tensor<fp16, [1, 36, 64, 64]> input_51_cast_fp16 = conv(bias = const_110_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_109_to_fp16, x = var_2937_cast_fp16)[name = string("input_51_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_53_cast_fp16 = relu(x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string input_55_pad_type_0 = const()[name = string("input_55_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_55_pad_0 = const()[name = string("input_55_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51520)))];
            int32 input_55_groups_0 = const()[name = string("input_55_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_55_strides_0 = const()[name = string("input_55_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_55_dilations_0 = const()[name = string("input_55_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_111_to_fp16 = const()[name = string("const_111_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51648)))];
            tensor<fp16, [36]> const_112_to_fp16 = const()[name = string("const_112_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53568)))];
            tensor<fp16, [1, 36, 64, 64]> input_57_cast_fp16 = conv(bias = const_112_to_fp16, dilations = input_55_dilations_0, groups = input_55_groups_0, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = input_55_strides_0, weight = const_111_to_fp16, x = input_53_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_59_pad_type_0 = const()[name = string("input_59_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_59_strides_0 = const()[name = string("input_59_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_59_pad_0 = const()[name = string("input_59_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53760)))];
            tensor<int32, [2]> input_59_dilations_0 = const()[name = string("input_59_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_59_groups_0 = const()[name = string("input_59_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_113_to_fp16 = const()[name = string("const_113_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53888)))];
            tensor<fp16, [36]> const_114_to_fp16 = const()[name = string("const_114_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56576)))];
            tensor<fp16, [1, 36, 64, 64]> input_61_cast_fp16 = conv(bias = const_114_to_fp16, dilations = input_59_dilations_0, groups = input_59_groups_0, pad = input_59_pad_0, pad_type = input_59_pad_type_0, strides = input_59_strides_0, weight = const_113_to_fp16, x = input_57_cast_fp16)[name = string("input_61_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_1_cast_fp16 = relu(x = input_61_cast_fp16)[name = string("out2_1_cast_fp16")];
            string input_65_pad_type_0 = const()[name = string("input_65_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_65_strides_0 = const()[name = string("input_65_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_65_pad_0 = const()[name = string("input_65_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56768)))];
            tensor<int32, [2]> input_65_dilations_0 = const()[name = string("input_65_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_65_groups_0 = const()[name = string("input_65_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56896)))];
            tensor<fp16, [36]> const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59584)))];
            tensor<fp16, [1, 36, 64, 64]> input_67_cast_fp16 = conv(bias = const_116_to_fp16, dilations = input_65_dilations_0, groups = input_65_groups_0, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = input_65_strides_0, weight = const_115_to_fp16, x = var_2941_cast_fp16)[name = string("input_67_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_69_cast_fp16 = relu(x = input_67_cast_fp16)[name = string("input_69_cast_fp16")];
            string input_71_pad_type_0 = const()[name = string("input_71_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_71_pad_0 = const()[name = string("input_71_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59776)))];
            int32 input_71_groups_0 = const()[name = string("input_71_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_71_strides_0 = const()[name = string("input_71_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_71_dilations_0 = const()[name = string("input_71_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_117_to_fp16 = const()[name = string("const_117_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59904)))];
            tensor<fp16, [36]> const_118_to_fp16 = const()[name = string("const_118_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61824)))];
            tensor<fp16, [1, 36, 64, 64]> input_73_cast_fp16 = conv(bias = const_118_to_fp16, dilations = input_71_dilations_0, groups = input_71_groups_0, pad = input_71_pad_0, pad_type = input_71_pad_type_0, strides = input_71_strides_0, weight = const_117_to_fp16, x = input_69_cast_fp16)[name = string("input_73_cast_fp16")];
            string input_75_pad_type_0 = const()[name = string("input_75_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_75_strides_0 = const()[name = string("input_75_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_75_pad_0 = const()[name = string("input_75_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(62016)))];
            tensor<int32, [2]> input_75_dilations_0 = const()[name = string("input_75_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_75_groups_0 = const()[name = string("input_75_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_119_to_fp16 = const()[name = string("const_119_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(62144)))];
            tensor<fp16, [36]> const_120_to_fp16 = const()[name = string("const_120_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64832)))];
            tensor<fp16, [1, 36, 64, 64]> input_77_cast_fp16 = conv(bias = const_120_to_fp16, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = const_119_to_fp16, x = input_73_cast_fp16)[name = string("input_77_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_1_cast_fp16 = relu(x = input_77_cast_fp16)[name = string("out3_1_cast_fp16")];
            bool input_79_interleave_0 = const()[name = string("input_79_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_79_cast_fp16 = concat(axis = var_86, interleave = input_79_interleave_0, values = (var_2929_cast_fp16, out1_1_cast_fp16, out2_1_cast_fp16, out3_1_cast_fp16))[name = string("input_79_cast_fp16")];
            string input_81_pad_type_0 = const()[name = string("input_81_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_81_strides_0 = const()[name = string("input_81_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_81_pad_0 = const()[name = string("input_81_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(65024)))];
            tensor<int32, [2]> input_81_dilations_0 = const()[name = string("input_81_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_81_groups_0 = const()[name = string("input_81_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_121_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(65152))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85952))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86336)))];
            tensor<fp16, [144]> const_122_to_fp16 = const()[name = string("const_122_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86592)))];
            tensor<fp16, [1, 144, 64, 64]> input_83_cast_fp16 = conv(bias = const_122_to_fp16, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = const_121_to_fp16, x = input_79_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_85_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("input_85_cast_fp16")];
            string input_87_pad_type_0 = const()[name = string("input_87_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86976)))];
            int32 input_87_groups_0 = const()[name = string("input_87_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_87_strides_0 = const()[name = string("input_87_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_87_dilations_0 = const()[name = string("input_87_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [144, 1, 5, 5]> const_123_to_fp16 = const()[name = string("const_123_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(87104)))];
            tensor<fp16, [144]> const_124_to_fp16 = const()[name = string("const_124_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94400)))];
            tensor<fp16, [1, 144, 64, 64]> input_89_cast_fp16 = conv(bias = const_124_to_fp16, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = const_123_to_fp16, x = input_85_cast_fp16)[name = string("input_89_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_91_cast_fp16 = relu(x = input_89_cast_fp16)[name = string("input_91_cast_fp16")];
            string input_93_pad_type_0 = const()[name = string("input_93_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_93_strides_0 = const()[name = string("input_93_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_93_pad_0 = const()[name = string("input_93_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94784)))];
            tensor<int32, [2]> input_93_dilations_0 = const()[name = string("input_93_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_93_groups_0 = const()[name = string("input_93_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_125_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94912))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(115712))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116096)))];
            tensor<fp16, [144]> const_126_to_fp16 = const()[name = string("const_126_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116352)))];
            tensor<fp16, [1, 144, 64, 64]> y_1_cast_fp16 = conv(bias = const_126_to_fp16, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = const_125_to_fp16, x = input_91_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> x_3_cast_fp16 = add(x = input_79_cast_fp16, y = y_1_cast_fp16)[name = string("x_3_cast_fp16")];
            tensor<int32, [4]> var_3041_begin_0 = const()[name = string("op_3041_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116736)))];
            tensor<int32, [4]> var_3041_end_0 = const()[name = string("op_3041_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116864)))];
            tensor<bool, [4]> var_3041_end_mask_0 = const()[name = string("op_3041_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3041_cast_fp16 = slice_by_index(begin = var_3041_begin_0, end = var_3041_end_0, end_mask = var_3041_end_mask_0, x = x_3_cast_fp16)[name = string("op_3041_cast_fp16")];
            tensor<int32, [4]> var_3045_begin_0 = const()[name = string("op_3045_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116992)))];
            tensor<int32, [4]> var_3045_end_0 = const()[name = string("op_3045_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117120)))];
            tensor<bool, [4]> var_3045_end_mask_0 = const()[name = string("op_3045_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3045_cast_fp16 = slice_by_index(begin = var_3045_begin_0, end = var_3045_end_0, end_mask = var_3045_end_mask_0, x = x_3_cast_fp16)[name = string("op_3045_cast_fp16")];
            tensor<int32, [4]> var_3049_begin_0 = const()[name = string("op_3049_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117248)))];
            tensor<int32, [4]> var_3049_end_0 = const()[name = string("op_3049_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117376)))];
            tensor<bool, [4]> var_3049_end_mask_0 = const()[name = string("op_3049_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3049_cast_fp16 = slice_by_index(begin = var_3049_begin_0, end = var_3049_end_0, end_mask = var_3049_end_mask_0, x = x_3_cast_fp16)[name = string("op_3049_cast_fp16")];
            tensor<int32, [4]> var_3053_begin_0 = const()[name = string("op_3053_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117504)))];
            tensor<int32, [4]> var_3053_end_0 = const()[name = string("op_3053_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117632)))];
            tensor<bool, [4]> var_3053_end_mask_0 = const()[name = string("op_3053_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3053_cast_fp16 = slice_by_index(begin = var_3053_begin_0, end = var_3053_end_0, end_mask = var_3053_end_mask_0, x = x_3_cast_fp16)[name = string("op_3053_cast_fp16")];
            string input_97_pad_type_0 = const()[name = string("input_97_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_97_strides_0 = const()[name = string("input_97_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117760)))];
            tensor<int32, [2]> input_97_dilations_0 = const()[name = string("input_97_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_97_groups_0 = const()[name = string("input_97_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_127_to_fp16 = const()[name = string("const_127_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117888)))];
            tensor<fp16, [36]> const_128_to_fp16 = const()[name = string("const_128_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120576)))];
            tensor<fp16, [1, 36, 64, 64]> input_99_cast_fp16 = conv(bias = const_128_to_fp16, dilations = input_97_dilations_0, groups = input_97_groups_0, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = input_97_strides_0, weight = const_127_to_fp16, x = var_3045_cast_fp16)[name = string("input_99_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_101_cast_fp16 = relu(x = input_99_cast_fp16)[name = string("input_101_cast_fp16")];
            string input_103_pad_type_0 = const()[name = string("input_103_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_103_pad_0 = const()[name = string("input_103_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120768)))];
            int32 input_103_groups_0 = const()[name = string("input_103_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_103_strides_0 = const()[name = string("input_103_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_103_dilations_0 = const()[name = string("input_103_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_129_to_fp16 = const()[name = string("const_129_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120896)))];
            tensor<fp16, [36]> const_130_to_fp16 = const()[name = string("const_130_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(122816)))];
            tensor<fp16, [1, 36, 64, 64]> input_105_cast_fp16 = conv(bias = const_130_to_fp16, dilations = input_103_dilations_0, groups = input_103_groups_0, pad = input_103_pad_0, pad_type = input_103_pad_type_0, strides = input_103_strides_0, weight = const_129_to_fp16, x = input_101_cast_fp16)[name = string("input_105_cast_fp16")];
            string input_107_pad_type_0 = const()[name = string("input_107_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_107_strides_0 = const()[name = string("input_107_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_107_pad_0 = const()[name = string("input_107_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123008)))];
            tensor<int32, [2]> input_107_dilations_0 = const()[name = string("input_107_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_107_groups_0 = const()[name = string("input_107_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_131_to_fp16 = const()[name = string("const_131_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123136)))];
            tensor<fp16, [36]> const_132_to_fp16 = const()[name = string("const_132_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(125824)))];
            tensor<fp16, [1, 36, 64, 64]> input_109_cast_fp16 = conv(bias = const_132_to_fp16, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = const_131_to_fp16, x = input_105_cast_fp16)[name = string("input_109_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_3_cast_fp16 = relu(x = input_109_cast_fp16)[name = string("out1_3_cast_fp16")];
            string input_113_pad_type_0 = const()[name = string("input_113_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_113_strides_0 = const()[name = string("input_113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_113_pad_0 = const()[name = string("input_113_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(126016)))];
            tensor<int32, [2]> input_113_dilations_0 = const()[name = string("input_113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_113_groups_0 = const()[name = string("input_113_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_133_to_fp16 = const()[name = string("const_133_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(126144)))];
            tensor<fp16, [36]> const_134_to_fp16 = const()[name = string("const_134_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(128832)))];
            tensor<fp16, [1, 36, 64, 64]> input_115_cast_fp16 = conv(bias = const_134_to_fp16, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = const_133_to_fp16, x = var_3049_cast_fp16)[name = string("input_115_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_117_cast_fp16 = relu(x = input_115_cast_fp16)[name = string("input_117_cast_fp16")];
            string input_119_pad_type_0 = const()[name = string("input_119_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_119_pad_0 = const()[name = string("input_119_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(129024)))];
            int32 input_119_groups_0 = const()[name = string("input_119_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_119_strides_0 = const()[name = string("input_119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_119_dilations_0 = const()[name = string("input_119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_135_to_fp16 = const()[name = string("const_135_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(129152)))];
            tensor<fp16, [36]> const_136_to_fp16 = const()[name = string("const_136_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131072)))];
            tensor<fp16, [1, 36, 64, 64]> input_121_cast_fp16 = conv(bias = const_136_to_fp16, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = const_135_to_fp16, x = input_117_cast_fp16)[name = string("input_121_cast_fp16")];
            string input_123_pad_type_0 = const()[name = string("input_123_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_123_strides_0 = const()[name = string("input_123_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_123_pad_0 = const()[name = string("input_123_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131264)))];
            tensor<int32, [2]> input_123_dilations_0 = const()[name = string("input_123_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_123_groups_0 = const()[name = string("input_123_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_137_to_fp16 = const()[name = string("const_137_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131392)))];
            tensor<fp16, [36]> const_138_to_fp16 = const()[name = string("const_138_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134080)))];
            tensor<fp16, [1, 36, 64, 64]> input_125_cast_fp16 = conv(bias = const_138_to_fp16, dilations = input_123_dilations_0, groups = input_123_groups_0, pad = input_123_pad_0, pad_type = input_123_pad_type_0, strides = input_123_strides_0, weight = const_137_to_fp16, x = input_121_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_3_cast_fp16 = relu(x = input_125_cast_fp16)[name = string("out2_3_cast_fp16")];
            string input_129_pad_type_0 = const()[name = string("input_129_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_129_strides_0 = const()[name = string("input_129_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_129_pad_0 = const()[name = string("input_129_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134272)))];
            tensor<int32, [2]> input_129_dilations_0 = const()[name = string("input_129_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_129_groups_0 = const()[name = string("input_129_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_139_to_fp16 = const()[name = string("const_139_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134400)))];
            tensor<fp16, [36]> const_140_to_fp16 = const()[name = string("const_140_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137088)))];
            tensor<fp16, [1, 36, 64, 64]> input_131_cast_fp16 = conv(bias = const_140_to_fp16, dilations = input_129_dilations_0, groups = input_129_groups_0, pad = input_129_pad_0, pad_type = input_129_pad_type_0, strides = input_129_strides_0, weight = const_139_to_fp16, x = var_3053_cast_fp16)[name = string("input_131_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_133_cast_fp16 = relu(x = input_131_cast_fp16)[name = string("input_133_cast_fp16")];
            string input_135_pad_type_0 = const()[name = string("input_135_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_135_pad_0 = const()[name = string("input_135_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137280)))];
            int32 input_135_groups_0 = const()[name = string("input_135_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_135_strides_0 = const()[name = string("input_135_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_135_dilations_0 = const()[name = string("input_135_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_141_to_fp16 = const()[name = string("const_141_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137408)))];
            tensor<fp16, [36]> const_142_to_fp16 = const()[name = string("const_142_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139328)))];
            tensor<fp16, [1, 36, 64, 64]> input_137_cast_fp16 = conv(bias = const_142_to_fp16, dilations = input_135_dilations_0, groups = input_135_groups_0, pad = input_135_pad_0, pad_type = input_135_pad_type_0, strides = input_135_strides_0, weight = const_141_to_fp16, x = input_133_cast_fp16)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139520)))];
            tensor<int32, [2]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_143_to_fp16 = const()[name = string("const_143_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139648)))];
            tensor<fp16, [36]> const_144_to_fp16 = const()[name = string("const_144_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142336)))];
            tensor<fp16, [1, 36, 64, 64]> input_141_cast_fp16 = conv(bias = const_144_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = const_143_to_fp16, x = input_137_cast_fp16)[name = string("input_141_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_3_cast_fp16 = relu(x = input_141_cast_fp16)[name = string("out3_3_cast_fp16")];
            bool input_143_interleave_0 = const()[name = string("input_143_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_143_cast_fp16 = concat(axis = var_86, interleave = input_143_interleave_0, values = (var_3041_cast_fp16, out1_3_cast_fp16, out2_3_cast_fp16, out3_3_cast_fp16))[name = string("input_143_cast_fp16")];
            string input_145_pad_type_0 = const()[name = string("input_145_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_145_strides_0 = const()[name = string("input_145_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_145_pad_0 = const()[name = string("input_145_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142528)))];
            tensor<int32, [2]> input_145_dilations_0 = const()[name = string("input_145_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_145_groups_0 = const()[name = string("input_145_groups_0"), val = int32(1)];
            tensor<fp16, [256, 144, 1, 1]> const_145_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142656))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(179584))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180160)))];
            tensor<fp16, [256]> const_146_to_fp16 = const()[name = string("const_146_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180480)))];
            tensor<fp16, [1, 256, 64, 64]> input_147_cast_fp16 = conv(bias = const_146_to_fp16, dilations = input_145_dilations_0, groups = input_145_groups_0, pad = input_145_pad_0, pad_type = input_145_pad_type_0, strides = input_145_strides_0, weight = const_145_to_fp16, x = input_143_cast_fp16)[name = string("input_147_cast_fp16")];
            tensor<fp16, [1, 256, 64, 64]> input_149_cast_fp16 = relu(x = input_147_cast_fp16)[name = string("input_149_cast_fp16")];
            string input_151_pad_type_0 = const()[name = string("input_151_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_151_pad_0 = const()[name = string("input_151_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181056)))];
            tensor<int32, [2]> input_151_strides_0 = const()[name = string("input_151_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_151_groups_0 = const()[name = string("input_151_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_151_dilations_0 = const()[name = string("input_151_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_147_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181184))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(187648))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(188224)))];
            tensor<fp16, [256]> const_148_to_fp16 = const()[name = string("const_148_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(188544)))];
            tensor<fp16, [1, 256, 32, 32]> input_153_cast_fp16 = conv(bias = const_148_to_fp16, dilations = input_151_dilations_0, groups = input_151_groups_0, pad = input_151_pad_0, pad_type = input_151_pad_type_0, strides = input_151_strides_0, weight = const_147_to_fp16, x = input_149_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_155_cast_fp16 = relu(x = input_153_cast_fp16)[name = string("input_155_cast_fp16")];
            string input_157_pad_type_0 = const()[name = string("input_157_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_157_strides_0 = const()[name = string("input_157_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_157_pad_0 = const()[name = string("input_157_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189120)))];
            tensor<int32, [2]> input_157_dilations_0 = const()[name = string("input_157_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_157_groups_0 = const()[name = string("input_157_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_149_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189248))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(254848))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(255424)))];
            tensor<fp16, [256]> const_150_to_fp16 = const()[name = string("const_150_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(255744)))];
            tensor<fp16, [1, 256, 32, 32]> x_5_cast_fp16 = conv(bias = const_150_to_fp16, dilations = input_157_dilations_0, groups = input_157_groups_0, pad = input_157_pad_0, pad_type = input_157_pad_type_0, strides = input_157_strides_0, weight = const_149_to_fp16, x = input_155_cast_fp16)[name = string("x_5_cast_fp16")];
            tensor<int32, [4]> var_3152_begin_0 = const()[name = string("op_3152_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256320)))];
            tensor<int32, [4]> var_3152_end_0 = const()[name = string("op_3152_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256448)))];
            tensor<bool, [4]> var_3152_end_mask_0 = const()[name = string("op_3152_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3152_cast_fp16 = slice_by_index(begin = var_3152_begin_0, end = var_3152_end_0, end_mask = var_3152_end_mask_0, x = x_5_cast_fp16)[name = string("op_3152_cast_fp16")];
            tensor<int32, [4]> var_3156_begin_0 = const()[name = string("op_3156_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256576)))];
            tensor<int32, [4]> var_3156_end_0 = const()[name = string("op_3156_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256704)))];
            tensor<bool, [4]> var_3156_end_mask_0 = const()[name = string("op_3156_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3156_cast_fp16 = slice_by_index(begin = var_3156_begin_0, end = var_3156_end_0, end_mask = var_3156_end_mask_0, x = x_5_cast_fp16)[name = string("op_3156_cast_fp16")];
            tensor<int32, [4]> var_3160_begin_0 = const()[name = string("op_3160_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256832)))];
            tensor<int32, [4]> var_3160_end_0 = const()[name = string("op_3160_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256960)))];
            tensor<bool, [4]> var_3160_end_mask_0 = const()[name = string("op_3160_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3160_cast_fp16 = slice_by_index(begin = var_3160_begin_0, end = var_3160_end_0, end_mask = var_3160_end_mask_0, x = x_5_cast_fp16)[name = string("op_3160_cast_fp16")];
            tensor<int32, [4]> var_3164_begin_0 = const()[name = string("op_3164_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257088)))];
            tensor<int32, [4]> var_3164_end_0 = const()[name = string("op_3164_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257216)))];
            tensor<bool, [4]> var_3164_end_mask_0 = const()[name = string("op_3164_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3164_cast_fp16 = slice_by_index(begin = var_3164_begin_0, end = var_3164_end_0, end_mask = var_3164_end_mask_0, x = x_5_cast_fp16)[name = string("op_3164_cast_fp16")];
            string input_161_pad_type_0 = const()[name = string("input_161_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_161_strides_0 = const()[name = string("input_161_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_161_pad_0 = const()[name = string("input_161_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257344)))];
            tensor<int32, [2]> input_161_dilations_0 = const()[name = string("input_161_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_161_groups_0 = const()[name = string("input_161_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_151_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257472))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261632))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261824)))];
            tensor<fp16, [64]> const_152_to_fp16 = const()[name = string("const_152_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261952)))];
            tensor<fp16, [1, 64, 32, 32]> input_163_cast_fp16 = conv(bias = const_152_to_fp16, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_151_to_fp16, x = var_3156_cast_fp16)[name = string("input_163_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_165_cast_fp16 = relu(x = input_163_cast_fp16)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262144)))];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_153_to_fp16 = const()[name = string("const_153_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262272)))];
            tensor<fp16, [64]> const_154_to_fp16 = const()[name = string("const_154_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265536)))];
            tensor<fp16, [1, 64, 32, 32]> input_169_cast_fp16 = conv(bias = const_154_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_153_to_fp16, x = input_165_cast_fp16)[name = string("input_169_cast_fp16")];
            string input_171_pad_type_0 = const()[name = string("input_171_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_171_strides_0 = const()[name = string("input_171_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_171_pad_0 = const()[name = string("input_171_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265728)))];
            tensor<int32, [2]> input_171_dilations_0 = const()[name = string("input_171_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_171_groups_0 = const()[name = string("input_171_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_155_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265856))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270016))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270208)))];
            tensor<fp16, [64]> const_156_to_fp16 = const()[name = string("const_156_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270336)))];
            tensor<fp16, [1, 64, 32, 32]> input_173_cast_fp16 = conv(bias = const_156_to_fp16, dilations = input_171_dilations_0, groups = input_171_groups_0, pad = input_171_pad_0, pad_type = input_171_pad_type_0, strides = input_171_strides_0, weight = const_155_to_fp16, x = input_169_cast_fp16)[name = string("input_173_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_5_cast_fp16 = relu(x = input_173_cast_fp16)[name = string("out1_5_cast_fp16")];
            string input_177_pad_type_0 = const()[name = string("input_177_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_177_strides_0 = const()[name = string("input_177_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_177_pad_0 = const()[name = string("input_177_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270528)))];
            tensor<int32, [2]> input_177_dilations_0 = const()[name = string("input_177_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_177_groups_0 = const()[name = string("input_177_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_157_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270656))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274816))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275008)))];
            tensor<fp16, [64]> const_158_to_fp16 = const()[name = string("const_158_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275136)))];
            tensor<fp16, [1, 64, 32, 32]> input_179_cast_fp16 = conv(bias = const_158_to_fp16, dilations = input_177_dilations_0, groups = input_177_groups_0, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = input_177_strides_0, weight = const_157_to_fp16, x = var_3160_cast_fp16)[name = string("input_179_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_181_cast_fp16 = relu(x = input_179_cast_fp16)[name = string("input_181_cast_fp16")];
            string input_183_pad_type_0 = const()[name = string("input_183_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_183_pad_0 = const()[name = string("input_183_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275328)))];
            int32 input_183_groups_0 = const()[name = string("input_183_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_183_strides_0 = const()[name = string("input_183_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_183_dilations_0 = const()[name = string("input_183_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_159_to_fp16 = const()[name = string("const_159_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275456)))];
            tensor<fp16, [64]> const_160_to_fp16 = const()[name = string("const_160_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278720)))];
            tensor<fp16, [1, 64, 32, 32]> input_185_cast_fp16 = conv(bias = const_160_to_fp16, dilations = input_183_dilations_0, groups = input_183_groups_0, pad = input_183_pad_0, pad_type = input_183_pad_type_0, strides = input_183_strides_0, weight = const_159_to_fp16, x = input_181_cast_fp16)[name = string("input_185_cast_fp16")];
            string input_187_pad_type_0 = const()[name = string("input_187_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_187_strides_0 = const()[name = string("input_187_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_187_pad_0 = const()[name = string("input_187_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278912)))];
            tensor<int32, [2]> input_187_dilations_0 = const()[name = string("input_187_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_187_groups_0 = const()[name = string("input_187_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_161_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(279040))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283200))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283392)))];
            tensor<fp16, [64]> const_162_to_fp16 = const()[name = string("const_162_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283520)))];
            tensor<fp16, [1, 64, 32, 32]> input_189_cast_fp16 = conv(bias = const_162_to_fp16, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = const_161_to_fp16, x = input_185_cast_fp16)[name = string("input_189_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_5_cast_fp16 = relu(x = input_189_cast_fp16)[name = string("out2_5_cast_fp16")];
            string input_193_pad_type_0 = const()[name = string("input_193_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_193_strides_0 = const()[name = string("input_193_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_193_pad_0 = const()[name = string("input_193_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283712)))];
            tensor<int32, [2]> input_193_dilations_0 = const()[name = string("input_193_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_193_groups_0 = const()[name = string("input_193_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_163_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283840))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288000))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288192)))];
            tensor<fp16, [64]> const_164_to_fp16 = const()[name = string("const_164_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288320)))];
            tensor<fp16, [1, 64, 32, 32]> input_195_cast_fp16 = conv(bias = const_164_to_fp16, dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = const_163_to_fp16, x = var_3164_cast_fp16)[name = string("input_195_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_197_cast_fp16 = relu(x = input_195_cast_fp16)[name = string("input_197_cast_fp16")];
            string input_199_pad_type_0 = const()[name = string("input_199_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_199_pad_0 = const()[name = string("input_199_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288512)))];
            int32 input_199_groups_0 = const()[name = string("input_199_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_199_strides_0 = const()[name = string("input_199_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_199_dilations_0 = const()[name = string("input_199_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_165_to_fp16 = const()[name = string("const_165_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288640)))];
            tensor<fp16, [64]> const_166_to_fp16 = const()[name = string("const_166_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(291904)))];
            tensor<fp16, [1, 64, 32, 32]> input_201_cast_fp16 = conv(bias = const_166_to_fp16, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_165_to_fp16, x = input_197_cast_fp16)[name = string("input_201_cast_fp16")];
            string input_203_pad_type_0 = const()[name = string("input_203_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_203_strides_0 = const()[name = string("input_203_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_203_pad_0 = const()[name = string("input_203_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(292096)))];
            tensor<int32, [2]> input_203_dilations_0 = const()[name = string("input_203_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_203_groups_0 = const()[name = string("input_203_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_167_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(292224))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296384))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296576)))];
            tensor<fp16, [64]> const_168_to_fp16 = const()[name = string("const_168_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296704)))];
            tensor<fp16, [1, 64, 32, 32]> input_205_cast_fp16 = conv(bias = const_168_to_fp16, dilations = input_203_dilations_0, groups = input_203_groups_0, pad = input_203_pad_0, pad_type = input_203_pad_type_0, strides = input_203_strides_0, weight = const_167_to_fp16, x = input_201_cast_fp16)[name = string("input_205_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_5_cast_fp16 = relu(x = input_205_cast_fp16)[name = string("out3_5_cast_fp16")];
            bool input_207_interleave_0 = const()[name = string("input_207_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_207_cast_fp16 = concat(axis = var_86, interleave = input_207_interleave_0, values = (var_3152_cast_fp16, out1_5_cast_fp16, out2_5_cast_fp16, out3_5_cast_fp16))[name = string("input_207_cast_fp16")];
            string input_209_pad_type_0 = const()[name = string("input_209_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_209_strides_0 = const()[name = string("input_209_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_209_pad_0 = const()[name = string("input_209_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296896)))];
            tensor<int32, [2]> input_209_dilations_0 = const()[name = string("input_209_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_209_groups_0 = const()[name = string("input_209_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_169_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(297024))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(362624))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(363200)))];
            tensor<fp16, [256]> const_170_to_fp16 = const()[name = string("const_170_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(363520)))];
            tensor<fp16, [1, 256, 32, 32]> input_211_cast_fp16 = conv(bias = const_170_to_fp16, dilations = input_209_dilations_0, groups = input_209_groups_0, pad = input_209_pad_0, pad_type = input_209_pad_type_0, strides = input_209_strides_0, weight = const_169_to_fp16, x = input_207_cast_fp16)[name = string("input_211_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_213_cast_fp16 = relu(x = input_211_cast_fp16)[name = string("input_213_cast_fp16")];
            string input_215_pad_type_0 = const()[name = string("input_215_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_215_pad_0 = const()[name = string("input_215_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(364096)))];
            int32 input_215_groups_0 = const()[name = string("input_215_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_215_strides_0 = const()[name = string("input_215_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_215_dilations_0 = const()[name = string("input_215_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_171_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(364224))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(370688))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(371264)))];
            tensor<fp16, [256]> const_172_to_fp16 = const()[name = string("const_172_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(371584)))];
            tensor<fp16, [1, 256, 32, 32]> input_217_cast_fp16 = conv(bias = const_172_to_fp16, dilations = input_215_dilations_0, groups = input_215_groups_0, pad = input_215_pad_0, pad_type = input_215_pad_type_0, strides = input_215_strides_0, weight = const_171_to_fp16, x = input_213_cast_fp16)[name = string("input_217_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_219_cast_fp16 = relu(x = input_217_cast_fp16)[name = string("input_219_cast_fp16")];
            string input_221_pad_type_0 = const()[name = string("input_221_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_221_strides_0 = const()[name = string("input_221_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_221_pad_0 = const()[name = string("input_221_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(372160)))];
            tensor<int32, [2]> input_221_dilations_0 = const()[name = string("input_221_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_221_groups_0 = const()[name = string("input_221_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_173_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(372288))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(437888))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(438464)))];
            tensor<fp16, [256]> const_174_to_fp16 = const()[name = string("const_174_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(438784)))];
            tensor<fp16, [1, 256, 32, 32]> y_3_cast_fp16 = conv(bias = const_174_to_fp16, dilations = input_221_dilations_0, groups = input_221_groups_0, pad = input_221_pad_0, pad_type = input_221_pad_type_0, strides = input_221_strides_0, weight = const_173_to_fp16, x = input_219_cast_fp16)[name = string("y_3_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_7_cast_fp16 = add(x = input_207_cast_fp16, y = y_3_cast_fp16)[name = string("x_7_cast_fp16")];
            tensor<int32, [4]> var_3264_begin_0 = const()[name = string("op_3264_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439360)))];
            tensor<int32, [4]> var_3264_end_0 = const()[name = string("op_3264_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439488)))];
            tensor<bool, [4]> var_3264_end_mask_0 = const()[name = string("op_3264_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3264_cast_fp16 = slice_by_index(begin = var_3264_begin_0, end = var_3264_end_0, end_mask = var_3264_end_mask_0, x = x_7_cast_fp16)[name = string("op_3264_cast_fp16")];
            tensor<int32, [4]> var_3268_begin_0 = const()[name = string("op_3268_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439616)))];
            tensor<int32, [4]> var_3268_end_0 = const()[name = string("op_3268_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439744)))];
            tensor<bool, [4]> var_3268_end_mask_0 = const()[name = string("op_3268_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3268_cast_fp16 = slice_by_index(begin = var_3268_begin_0, end = var_3268_end_0, end_mask = var_3268_end_mask_0, x = x_7_cast_fp16)[name = string("op_3268_cast_fp16")];
            tensor<int32, [4]> var_3272_begin_0 = const()[name = string("op_3272_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439872)))];
            tensor<int32, [4]> var_3272_end_0 = const()[name = string("op_3272_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440000)))];
            tensor<bool, [4]> var_3272_end_mask_0 = const()[name = string("op_3272_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3272_cast_fp16 = slice_by_index(begin = var_3272_begin_0, end = var_3272_end_0, end_mask = var_3272_end_mask_0, x = x_7_cast_fp16)[name = string("op_3272_cast_fp16")];
            tensor<int32, [4]> var_3276_begin_0 = const()[name = string("op_3276_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440128)))];
            tensor<int32, [4]> var_3276_end_0 = const()[name = string("op_3276_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440256)))];
            tensor<bool, [4]> var_3276_end_mask_0 = const()[name = string("op_3276_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3276_cast_fp16 = slice_by_index(begin = var_3276_begin_0, end = var_3276_end_0, end_mask = var_3276_end_mask_0, x = x_7_cast_fp16)[name = string("op_3276_cast_fp16")];
            string input_225_pad_type_0 = const()[name = string("input_225_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_225_strides_0 = const()[name = string("input_225_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_225_pad_0 = const()[name = string("input_225_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440384)))];
            tensor<int32, [2]> input_225_dilations_0 = const()[name = string("input_225_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_225_groups_0 = const()[name = string("input_225_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_175_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440512))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444672))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444864)))];
            tensor<fp16, [64]> const_176_to_fp16 = const()[name = string("const_176_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444992)))];
            tensor<fp16, [1, 64, 32, 32]> input_227_cast_fp16 = conv(bias = const_176_to_fp16, dilations = input_225_dilations_0, groups = input_225_groups_0, pad = input_225_pad_0, pad_type = input_225_pad_type_0, strides = input_225_strides_0, weight = const_175_to_fp16, x = var_3268_cast_fp16)[name = string("input_227_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_229_cast_fp16 = relu(x = input_227_cast_fp16)[name = string("input_229_cast_fp16")];
            string input_231_pad_type_0 = const()[name = string("input_231_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_231_pad_0 = const()[name = string("input_231_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(445184)))];
            int32 input_231_groups_0 = const()[name = string("input_231_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_231_strides_0 = const()[name = string("input_231_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_231_dilations_0 = const()[name = string("input_231_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_177_to_fp16 = const()[name = string("const_177_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(445312)))];
            tensor<fp16, [64]> const_178_to_fp16 = const()[name = string("const_178_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448576)))];
            tensor<fp16, [1, 64, 32, 32]> input_233_cast_fp16 = conv(bias = const_178_to_fp16, dilations = input_231_dilations_0, groups = input_231_groups_0, pad = input_231_pad_0, pad_type = input_231_pad_type_0, strides = input_231_strides_0, weight = const_177_to_fp16, x = input_229_cast_fp16)[name = string("input_233_cast_fp16")];
            string input_235_pad_type_0 = const()[name = string("input_235_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_235_strides_0 = const()[name = string("input_235_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_235_pad_0 = const()[name = string("input_235_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448768)))];
            tensor<int32, [2]> input_235_dilations_0 = const()[name = string("input_235_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_235_groups_0 = const()[name = string("input_235_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_179_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448896))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453056))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453248)))];
            tensor<fp16, [64]> const_180_to_fp16 = const()[name = string("const_180_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453376)))];
            tensor<fp16, [1, 64, 32, 32]> input_237_cast_fp16 = conv(bias = const_180_to_fp16, dilations = input_235_dilations_0, groups = input_235_groups_0, pad = input_235_pad_0, pad_type = input_235_pad_type_0, strides = input_235_strides_0, weight = const_179_to_fp16, x = input_233_cast_fp16)[name = string("input_237_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_7_cast_fp16 = relu(x = input_237_cast_fp16)[name = string("out1_7_cast_fp16")];
            string input_241_pad_type_0 = const()[name = string("input_241_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_241_strides_0 = const()[name = string("input_241_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_241_pad_0 = const()[name = string("input_241_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453568)))];
            tensor<int32, [2]> input_241_dilations_0 = const()[name = string("input_241_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_241_groups_0 = const()[name = string("input_241_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_181_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453696))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(457856))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458048)))];
            tensor<fp16, [64]> const_182_to_fp16 = const()[name = string("const_182_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458176)))];
            tensor<fp16, [1, 64, 32, 32]> input_243_cast_fp16 = conv(bias = const_182_to_fp16, dilations = input_241_dilations_0, groups = input_241_groups_0, pad = input_241_pad_0, pad_type = input_241_pad_type_0, strides = input_241_strides_0, weight = const_181_to_fp16, x = var_3272_cast_fp16)[name = string("input_243_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_245_cast_fp16 = relu(x = input_243_cast_fp16)[name = string("input_245_cast_fp16")];
            string input_247_pad_type_0 = const()[name = string("input_247_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_247_pad_0 = const()[name = string("input_247_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458368)))];
            int32 input_247_groups_0 = const()[name = string("input_247_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_247_strides_0 = const()[name = string("input_247_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_247_dilations_0 = const()[name = string("input_247_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_183_to_fp16 = const()[name = string("const_183_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458496)))];
            tensor<fp16, [64]> const_184_to_fp16 = const()[name = string("const_184_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(461760)))];
            tensor<fp16, [1, 64, 32, 32]> input_249_cast_fp16 = conv(bias = const_184_to_fp16, dilations = input_247_dilations_0, groups = input_247_groups_0, pad = input_247_pad_0, pad_type = input_247_pad_type_0, strides = input_247_strides_0, weight = const_183_to_fp16, x = input_245_cast_fp16)[name = string("input_249_cast_fp16")];
            string input_251_pad_type_0 = const()[name = string("input_251_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_251_strides_0 = const()[name = string("input_251_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_251_pad_0 = const()[name = string("input_251_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(461952)))];
            tensor<int32, [2]> input_251_dilations_0 = const()[name = string("input_251_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_251_groups_0 = const()[name = string("input_251_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_185_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(462080))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466240))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466432)))];
            tensor<fp16, [64]> const_186_to_fp16 = const()[name = string("const_186_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466560)))];
            tensor<fp16, [1, 64, 32, 32]> input_253_cast_fp16 = conv(bias = const_186_to_fp16, dilations = input_251_dilations_0, groups = input_251_groups_0, pad = input_251_pad_0, pad_type = input_251_pad_type_0, strides = input_251_strides_0, weight = const_185_to_fp16, x = input_249_cast_fp16)[name = string("input_253_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_7_cast_fp16 = relu(x = input_253_cast_fp16)[name = string("out2_7_cast_fp16")];
            string input_257_pad_type_0 = const()[name = string("input_257_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_257_strides_0 = const()[name = string("input_257_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_257_pad_0 = const()[name = string("input_257_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466752)))];
            tensor<int32, [2]> input_257_dilations_0 = const()[name = string("input_257_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_257_groups_0 = const()[name = string("input_257_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_187_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466880))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471040))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471232)))];
            tensor<fp16, [64]> const_188_to_fp16 = const()[name = string("const_188_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471360)))];
            tensor<fp16, [1, 64, 32, 32]> input_259_cast_fp16 = conv(bias = const_188_to_fp16, dilations = input_257_dilations_0, groups = input_257_groups_0, pad = input_257_pad_0, pad_type = input_257_pad_type_0, strides = input_257_strides_0, weight = const_187_to_fp16, x = var_3276_cast_fp16)[name = string("input_259_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_261_cast_fp16 = relu(x = input_259_cast_fp16)[name = string("input_261_cast_fp16")];
            string input_263_pad_type_0 = const()[name = string("input_263_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_263_pad_0 = const()[name = string("input_263_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471552)))];
            int32 input_263_groups_0 = const()[name = string("input_263_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_263_strides_0 = const()[name = string("input_263_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_263_dilations_0 = const()[name = string("input_263_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_189_to_fp16 = const()[name = string("const_189_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471680)))];
            tensor<fp16, [64]> const_190_to_fp16 = const()[name = string("const_190_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(474944)))];
            tensor<fp16, [1, 64, 32, 32]> input_265_cast_fp16 = conv(bias = const_190_to_fp16, dilations = input_263_dilations_0, groups = input_263_groups_0, pad = input_263_pad_0, pad_type = input_263_pad_type_0, strides = input_263_strides_0, weight = const_189_to_fp16, x = input_261_cast_fp16)[name = string("input_265_cast_fp16")];
            string input_267_pad_type_0 = const()[name = string("input_267_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_267_strides_0 = const()[name = string("input_267_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_267_pad_0 = const()[name = string("input_267_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(475136)))];
            tensor<int32, [2]> input_267_dilations_0 = const()[name = string("input_267_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_267_groups_0 = const()[name = string("input_267_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_191_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(475264))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479424))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479616)))];
            tensor<fp16, [64]> const_192_to_fp16 = const()[name = string("const_192_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479744)))];
            tensor<fp16, [1, 64, 32, 32]> input_269_cast_fp16 = conv(bias = const_192_to_fp16, dilations = input_267_dilations_0, groups = input_267_groups_0, pad = input_267_pad_0, pad_type = input_267_pad_type_0, strides = input_267_strides_0, weight = const_191_to_fp16, x = input_265_cast_fp16)[name = string("input_269_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_7_cast_fp16 = relu(x = input_269_cast_fp16)[name = string("out3_7_cast_fp16")];
            bool input_271_interleave_0 = const()[name = string("input_271_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_271_cast_fp16 = concat(axis = var_86, interleave = input_271_interleave_0, values = (var_3264_cast_fp16, out1_7_cast_fp16, out2_7_cast_fp16, out3_7_cast_fp16))[name = string("input_271_cast_fp16")];
            string input_273_pad_type_0 = const()[name = string("input_273_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_273_strides_0 = const()[name = string("input_273_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_273_pad_0 = const()[name = string("input_273_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479936)))];
            tensor<int32, [2]> input_273_dilations_0 = const()[name = string("input_273_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_273_groups_0 = const()[name = string("input_273_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_193_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(480064))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(545664))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(546240)))];
            tensor<fp16, [256]> const_194_to_fp16 = const()[name = string("const_194_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(546560)))];
            tensor<fp16, [1, 256, 32, 32]> input_275_cast_fp16 = conv(bias = const_194_to_fp16, dilations = input_273_dilations_0, groups = input_273_groups_0, pad = input_273_pad_0, pad_type = input_273_pad_type_0, strides = input_273_strides_0, weight = const_193_to_fp16, x = input_271_cast_fp16)[name = string("input_275_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_277_cast_fp16 = relu(x = input_275_cast_fp16)[name = string("input_277_cast_fp16")];
            string input_279_pad_type_0 = const()[name = string("input_279_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_279_pad_0 = const()[name = string("input_279_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(547136)))];
            int32 input_279_groups_0 = const()[name = string("input_279_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_279_strides_0 = const()[name = string("input_279_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_279_dilations_0 = const()[name = string("input_279_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_195_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(547264))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(553728))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(554304)))];
            tensor<fp16, [256]> const_196_to_fp16 = const()[name = string("const_196_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(554624)))];
            tensor<fp16, [1, 256, 32, 32]> input_281_cast_fp16 = conv(bias = const_196_to_fp16, dilations = input_279_dilations_0, groups = input_279_groups_0, pad = input_279_pad_0, pad_type = input_279_pad_type_0, strides = input_279_strides_0, weight = const_195_to_fp16, x = input_277_cast_fp16)[name = string("input_281_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_283_cast_fp16 = relu(x = input_281_cast_fp16)[name = string("input_283_cast_fp16")];
            string input_285_pad_type_0 = const()[name = string("input_285_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_285_strides_0 = const()[name = string("input_285_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_285_pad_0 = const()[name = string("input_285_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(555200)))];
            tensor<int32, [2]> input_285_dilations_0 = const()[name = string("input_285_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_285_groups_0 = const()[name = string("input_285_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_197_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(555328))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(620928))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(621504)))];
            tensor<fp16, [256]> const_198_to_fp16 = const()[name = string("const_198_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(621824)))];
            tensor<fp16, [1, 256, 32, 32]> y_5_cast_fp16 = conv(bias = const_198_to_fp16, dilations = input_285_dilations_0, groups = input_285_groups_0, pad = input_285_pad_0, pad_type = input_285_pad_type_0, strides = input_285_strides_0, weight = const_197_to_fp16, x = input_283_cast_fp16)[name = string("y_5_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_9_cast_fp16 = add(x = input_271_cast_fp16, y = y_5_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<int32, [4]> var_3376_begin_0 = const()[name = string("op_3376_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622400)))];
            tensor<int32, [4]> var_3376_end_0 = const()[name = string("op_3376_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622528)))];
            tensor<bool, [4]> var_3376_end_mask_0 = const()[name = string("op_3376_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3376_cast_fp16 = slice_by_index(begin = var_3376_begin_0, end = var_3376_end_0, end_mask = var_3376_end_mask_0, x = x_9_cast_fp16)[name = string("op_3376_cast_fp16")];
            tensor<int32, [4]> var_3380_begin_0 = const()[name = string("op_3380_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622656)))];
            tensor<int32, [4]> var_3380_end_0 = const()[name = string("op_3380_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622784)))];
            tensor<bool, [4]> var_3380_end_mask_0 = const()[name = string("op_3380_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3380_cast_fp16 = slice_by_index(begin = var_3380_begin_0, end = var_3380_end_0, end_mask = var_3380_end_mask_0, x = x_9_cast_fp16)[name = string("op_3380_cast_fp16")];
            tensor<int32, [4]> var_3384_begin_0 = const()[name = string("op_3384_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622912)))];
            tensor<int32, [4]> var_3384_end_0 = const()[name = string("op_3384_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623040)))];
            tensor<bool, [4]> var_3384_end_mask_0 = const()[name = string("op_3384_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3384_cast_fp16 = slice_by_index(begin = var_3384_begin_0, end = var_3384_end_0, end_mask = var_3384_end_mask_0, x = x_9_cast_fp16)[name = string("op_3384_cast_fp16")];
            tensor<int32, [4]> var_3388_begin_0 = const()[name = string("op_3388_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623168)))];
            tensor<int32, [4]> var_3388_end_0 = const()[name = string("op_3388_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623296)))];
            tensor<bool, [4]> var_3388_end_mask_0 = const()[name = string("op_3388_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3388_cast_fp16 = slice_by_index(begin = var_3388_begin_0, end = var_3388_end_0, end_mask = var_3388_end_mask_0, x = x_9_cast_fp16)[name = string("op_3388_cast_fp16")];
            string input_289_pad_type_0 = const()[name = string("input_289_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_289_strides_0 = const()[name = string("input_289_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_289_pad_0 = const()[name = string("input_289_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623424)))];
            tensor<int32, [2]> input_289_dilations_0 = const()[name = string("input_289_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_289_groups_0 = const()[name = string("input_289_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_199_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623552))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627712))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627904)))];
            tensor<fp16, [64]> const_200_to_fp16 = const()[name = string("const_200_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628032)))];
            tensor<fp16, [1, 64, 32, 32]> input_291_cast_fp16 = conv(bias = const_200_to_fp16, dilations = input_289_dilations_0, groups = input_289_groups_0, pad = input_289_pad_0, pad_type = input_289_pad_type_0, strides = input_289_strides_0, weight = const_199_to_fp16, x = var_3380_cast_fp16)[name = string("input_291_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_293_cast_fp16 = relu(x = input_291_cast_fp16)[name = string("input_293_cast_fp16")];
            string input_295_pad_type_0 = const()[name = string("input_295_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_295_pad_0 = const()[name = string("input_295_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628224)))];
            int32 input_295_groups_0 = const()[name = string("input_295_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_295_strides_0 = const()[name = string("input_295_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_295_dilations_0 = const()[name = string("input_295_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_201_to_fp16 = const()[name = string("const_201_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628352)))];
            tensor<fp16, [64]> const_202_to_fp16 = const()[name = string("const_202_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631616)))];
            tensor<fp16, [1, 64, 32, 32]> input_297_cast_fp16 = conv(bias = const_202_to_fp16, dilations = input_295_dilations_0, groups = input_295_groups_0, pad = input_295_pad_0, pad_type = input_295_pad_type_0, strides = input_295_strides_0, weight = const_201_to_fp16, x = input_293_cast_fp16)[name = string("input_297_cast_fp16")];
            string input_299_pad_type_0 = const()[name = string("input_299_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_299_strides_0 = const()[name = string("input_299_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_299_pad_0 = const()[name = string("input_299_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631808)))];
            tensor<int32, [2]> input_299_dilations_0 = const()[name = string("input_299_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_299_groups_0 = const()[name = string("input_299_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_203_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631936))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636096))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636288)))];
            tensor<fp16, [64]> const_204_to_fp16 = const()[name = string("const_204_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636416)))];
            tensor<fp16, [1, 64, 32, 32]> input_301_cast_fp16 = conv(bias = const_204_to_fp16, dilations = input_299_dilations_0, groups = input_299_groups_0, pad = input_299_pad_0, pad_type = input_299_pad_type_0, strides = input_299_strides_0, weight = const_203_to_fp16, x = input_297_cast_fp16)[name = string("input_301_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_9_cast_fp16 = relu(x = input_301_cast_fp16)[name = string("out1_9_cast_fp16")];
            string input_305_pad_type_0 = const()[name = string("input_305_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_305_strides_0 = const()[name = string("input_305_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_305_pad_0 = const()[name = string("input_305_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636608)))];
            tensor<int32, [2]> input_305_dilations_0 = const()[name = string("input_305_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_305_groups_0 = const()[name = string("input_305_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_205_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636736))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(640896))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641088)))];
            tensor<fp16, [64]> const_206_to_fp16 = const()[name = string("const_206_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641216)))];
            tensor<fp16, [1, 64, 32, 32]> input_307_cast_fp16 = conv(bias = const_206_to_fp16, dilations = input_305_dilations_0, groups = input_305_groups_0, pad = input_305_pad_0, pad_type = input_305_pad_type_0, strides = input_305_strides_0, weight = const_205_to_fp16, x = var_3384_cast_fp16)[name = string("input_307_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_309_cast_fp16 = relu(x = input_307_cast_fp16)[name = string("input_309_cast_fp16")];
            string input_311_pad_type_0 = const()[name = string("input_311_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_311_pad_0 = const()[name = string("input_311_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641408)))];
            int32 input_311_groups_0 = const()[name = string("input_311_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_311_strides_0 = const()[name = string("input_311_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_311_dilations_0 = const()[name = string("input_311_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_207_to_fp16 = const()[name = string("const_207_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641536)))];
            tensor<fp16, [64]> const_208_to_fp16 = const()[name = string("const_208_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(644800)))];
            tensor<fp16, [1, 64, 32, 32]> input_313_cast_fp16 = conv(bias = const_208_to_fp16, dilations = input_311_dilations_0, groups = input_311_groups_0, pad = input_311_pad_0, pad_type = input_311_pad_type_0, strides = input_311_strides_0, weight = const_207_to_fp16, x = input_309_cast_fp16)[name = string("input_313_cast_fp16")];
            string input_315_pad_type_0 = const()[name = string("input_315_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_315_strides_0 = const()[name = string("input_315_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_315_pad_0 = const()[name = string("input_315_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(644992)))];
            tensor<int32, [2]> input_315_dilations_0 = const()[name = string("input_315_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_315_groups_0 = const()[name = string("input_315_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_209_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(645120))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649280))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649472)))];
            tensor<fp16, [64]> const_210_to_fp16 = const()[name = string("const_210_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649600)))];
            tensor<fp16, [1, 64, 32, 32]> input_317_cast_fp16 = conv(bias = const_210_to_fp16, dilations = input_315_dilations_0, groups = input_315_groups_0, pad = input_315_pad_0, pad_type = input_315_pad_type_0, strides = input_315_strides_0, weight = const_209_to_fp16, x = input_313_cast_fp16)[name = string("input_317_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_9_cast_fp16 = relu(x = input_317_cast_fp16)[name = string("out2_9_cast_fp16")];
            string input_321_pad_type_0 = const()[name = string("input_321_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_321_strides_0 = const()[name = string("input_321_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_321_pad_0 = const()[name = string("input_321_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649792)))];
            tensor<int32, [2]> input_321_dilations_0 = const()[name = string("input_321_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_321_groups_0 = const()[name = string("input_321_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_211_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649920))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654080))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654272)))];
            tensor<fp16, [64]> const_212_to_fp16 = const()[name = string("const_212_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654400)))];
            tensor<fp16, [1, 64, 32, 32]> input_323_cast_fp16 = conv(bias = const_212_to_fp16, dilations = input_321_dilations_0, groups = input_321_groups_0, pad = input_321_pad_0, pad_type = input_321_pad_type_0, strides = input_321_strides_0, weight = const_211_to_fp16, x = var_3388_cast_fp16)[name = string("input_323_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_325_cast_fp16 = relu(x = input_323_cast_fp16)[name = string("input_325_cast_fp16")];
            string input_327_pad_type_0 = const()[name = string("input_327_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_327_pad_0 = const()[name = string("input_327_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654592)))];
            int32 input_327_groups_0 = const()[name = string("input_327_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_327_strides_0 = const()[name = string("input_327_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_327_dilations_0 = const()[name = string("input_327_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_213_to_fp16 = const()[name = string("const_213_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654720)))];
            tensor<fp16, [64]> const_214_to_fp16 = const()[name = string("const_214_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(657984)))];
            tensor<fp16, [1, 64, 32, 32]> input_329_cast_fp16 = conv(bias = const_214_to_fp16, dilations = input_327_dilations_0, groups = input_327_groups_0, pad = input_327_pad_0, pad_type = input_327_pad_type_0, strides = input_327_strides_0, weight = const_213_to_fp16, x = input_325_cast_fp16)[name = string("input_329_cast_fp16")];
            string input_331_pad_type_0 = const()[name = string("input_331_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_331_strides_0 = const()[name = string("input_331_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_331_pad_0 = const()[name = string("input_331_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658176)))];
            tensor<int32, [2]> input_331_dilations_0 = const()[name = string("input_331_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_331_groups_0 = const()[name = string("input_331_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_215_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658304))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662464))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662656)))];
            tensor<fp16, [64]> const_216_to_fp16 = const()[name = string("const_216_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662784)))];
            tensor<fp16, [1, 64, 32, 32]> input_333_cast_fp16 = conv(bias = const_216_to_fp16, dilations = input_331_dilations_0, groups = input_331_groups_0, pad = input_331_pad_0, pad_type = input_331_pad_type_0, strides = input_331_strides_0, weight = const_215_to_fp16, x = input_329_cast_fp16)[name = string("input_333_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_9_cast_fp16 = relu(x = input_333_cast_fp16)[name = string("out3_9_cast_fp16")];
            bool input_335_interleave_0 = const()[name = string("input_335_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_335_cast_fp16 = concat(axis = var_86, interleave = input_335_interleave_0, values = (var_3376_cast_fp16, out1_9_cast_fp16, out2_9_cast_fp16, out3_9_cast_fp16))[name = string("input_335_cast_fp16")];
            string input_337_pad_type_0 = const()[name = string("input_337_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_337_strides_0 = const()[name = string("input_337_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_337_pad_0 = const()[name = string("input_337_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662976)))];
            tensor<int32, [2]> input_337_dilations_0 = const()[name = string("input_337_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_337_groups_0 = const()[name = string("input_337_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_217_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(663104))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(728704))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729280)))];
            tensor<fp16, [256]> const_218_to_fp16 = const()[name = string("const_218_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729600)))];
            tensor<fp16, [1, 256, 32, 32]> input_339_cast_fp16 = conv(bias = const_218_to_fp16, dilations = input_337_dilations_0, groups = input_337_groups_0, pad = input_337_pad_0, pad_type = input_337_pad_type_0, strides = input_337_strides_0, weight = const_217_to_fp16, x = input_335_cast_fp16)[name = string("input_339_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_341_cast_fp16 = relu(x = input_339_cast_fp16)[name = string("input_341_cast_fp16")];
            string input_343_pad_type_0 = const()[name = string("input_343_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_343_pad_0 = const()[name = string("input_343_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(730176)))];
            int32 input_343_groups_0 = const()[name = string("input_343_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_343_strides_0 = const()[name = string("input_343_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_343_dilations_0 = const()[name = string("input_343_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_219_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(730304))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(736768))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(737344)))];
            tensor<fp16, [256]> const_220_to_fp16 = const()[name = string("const_220_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(737664)))];
            tensor<fp16, [1, 256, 32, 32]> input_345_cast_fp16 = conv(bias = const_220_to_fp16, dilations = input_343_dilations_0, groups = input_343_groups_0, pad = input_343_pad_0, pad_type = input_343_pad_type_0, strides = input_343_strides_0, weight = const_219_to_fp16, x = input_341_cast_fp16)[name = string("input_345_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_347_cast_fp16 = relu(x = input_345_cast_fp16)[name = string("input_347_cast_fp16")];
            string input_349_pad_type_0 = const()[name = string("input_349_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_349_strides_0 = const()[name = string("input_349_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_349_pad_0 = const()[name = string("input_349_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(738240)))];
            tensor<int32, [2]> input_349_dilations_0 = const()[name = string("input_349_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_349_groups_0 = const()[name = string("input_349_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_221_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(738368))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(803968))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(804544)))];
            tensor<fp16, [256]> const_222_to_fp16 = const()[name = string("const_222_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(804864)))];
            tensor<fp16, [1, 256, 32, 32]> y_7_cast_fp16 = conv(bias = const_222_to_fp16, dilations = input_349_dilations_0, groups = input_349_groups_0, pad = input_349_pad_0, pad_type = input_349_pad_type_0, strides = input_349_strides_0, weight = const_221_to_fp16, x = input_347_cast_fp16)[name = string("y_7_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_11_cast_fp16 = add(x = input_335_cast_fp16, y = y_7_cast_fp16)[name = string("x_11_cast_fp16")];
            tensor<int32, [4]> var_3488_begin_0 = const()[name = string("op_3488_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805440)))];
            tensor<int32, [4]> var_3488_end_0 = const()[name = string("op_3488_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805568)))];
            tensor<bool, [4]> var_3488_end_mask_0 = const()[name = string("op_3488_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3488_cast_fp16 = slice_by_index(begin = var_3488_begin_0, end = var_3488_end_0, end_mask = var_3488_end_mask_0, x = x_11_cast_fp16)[name = string("op_3488_cast_fp16")];
            tensor<int32, [4]> var_3492_begin_0 = const()[name = string("op_3492_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805696)))];
            tensor<int32, [4]> var_3492_end_0 = const()[name = string("op_3492_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805824)))];
            tensor<bool, [4]> var_3492_end_mask_0 = const()[name = string("op_3492_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3492_cast_fp16 = slice_by_index(begin = var_3492_begin_0, end = var_3492_end_0, end_mask = var_3492_end_mask_0, x = x_11_cast_fp16)[name = string("op_3492_cast_fp16")];
            tensor<int32, [4]> var_3496_begin_0 = const()[name = string("op_3496_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805952)))];
            tensor<int32, [4]> var_3496_end_0 = const()[name = string("op_3496_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806080)))];
            tensor<bool, [4]> var_3496_end_mask_0 = const()[name = string("op_3496_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3496_cast_fp16 = slice_by_index(begin = var_3496_begin_0, end = var_3496_end_0, end_mask = var_3496_end_mask_0, x = x_11_cast_fp16)[name = string("op_3496_cast_fp16")];
            tensor<int32, [4]> var_3500_begin_0 = const()[name = string("op_3500_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806208)))];
            tensor<int32, [4]> var_3500_end_0 = const()[name = string("op_3500_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806336)))];
            tensor<bool, [4]> var_3500_end_mask_0 = const()[name = string("op_3500_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3500_cast_fp16 = slice_by_index(begin = var_3500_begin_0, end = var_3500_end_0, end_mask = var_3500_end_mask_0, x = x_11_cast_fp16)[name = string("op_3500_cast_fp16")];
            string input_353_pad_type_0 = const()[name = string("input_353_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_353_strides_0 = const()[name = string("input_353_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_353_pad_0 = const()[name = string("input_353_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806464)))];
            tensor<int32, [2]> input_353_dilations_0 = const()[name = string("input_353_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_353_groups_0 = const()[name = string("input_353_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_223_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806592))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(810752))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(810944)))];
            tensor<fp16, [64]> const_224_to_fp16 = const()[name = string("const_224_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811072)))];
            tensor<fp16, [1, 64, 32, 32]> input_355_cast_fp16 = conv(bias = const_224_to_fp16, dilations = input_353_dilations_0, groups = input_353_groups_0, pad = input_353_pad_0, pad_type = input_353_pad_type_0, strides = input_353_strides_0, weight = const_223_to_fp16, x = var_3492_cast_fp16)[name = string("input_355_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_357_cast_fp16 = relu(x = input_355_cast_fp16)[name = string("input_357_cast_fp16")];
            string input_359_pad_type_0 = const()[name = string("input_359_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_359_pad_0 = const()[name = string("input_359_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811264)))];
            int32 input_359_groups_0 = const()[name = string("input_359_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_359_strides_0 = const()[name = string("input_359_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_359_dilations_0 = const()[name = string("input_359_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_225_to_fp16 = const()[name = string("const_225_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811392)))];
            tensor<fp16, [64]> const_226_to_fp16 = const()[name = string("const_226_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814656)))];
            tensor<fp16, [1, 64, 32, 32]> input_361_cast_fp16 = conv(bias = const_226_to_fp16, dilations = input_359_dilations_0, groups = input_359_groups_0, pad = input_359_pad_0, pad_type = input_359_pad_type_0, strides = input_359_strides_0, weight = const_225_to_fp16, x = input_357_cast_fp16)[name = string("input_361_cast_fp16")];
            string input_363_pad_type_0 = const()[name = string("input_363_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_363_strides_0 = const()[name = string("input_363_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_363_pad_0 = const()[name = string("input_363_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814848)))];
            tensor<int32, [2]> input_363_dilations_0 = const()[name = string("input_363_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_363_groups_0 = const()[name = string("input_363_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_227_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814976))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819136))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819328)))];
            tensor<fp16, [64]> const_228_to_fp16 = const()[name = string("const_228_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819456)))];
            tensor<fp16, [1, 64, 32, 32]> input_365_cast_fp16 = conv(bias = const_228_to_fp16, dilations = input_363_dilations_0, groups = input_363_groups_0, pad = input_363_pad_0, pad_type = input_363_pad_type_0, strides = input_363_strides_0, weight = const_227_to_fp16, x = input_361_cast_fp16)[name = string("input_365_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_11_cast_fp16 = relu(x = input_365_cast_fp16)[name = string("out1_11_cast_fp16")];
            string input_369_pad_type_0 = const()[name = string("input_369_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_369_strides_0 = const()[name = string("input_369_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_369_pad_0 = const()[name = string("input_369_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819648)))];
            tensor<int32, [2]> input_369_dilations_0 = const()[name = string("input_369_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_369_groups_0 = const()[name = string("input_369_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_229_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819776))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(823936))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824128)))];
            tensor<fp16, [64]> const_230_to_fp16 = const()[name = string("const_230_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824256)))];
            tensor<fp16, [1, 64, 32, 32]> input_371_cast_fp16 = conv(bias = const_230_to_fp16, dilations = input_369_dilations_0, groups = input_369_groups_0, pad = input_369_pad_0, pad_type = input_369_pad_type_0, strides = input_369_strides_0, weight = const_229_to_fp16, x = var_3496_cast_fp16)[name = string("input_371_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_373_cast_fp16 = relu(x = input_371_cast_fp16)[name = string("input_373_cast_fp16")];
            string input_375_pad_type_0 = const()[name = string("input_375_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_375_pad_0 = const()[name = string("input_375_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824448)))];
            int32 input_375_groups_0 = const()[name = string("input_375_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_375_strides_0 = const()[name = string("input_375_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_375_dilations_0 = const()[name = string("input_375_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_231_to_fp16 = const()[name = string("const_231_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824576)))];
            tensor<fp16, [64]> const_232_to_fp16 = const()[name = string("const_232_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(827840)))];
            tensor<fp16, [1, 64, 32, 32]> input_377_cast_fp16 = conv(bias = const_232_to_fp16, dilations = input_375_dilations_0, groups = input_375_groups_0, pad = input_375_pad_0, pad_type = input_375_pad_type_0, strides = input_375_strides_0, weight = const_231_to_fp16, x = input_373_cast_fp16)[name = string("input_377_cast_fp16")];
            string input_379_pad_type_0 = const()[name = string("input_379_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_379_strides_0 = const()[name = string("input_379_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_379_pad_0 = const()[name = string("input_379_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(828032)))];
            tensor<int32, [2]> input_379_dilations_0 = const()[name = string("input_379_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_379_groups_0 = const()[name = string("input_379_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_233_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(828160))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832320))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832512)))];
            tensor<fp16, [64]> const_234_to_fp16 = const()[name = string("const_234_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832640)))];
            tensor<fp16, [1, 64, 32, 32]> input_381_cast_fp16 = conv(bias = const_234_to_fp16, dilations = input_379_dilations_0, groups = input_379_groups_0, pad = input_379_pad_0, pad_type = input_379_pad_type_0, strides = input_379_strides_0, weight = const_233_to_fp16, x = input_377_cast_fp16)[name = string("input_381_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_11_cast_fp16 = relu(x = input_381_cast_fp16)[name = string("out2_11_cast_fp16")];
            string input_385_pad_type_0 = const()[name = string("input_385_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_385_strides_0 = const()[name = string("input_385_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_385_pad_0 = const()[name = string("input_385_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832832)))];
            tensor<int32, [2]> input_385_dilations_0 = const()[name = string("input_385_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_385_groups_0 = const()[name = string("input_385_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_235_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832960))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837120))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837312)))];
            tensor<fp16, [64]> const_236_to_fp16 = const()[name = string("const_236_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837440)))];
            tensor<fp16, [1, 64, 32, 32]> input_387_cast_fp16 = conv(bias = const_236_to_fp16, dilations = input_385_dilations_0, groups = input_385_groups_0, pad = input_385_pad_0, pad_type = input_385_pad_type_0, strides = input_385_strides_0, weight = const_235_to_fp16, x = var_3500_cast_fp16)[name = string("input_387_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_389_cast_fp16 = relu(x = input_387_cast_fp16)[name = string("input_389_cast_fp16")];
            string input_391_pad_type_0 = const()[name = string("input_391_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_391_pad_0 = const()[name = string("input_391_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837632)))];
            int32 input_391_groups_0 = const()[name = string("input_391_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_391_strides_0 = const()[name = string("input_391_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_391_dilations_0 = const()[name = string("input_391_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_237_to_fp16 = const()[name = string("const_237_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837760)))];
            tensor<fp16, [64]> const_238_to_fp16 = const()[name = string("const_238_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841024)))];
            tensor<fp16, [1, 64, 32, 32]> input_393_cast_fp16 = conv(bias = const_238_to_fp16, dilations = input_391_dilations_0, groups = input_391_groups_0, pad = input_391_pad_0, pad_type = input_391_pad_type_0, strides = input_391_strides_0, weight = const_237_to_fp16, x = input_389_cast_fp16)[name = string("input_393_cast_fp16")];
            string input_395_pad_type_0 = const()[name = string("input_395_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_395_strides_0 = const()[name = string("input_395_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_395_pad_0 = const()[name = string("input_395_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841216)))];
            tensor<int32, [2]> input_395_dilations_0 = const()[name = string("input_395_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_395_groups_0 = const()[name = string("input_395_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_239_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841344))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845504))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845696)))];
            tensor<fp16, [64]> const_240_to_fp16 = const()[name = string("const_240_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845824)))];
            tensor<fp16, [1, 64, 32, 32]> input_397_cast_fp16 = conv(bias = const_240_to_fp16, dilations = input_395_dilations_0, groups = input_395_groups_0, pad = input_395_pad_0, pad_type = input_395_pad_type_0, strides = input_395_strides_0, weight = const_239_to_fp16, x = input_393_cast_fp16)[name = string("input_397_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_11_cast_fp16 = relu(x = input_397_cast_fp16)[name = string("out3_11_cast_fp16")];
            bool input_399_interleave_0 = const()[name = string("input_399_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_399_cast_fp16 = concat(axis = var_86, interleave = input_399_interleave_0, values = (var_3488_cast_fp16, out1_11_cast_fp16, out2_11_cast_fp16, out3_11_cast_fp16))[name = string("input_399_cast_fp16")];
            string input_401_pad_type_0 = const()[name = string("input_401_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_401_strides_0 = const()[name = string("input_401_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_401_pad_0 = const()[name = string("input_401_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846016)))];
            tensor<int32, [2]> input_401_dilations_0 = const()[name = string("input_401_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_401_groups_0 = const()[name = string("input_401_groups_0"), val = int32(1)];
            tensor<fp16, [512, 256, 1, 1]> const_241_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846144))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(977280))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(978368)))];
            tensor<fp16, [512]> const_242_to_fp16 = const()[name = string("const_242_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(978944)))];
            tensor<fp16, [1, 512, 32, 32]> input_403_cast_fp16 = conv(bias = const_242_to_fp16, dilations = input_401_dilations_0, groups = input_401_groups_0, pad = input_401_pad_0, pad_type = input_401_pad_type_0, strides = input_401_strides_0, weight = const_241_to_fp16, x = input_399_cast_fp16)[name = string("input_403_cast_fp16")];
            tensor<fp16, [1, 512, 32, 32]> input_405_cast_fp16 = relu(x = input_403_cast_fp16)[name = string("input_405_cast_fp16")];
            string input_407_pad_type_0 = const()[name = string("input_407_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_407_pad_0 = const()[name = string("input_407_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(980032)))];
            tensor<int32, [2]> input_407_strides_0 = const()[name = string("input_407_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_407_groups_0 = const()[name = string("input_407_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_407_dilations_0 = const()[name = string("input_407_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [512, 1, 5, 5]> const_243_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(980160))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(993024))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(994112)))];
            tensor<fp16, [512]> const_244_to_fp16 = const()[name = string("const_244_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(994688)))];
            tensor<fp16, [1, 512, 16, 16]> input_409_cast_fp16 = conv(bias = const_244_to_fp16, dilations = input_407_dilations_0, groups = input_407_groups_0, pad = input_407_pad_0, pad_type = input_407_pad_type_0, strides = input_407_strides_0, weight = const_243_to_fp16, x = input_405_cast_fp16)[name = string("input_409_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_411_cast_fp16 = relu(x = input_409_cast_fp16)[name = string("input_411_cast_fp16")];
            string input_413_pad_type_0 = const()[name = string("input_413_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_413_strides_0 = const()[name = string("input_413_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_413_pad_0 = const()[name = string("input_413_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(995776)))];
            tensor<int32, [2]> input_413_dilations_0 = const()[name = string("input_413_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_413_groups_0 = const()[name = string("input_413_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_245_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(995904))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1258112))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1259200)))];
            tensor<fp16, [512]> const_246_to_fp16 = const()[name = string("const_246_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1259776)))];
            tensor<fp16, [1, 512, 16, 16]> x_13_cast_fp16 = conv(bias = const_246_to_fp16, dilations = input_413_dilations_0, groups = input_413_groups_0, pad = input_413_pad_0, pad_type = input_413_pad_type_0, strides = input_413_strides_0, weight = const_245_to_fp16, x = input_411_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<int32, [4]> var_3599_begin_0 = const()[name = string("op_3599_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1260864)))];
            tensor<int32, [4]> var_3599_end_0 = const()[name = string("op_3599_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1260992)))];
            tensor<bool, [4]> var_3599_end_mask_0 = const()[name = string("op_3599_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3599_cast_fp16 = slice_by_index(begin = var_3599_begin_0, end = var_3599_end_0, end_mask = var_3599_end_mask_0, x = x_13_cast_fp16)[name = string("op_3599_cast_fp16")];
            tensor<int32, [4]> var_3603_begin_0 = const()[name = string("op_3603_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261120)))];
            tensor<int32, [4]> var_3603_end_0 = const()[name = string("op_3603_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261248)))];
            tensor<bool, [4]> var_3603_end_mask_0 = const()[name = string("op_3603_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3603_cast_fp16 = slice_by_index(begin = var_3603_begin_0, end = var_3603_end_0, end_mask = var_3603_end_mask_0, x = x_13_cast_fp16)[name = string("op_3603_cast_fp16")];
            tensor<int32, [4]> var_3607_begin_0 = const()[name = string("op_3607_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261376)))];
            tensor<int32, [4]> var_3607_end_0 = const()[name = string("op_3607_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261504)))];
            tensor<bool, [4]> var_3607_end_mask_0 = const()[name = string("op_3607_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3607_cast_fp16 = slice_by_index(begin = var_3607_begin_0, end = var_3607_end_0, end_mask = var_3607_end_mask_0, x = x_13_cast_fp16)[name = string("op_3607_cast_fp16")];
            tensor<int32, [4]> var_3611_begin_0 = const()[name = string("op_3611_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261632)))];
            tensor<int32, [4]> var_3611_end_0 = const()[name = string("op_3611_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261760)))];
            tensor<bool, [4]> var_3611_end_mask_0 = const()[name = string("op_3611_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3611_cast_fp16 = slice_by_index(begin = var_3611_begin_0, end = var_3611_end_0, end_mask = var_3611_end_mask_0, x = x_13_cast_fp16)[name = string("op_3611_cast_fp16")];
            string input_417_pad_type_0 = const()[name = string("input_417_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_417_strides_0 = const()[name = string("input_417_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_417_pad_0 = const()[name = string("input_417_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261888)))];
            tensor<int32, [2]> input_417_dilations_0 = const()[name = string("input_417_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_417_groups_0 = const()[name = string("input_417_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_247_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1262016))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278464))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278784)))];
            tensor<fp16, [128]> const_248_to_fp16 = const()[name = string("const_248_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278976)))];
            tensor<fp16, [1, 128, 16, 16]> input_419_cast_fp16 = conv(bias = const_248_to_fp16, dilations = input_417_dilations_0, groups = input_417_groups_0, pad = input_417_pad_0, pad_type = input_417_pad_type_0, strides = input_417_strides_0, weight = const_247_to_fp16, x = var_3603_cast_fp16)[name = string("input_419_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_421_cast_fp16 = relu(x = input_419_cast_fp16)[name = string("input_421_cast_fp16")];
            string input_423_pad_type_0 = const()[name = string("input_423_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_423_pad_0 = const()[name = string("input_423_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1279296)))];
            int32 input_423_groups_0 = const()[name = string("input_423_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_423_strides_0 = const()[name = string("input_423_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_423_dilations_0 = const()[name = string("input_423_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_249_to_fp16 = const()[name = string("const_249_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1279424)))];
            tensor<fp16, [128]> const_250_to_fp16 = const()[name = string("const_250_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1285888)))];
            tensor<fp16, [1, 128, 16, 16]> input_425_cast_fp16 = conv(bias = const_250_to_fp16, dilations = input_423_dilations_0, groups = input_423_groups_0, pad = input_423_pad_0, pad_type = input_423_pad_type_0, strides = input_423_strides_0, weight = const_249_to_fp16, x = input_421_cast_fp16)[name = string("input_425_cast_fp16")];
            string input_427_pad_type_0 = const()[name = string("input_427_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_427_strides_0 = const()[name = string("input_427_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_427_pad_0 = const()[name = string("input_427_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1286208)))];
            tensor<int32, [2]> input_427_dilations_0 = const()[name = string("input_427_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_427_groups_0 = const()[name = string("input_427_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_251_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1286336))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1302784))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303104)))];
            tensor<fp16, [128]> const_252_to_fp16 = const()[name = string("const_252_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303296)))];
            tensor<fp16, [1, 128, 16, 16]> input_429_cast_fp16 = conv(bias = const_252_to_fp16, dilations = input_427_dilations_0, groups = input_427_groups_0, pad = input_427_pad_0, pad_type = input_427_pad_type_0, strides = input_427_strides_0, weight = const_251_to_fp16, x = input_425_cast_fp16)[name = string("input_429_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_13_cast_fp16 = relu(x = input_429_cast_fp16)[name = string("out1_13_cast_fp16")];
            string input_433_pad_type_0 = const()[name = string("input_433_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_433_strides_0 = const()[name = string("input_433_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_433_pad_0 = const()[name = string("input_433_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303616)))];
            tensor<int32, [2]> input_433_dilations_0 = const()[name = string("input_433_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_433_groups_0 = const()[name = string("input_433_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_253_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303744))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320192))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320512)))];
            tensor<fp16, [128]> const_254_to_fp16 = const()[name = string("const_254_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320704)))];
            tensor<fp16, [1, 128, 16, 16]> input_435_cast_fp16 = conv(bias = const_254_to_fp16, dilations = input_433_dilations_0, groups = input_433_groups_0, pad = input_433_pad_0, pad_type = input_433_pad_type_0, strides = input_433_strides_0, weight = const_253_to_fp16, x = var_3607_cast_fp16)[name = string("input_435_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_437_cast_fp16 = relu(x = input_435_cast_fp16)[name = string("input_437_cast_fp16")];
            string input_439_pad_type_0 = const()[name = string("input_439_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_439_pad_0 = const()[name = string("input_439_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1321024)))];
            int32 input_439_groups_0 = const()[name = string("input_439_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_439_strides_0 = const()[name = string("input_439_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_439_dilations_0 = const()[name = string("input_439_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_255_to_fp16 = const()[name = string("const_255_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1321152)))];
            tensor<fp16, [128]> const_256_to_fp16 = const()[name = string("const_256_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1327616)))];
            tensor<fp16, [1, 128, 16, 16]> input_441_cast_fp16 = conv(bias = const_256_to_fp16, dilations = input_439_dilations_0, groups = input_439_groups_0, pad = input_439_pad_0, pad_type = input_439_pad_type_0, strides = input_439_strides_0, weight = const_255_to_fp16, x = input_437_cast_fp16)[name = string("input_441_cast_fp16")];
            string input_443_pad_type_0 = const()[name = string("input_443_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_443_strides_0 = const()[name = string("input_443_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_443_pad_0 = const()[name = string("input_443_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1327936)))];
            tensor<int32, [2]> input_443_dilations_0 = const()[name = string("input_443_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_443_groups_0 = const()[name = string("input_443_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_257_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1328064))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1344512))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1344832)))];
            tensor<fp16, [128]> const_258_to_fp16 = const()[name = string("const_258_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345024)))];
            tensor<fp16, [1, 128, 16, 16]> input_445_cast_fp16 = conv(bias = const_258_to_fp16, dilations = input_443_dilations_0, groups = input_443_groups_0, pad = input_443_pad_0, pad_type = input_443_pad_type_0, strides = input_443_strides_0, weight = const_257_to_fp16, x = input_441_cast_fp16)[name = string("input_445_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_13_cast_fp16 = relu(x = input_445_cast_fp16)[name = string("out2_13_cast_fp16")];
            string input_449_pad_type_0 = const()[name = string("input_449_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_449_strides_0 = const()[name = string("input_449_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_449_pad_0 = const()[name = string("input_449_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345344)))];
            tensor<int32, [2]> input_449_dilations_0 = const()[name = string("input_449_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_449_groups_0 = const()[name = string("input_449_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_259_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345472))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1361920))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362240)))];
            tensor<fp16, [128]> const_260_to_fp16 = const()[name = string("const_260_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362432)))];
            tensor<fp16, [1, 128, 16, 16]> input_451_cast_fp16 = conv(bias = const_260_to_fp16, dilations = input_449_dilations_0, groups = input_449_groups_0, pad = input_449_pad_0, pad_type = input_449_pad_type_0, strides = input_449_strides_0, weight = const_259_to_fp16, x = var_3611_cast_fp16)[name = string("input_451_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_453_cast_fp16 = relu(x = input_451_cast_fp16)[name = string("input_453_cast_fp16")];
            string input_455_pad_type_0 = const()[name = string("input_455_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_455_pad_0 = const()[name = string("input_455_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362752)))];
            int32 input_455_groups_0 = const()[name = string("input_455_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_455_strides_0 = const()[name = string("input_455_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_455_dilations_0 = const()[name = string("input_455_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_261_to_fp16 = const()[name = string("const_261_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362880)))];
            tensor<fp16, [128]> const_262_to_fp16 = const()[name = string("const_262_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369344)))];
            tensor<fp16, [1, 128, 16, 16]> input_457_cast_fp16 = conv(bias = const_262_to_fp16, dilations = input_455_dilations_0, groups = input_455_groups_0, pad = input_455_pad_0, pad_type = input_455_pad_type_0, strides = input_455_strides_0, weight = const_261_to_fp16, x = input_453_cast_fp16)[name = string("input_457_cast_fp16")];
            string input_459_pad_type_0 = const()[name = string("input_459_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_459_strides_0 = const()[name = string("input_459_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_459_pad_0 = const()[name = string("input_459_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369664)))];
            tensor<int32, [2]> input_459_dilations_0 = const()[name = string("input_459_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_459_groups_0 = const()[name = string("input_459_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_263_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369792))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386240))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386560)))];
            tensor<fp16, [128]> const_264_to_fp16 = const()[name = string("const_264_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386752)))];
            tensor<fp16, [1, 128, 16, 16]> input_461_cast_fp16 = conv(bias = const_264_to_fp16, dilations = input_459_dilations_0, groups = input_459_groups_0, pad = input_459_pad_0, pad_type = input_459_pad_type_0, strides = input_459_strides_0, weight = const_263_to_fp16, x = input_457_cast_fp16)[name = string("input_461_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_13_cast_fp16 = relu(x = input_461_cast_fp16)[name = string("out3_13_cast_fp16")];
            bool input_463_interleave_0 = const()[name = string("input_463_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_463_cast_fp16 = concat(axis = var_86, interleave = input_463_interleave_0, values = (var_3599_cast_fp16, out1_13_cast_fp16, out2_13_cast_fp16, out3_13_cast_fp16))[name = string("input_463_cast_fp16")];
            string input_465_pad_type_0 = const()[name = string("input_465_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_465_strides_0 = const()[name = string("input_465_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_465_pad_0 = const()[name = string("input_465_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1387072)))];
            tensor<int32, [2]> input_465_dilations_0 = const()[name = string("input_465_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_465_groups_0 = const()[name = string("input_465_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_265_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1387200))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1649408))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1650496)))];
            tensor<fp16, [512]> const_266_to_fp16 = const()[name = string("const_266_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1651072)))];
            tensor<fp16, [1, 512, 16, 16]> input_467_cast_fp16 = conv(bias = const_266_to_fp16, dilations = input_465_dilations_0, groups = input_465_groups_0, pad = input_465_pad_0, pad_type = input_465_pad_type_0, strides = input_465_strides_0, weight = const_265_to_fp16, x = input_463_cast_fp16)[name = string("input_467_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_469_cast_fp16 = relu(x = input_467_cast_fp16)[name = string("input_469_cast_fp16")];
            string input_471_pad_type_0 = const()[name = string("input_471_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_471_pad_0 = const()[name = string("input_471_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1652160)))];
            int32 input_471_groups_0 = const()[name = string("input_471_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_471_strides_0 = const()[name = string("input_471_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_471_dilations_0 = const()[name = string("input_471_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [512, 1, 5, 5]> const_267_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1652288))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1665152))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1666240)))];
            tensor<fp16, [512]> const_268_to_fp16 = const()[name = string("const_268_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1666816)))];
            tensor<fp16, [1, 512, 16, 16]> input_473_cast_fp16 = conv(bias = const_268_to_fp16, dilations = input_471_dilations_0, groups = input_471_groups_0, pad = input_471_pad_0, pad_type = input_471_pad_type_0, strides = input_471_strides_0, weight = const_267_to_fp16, x = input_469_cast_fp16)[name = string("input_473_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_475_cast_fp16 = relu(x = input_473_cast_fp16)[name = string("input_475_cast_fp16")];
            string input_477_pad_type_0 = const()[name = string("input_477_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_477_strides_0 = const()[name = string("input_477_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_477_pad_0 = const()[name = string("input_477_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1667904)))];
            tensor<int32, [2]> input_477_dilations_0 = const()[name = string("input_477_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_477_groups_0 = const()[name = string("input_477_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_269_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1668032))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1930240))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1931328)))];
            tensor<fp16, [512]> const_270_to_fp16 = const()[name = string("const_270_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1931904)))];
            tensor<fp16, [1, 512, 16, 16]> y_9_cast_fp16 = conv(bias = const_270_to_fp16, dilations = input_477_dilations_0, groups = input_477_groups_0, pad = input_477_pad_0, pad_type = input_477_pad_type_0, strides = input_477_strides_0, weight = const_269_to_fp16, x = input_475_cast_fp16)[name = string("y_9_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> x_15_cast_fp16 = add(x = input_463_cast_fp16, y = y_9_cast_fp16)[name = string("x_15_cast_fp16")];
            tensor<int32, [4]> var_3711_begin_0 = const()[name = string("op_3711_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1932992)))];
            tensor<int32, [4]> var_3711_end_0 = const()[name = string("op_3711_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933120)))];
            tensor<bool, [4]> var_3711_end_mask_0 = const()[name = string("op_3711_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3711_cast_fp16 = slice_by_index(begin = var_3711_begin_0, end = var_3711_end_0, end_mask = var_3711_end_mask_0, x = x_15_cast_fp16)[name = string("op_3711_cast_fp16")];
            tensor<int32, [4]> var_3715_begin_0 = const()[name = string("op_3715_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933248)))];
            tensor<int32, [4]> var_3715_end_0 = const()[name = string("op_3715_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933376)))];
            tensor<bool, [4]> var_3715_end_mask_0 = const()[name = string("op_3715_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3715_cast_fp16 = slice_by_index(begin = var_3715_begin_0, end = var_3715_end_0, end_mask = var_3715_end_mask_0, x = x_15_cast_fp16)[name = string("op_3715_cast_fp16")];
            tensor<int32, [4]> var_3719_begin_0 = const()[name = string("op_3719_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933504)))];
            tensor<int32, [4]> var_3719_end_0 = const()[name = string("op_3719_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933632)))];
            tensor<bool, [4]> var_3719_end_mask_0 = const()[name = string("op_3719_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3719_cast_fp16 = slice_by_index(begin = var_3719_begin_0, end = var_3719_end_0, end_mask = var_3719_end_mask_0, x = x_15_cast_fp16)[name = string("op_3719_cast_fp16")];
            tensor<int32, [4]> var_3723_begin_0 = const()[name = string("op_3723_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933760)))];
            tensor<int32, [4]> var_3723_end_0 = const()[name = string("op_3723_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933888)))];
            tensor<bool, [4]> var_3723_end_mask_0 = const()[name = string("op_3723_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3723_cast_fp16 = slice_by_index(begin = var_3723_begin_0, end = var_3723_end_0, end_mask = var_3723_end_mask_0, x = x_15_cast_fp16)[name = string("op_3723_cast_fp16")];
            string input_481_pad_type_0 = const()[name = string("input_481_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_481_strides_0 = const()[name = string("input_481_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_481_pad_0 = const()[name = string("input_481_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1934016)))];
            tensor<int32, [2]> input_481_dilations_0 = const()[name = string("input_481_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_481_groups_0 = const()[name = string("input_481_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_271_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1934144))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1950592))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1950912)))];
            tensor<fp16, [128]> const_272_to_fp16 = const()[name = string("const_272_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951104)))];
            tensor<fp16, [1, 128, 16, 16]> input_483_cast_fp16 = conv(bias = const_272_to_fp16, dilations = input_481_dilations_0, groups = input_481_groups_0, pad = input_481_pad_0, pad_type = input_481_pad_type_0, strides = input_481_strides_0, weight = const_271_to_fp16, x = var_3715_cast_fp16)[name = string("input_483_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_485_cast_fp16 = relu(x = input_483_cast_fp16)[name = string("input_485_cast_fp16")];
            string input_487_pad_type_0 = const()[name = string("input_487_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_487_pad_0 = const()[name = string("input_487_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951424)))];
            int32 input_487_groups_0 = const()[name = string("input_487_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_487_strides_0 = const()[name = string("input_487_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_487_dilations_0 = const()[name = string("input_487_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_273_to_fp16 = const()[name = string("const_273_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951552)))];
            tensor<fp16, [128]> const_274_to_fp16 = const()[name = string("const_274_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958016)))];
            tensor<fp16, [1, 128, 16, 16]> input_489_cast_fp16 = conv(bias = const_274_to_fp16, dilations = input_487_dilations_0, groups = input_487_groups_0, pad = input_487_pad_0, pad_type = input_487_pad_type_0, strides = input_487_strides_0, weight = const_273_to_fp16, x = input_485_cast_fp16)[name = string("input_489_cast_fp16")];
            string input_491_pad_type_0 = const()[name = string("input_491_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_491_strides_0 = const()[name = string("input_491_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_491_pad_0 = const()[name = string("input_491_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958336)))];
            tensor<int32, [2]> input_491_dilations_0 = const()[name = string("input_491_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_491_groups_0 = const()[name = string("input_491_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_275_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958464))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1974912))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975232)))];
            tensor<fp16, [128]> const_276_to_fp16 = const()[name = string("const_276_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975424)))];
            tensor<fp16, [1, 128, 16, 16]> input_493_cast_fp16 = conv(bias = const_276_to_fp16, dilations = input_491_dilations_0, groups = input_491_groups_0, pad = input_491_pad_0, pad_type = input_491_pad_type_0, strides = input_491_strides_0, weight = const_275_to_fp16, x = input_489_cast_fp16)[name = string("input_493_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_15_cast_fp16 = relu(x = input_493_cast_fp16)[name = string("out1_15_cast_fp16")];
            string input_497_pad_type_0 = const()[name = string("input_497_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_497_strides_0 = const()[name = string("input_497_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_497_pad_0 = const()[name = string("input_497_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975744)))];
            tensor<int32, [2]> input_497_dilations_0 = const()[name = string("input_497_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_497_groups_0 = const()[name = string("input_497_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_277_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975872))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992320))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992640)))];
            tensor<fp16, [128]> const_278_to_fp16 = const()[name = string("const_278_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992832)))];
            tensor<fp16, [1, 128, 16, 16]> input_499_cast_fp16 = conv(bias = const_278_to_fp16, dilations = input_497_dilations_0, groups = input_497_groups_0, pad = input_497_pad_0, pad_type = input_497_pad_type_0, strides = input_497_strides_0, weight = const_277_to_fp16, x = var_3719_cast_fp16)[name = string("input_499_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_501_cast_fp16 = relu(x = input_499_cast_fp16)[name = string("input_501_cast_fp16")];
            string input_503_pad_type_0 = const()[name = string("input_503_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_503_pad_0 = const()[name = string("input_503_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1993152)))];
            int32 input_503_groups_0 = const()[name = string("input_503_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_503_strides_0 = const()[name = string("input_503_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_503_dilations_0 = const()[name = string("input_503_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_279_to_fp16 = const()[name = string("const_279_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1993280)))];
            tensor<fp16, [128]> const_280_to_fp16 = const()[name = string("const_280_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1999744)))];
            tensor<fp16, [1, 128, 16, 16]> input_505_cast_fp16 = conv(bias = const_280_to_fp16, dilations = input_503_dilations_0, groups = input_503_groups_0, pad = input_503_pad_0, pad_type = input_503_pad_type_0, strides = input_503_strides_0, weight = const_279_to_fp16, x = input_501_cast_fp16)[name = string("input_505_cast_fp16")];
            string input_507_pad_type_0 = const()[name = string("input_507_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_507_strides_0 = const()[name = string("input_507_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_507_pad_0 = const()[name = string("input_507_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2000064)))];
            tensor<int32, [2]> input_507_dilations_0 = const()[name = string("input_507_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_507_groups_0 = const()[name = string("input_507_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_281_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2000192))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2016640))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2016960)))];
            tensor<fp16, [128]> const_282_to_fp16 = const()[name = string("const_282_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017152)))];
            tensor<fp16, [1, 128, 16, 16]> input_509_cast_fp16 = conv(bias = const_282_to_fp16, dilations = input_507_dilations_0, groups = input_507_groups_0, pad = input_507_pad_0, pad_type = input_507_pad_type_0, strides = input_507_strides_0, weight = const_281_to_fp16, x = input_505_cast_fp16)[name = string("input_509_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_15_cast_fp16 = relu(x = input_509_cast_fp16)[name = string("out2_15_cast_fp16")];
            string input_513_pad_type_0 = const()[name = string("input_513_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_513_strides_0 = const()[name = string("input_513_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_513_pad_0 = const()[name = string("input_513_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017472)))];
            tensor<int32, [2]> input_513_dilations_0 = const()[name = string("input_513_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_513_groups_0 = const()[name = string("input_513_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_283_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017600))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034048))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034368)))];
            tensor<fp16, [128]> const_284_to_fp16 = const()[name = string("const_284_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034560)))];
            tensor<fp16, [1, 128, 16, 16]> input_515_cast_fp16 = conv(bias = const_284_to_fp16, dilations = input_513_dilations_0, groups = input_513_groups_0, pad = input_513_pad_0, pad_type = input_513_pad_type_0, strides = input_513_strides_0, weight = const_283_to_fp16, x = var_3723_cast_fp16)[name = string("input_515_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_517_cast_fp16 = relu(x = input_515_cast_fp16)[name = string("input_517_cast_fp16")];
            string input_519_pad_type_0 = const()[name = string("input_519_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_519_pad_0 = const()[name = string("input_519_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034880)))];
            int32 input_519_groups_0 = const()[name = string("input_519_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_519_strides_0 = const()[name = string("input_519_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_519_dilations_0 = const()[name = string("input_519_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_285_to_fp16 = const()[name = string("const_285_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2035008)))];
            tensor<fp16, [128]> const_286_to_fp16 = const()[name = string("const_286_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041472)))];
            tensor<fp16, [1, 128, 16, 16]> input_521_cast_fp16 = conv(bias = const_286_to_fp16, dilations = input_519_dilations_0, groups = input_519_groups_0, pad = input_519_pad_0, pad_type = input_519_pad_type_0, strides = input_519_strides_0, weight = const_285_to_fp16, x = input_517_cast_fp16)[name = string("input_521_cast_fp16")];
            string input_523_pad_type_0 = const()[name = string("input_523_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_523_strides_0 = const()[name = string("input_523_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_523_pad_0 = const()[name = string("input_523_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041792)))];
            tensor<int32, [2]> input_523_dilations_0 = const()[name = string("input_523_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_523_groups_0 = const()[name = string("input_523_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_287_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041920))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058368))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058688)))];
            tensor<fp16, [128]> const_288_to_fp16 = const()[name = string("const_288_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058880)))];
            tensor<fp16, [1, 128, 16, 16]> input_525_cast_fp16 = conv(bias = const_288_to_fp16, dilations = input_523_dilations_0, groups = input_523_groups_0, pad = input_523_pad_0, pad_type = input_523_pad_type_0, strides = input_523_strides_0, weight = const_287_to_fp16, x = input_521_cast_fp16)[name = string("input_525_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_15_cast_fp16 = relu(x = input_525_cast_fp16)[name = string("out3_15_cast_fp16")];
            bool input_527_interleave_0 = const()[name = string("input_527_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_527_cast_fp16 = concat(axis = var_86, interleave = input_527_interleave_0, values = (var_3711_cast_fp16, out1_15_cast_fp16, out2_15_cast_fp16, out3_15_cast_fp16))[name = string("input_527_cast_fp16")];
            string input_529_pad_type_0 = const()[name = string("input_529_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_529_strides_0 = const()[name = string("input_529_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_529_pad_0 = const()[name = string("input_529_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2059200)))];
            tensor<int32, [2]> input_529_dilations_0 = const()[name = string("input_529_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_529_groups_0 = const()[name = string("input_529_groups_0"), val = int32(1)];
            tensor<fp16, [128, 512, 1, 1]> model_key_encoder_xfpn_p5_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2059328))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2124928))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125248)))];
            tensor<fp16, [1, 128, 16, 16]> input_529_cast_fp16 = conv(dilations = input_529_dilations_0, groups = input_529_groups_0, pad = input_529_pad_0, pad_type = input_529_pad_type_0, strides = input_529_strides_0, weight = model_key_encoder_xfpn_p5_1x1_weight_to_fp16, x = input_527_cast_fp16)[name = string("input_529_cast_fp16")];
            fp32 y_11_scale_factor_height_0 = const()[name = string("y_11_scale_factor_height_0"), val = fp32(2)];
            fp32 y_11_scale_factor_width_0 = const()[name = string("y_11_scale_factor_width_0"), val = fp32(2)];
            tensor<fp16, [1, 128, 32, 32]> y_11_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = y_11_scale_factor_height_0, scale_factor_width = y_11_scale_factor_width_0, x = input_529_cast_fp16)[name = string("y_11_cast_fp16")];
            string x_17_pad_type_0 = const()[name = string("x_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_17_strides_0 = const()[name = string("x_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_17_pad_0 = const()[name = string("x_17_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125440)))];
            tensor<int32, [2]> x_17_dilations_0 = const()[name = string("x_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_17_groups_0 = const()[name = string("x_17_groups_0"), val = int32(1)];
            tensor<fp16, [128, 256, 1, 1]> model_key_encoder_xfpn_p4_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125568))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158400))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158720)))];
            tensor<fp16, [1, 128, 32, 32]> x_17_cast_fp16 = conv(dilations = x_17_dilations_0, groups = x_17_groups_0, pad = x_17_pad_0, pad_type = x_17_pad_type_0, strides = x_17_strides_0, weight = model_key_encoder_xfpn_p4_1x1_weight_to_fp16, x = input_399_cast_fp16)[name = string("x_17_cast_fp16")];
            tensor<fp16, [1, 128, 32, 32]> input_531_cast_fp16 = add(x = x_17_cast_fp16, y = y_11_cast_fp16)[name = string("input_531_cast_fp16")];
            string input_631_pad_type_0 = const()[name = string("input_631_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_631_pad_0 = const()[name = string("input_631_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158912)))];
            int32 input_631_groups_0 = const()[name = string("input_631_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_631_strides_0 = const()[name = string("input_631_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_631_dilations_0 = const()[name = string("input_631_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> model_key_encoder_xfpn_fpn_output4_weight_to_fp16 = const()[name = string("model_key_encoder_xfpn_fpn_output4_weight_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2159040)))];
            tensor<fp16, [1, 128, 32, 32]> input_631_cast_fp16 = conv(dilations = input_631_dilations_0, groups = input_631_groups_0, pad = input_631_pad_0, pad_type = input_631_pad_type_0, strides = input_631_strides_0, weight = model_key_encoder_xfpn_fpn_output4_weight_to_fp16, x = input_531_cast_fp16)[name = string("input_631_cast_fp16")];
            string key_k_pad_type_0 = const()[name = string("key_k_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> key_k_pad_0 = const()[name = string("key_k_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2161408)))];
            tensor<int32, [2]> key_k_strides_0 = const()[name = string("key_k_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> key_k_dilations_0 = const()[name = string("key_k_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 key_k_groups_0 = const()[name = string("key_k_groups_0"), val = int32(1)];
            tensor<fp16, [64, 128, 3, 3]> model_key_proj_key_proj_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2161536))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235328))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235520)))];
            tensor<fp16, [64]> model_key_proj_key_proj_bias_to_fp16 = const()[name = string("model_key_proj_key_proj_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235648)))];
            tensor<fp16, [1, 64, 32, 32]> key_k_cast_fp16 = conv(bias = model_key_proj_key_proj_bias_to_fp16, dilations = key_k_dilations_0, groups = key_k_groups_0, pad = key_k_pad_0, pad_type = key_k_pad_type_0, strides = key_k_strides_0, weight = model_key_proj_key_proj_weight_to_fp16, x = input_631_cast_fp16)[name = string("key_k_cast_fp16")];
            int32 var_3877 = const()[name = string("op_3877"), val = int32(1)];
            bool input_633_interleave_0 = const()[name = string("input_633_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 512, 512]> other_masks_1_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [1, 1, 512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235840))), scale = tensor<fp16, [1]>([0]), zero_point = tensor<int8, [1]>([0])];
            tensor<fp16, [1, 2, 512, 512]> input_633_cast_fp16 = concat(axis = var_3877, interleave = input_633_interleave_0, values = (mask, other_masks_1_to_fp16))[name = string("input_633_cast_fp16")];
            string coord_features_1_pad_type_0 = const()[name = string("coord_features_1_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> coord_features_1_pad_0 = const()[name = string("coord_features_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2498048)))];
            tensor<int32, [2]> coord_features_1_strides_0 = const()[name = string("coord_features_1_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> coord_features_1_dilations_0 = const()[name = string("coord_features_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 coord_features_1_groups_0 = const()[name = string("coord_features_1_groups_0"), val = int32(1)];
            tensor<fp16, [24, 2, 3, 3]> model_value_encoder_mask_conv_weight_to_fp16 = const()[name = string("model_value_encoder_mask_conv_weight_to_fp16"), val = tensor<fp16, [24, 2, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2498176)))];
            tensor<fp16, [24]> model_value_encoder_mask_conv_bias_to_fp16 = const()[name = string("model_value_encoder_mask_conv_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2499136)))];
            tensor<fp16, [1, 24, 256, 256]> coord_features_1_cast_fp16 = conv(bias = model_value_encoder_mask_conv_bias_to_fp16, dilations = coord_features_1_dilations_0, groups = coord_features_1_groups_0, pad = coord_features_1_pad_0, pad_type = coord_features_1_pad_type_0, strides = coord_features_1_strides_0, weight = model_value_encoder_mask_conv_weight_to_fp16, x = input_633_cast_fp16)[name = string("coord_features_1_cast_fp16")];
            string input_637_pad_type_0 = const()[name = string("input_637_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_637_strides_0 = const()[name = string("input_637_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_637_pad_0 = const()[name = string("input_637_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2499264)))];
            tensor<int32, [2]> input_637_dilations_0 = const()[name = string("input_637_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_637_groups_0 = const()[name = string("input_637_groups_0"), val = int32(1)];
            tensor<fp16, [24, 3, 3, 3]> const_289_to_fp16 = const()[name = string("const_289_to_fp16"), val = tensor<fp16, [24, 3, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2499392)))];
            tensor<fp16, [24]> const_290_to_fp16 = const()[name = string("const_290_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2500800)))];
            tensor<fp16, [1, 24, 256, 256]> input_639_cast_fp16 = conv(bias = const_290_to_fp16, dilations = input_637_dilations_0, groups = input_637_groups_0, pad = input_637_pad_0, pad_type = input_637_pad_type_0, strides = input_637_strides_0, weight = const_289_to_fp16, x = input_3_cast_fp16)[name = string("input_639_cast_fp16")];
            tensor<fp16, [1, 24, 256, 256]> x_33_cast_fp16 = relu(x = input_639_cast_fp16)[name = string("x_33_cast_fp16")];
            tensor<fp16, [1, 24, 256, 256]> input_641_cast_fp16 = add(x = x_33_cast_fp16, y = coord_features_1_cast_fp16)[name = string("input_641_cast_fp16")];
            tensor<int32, [2]> var_6694 = const()[name = string("op_6694"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_6695 = const()[name = string("op_6695"), val = tensor<int32, [2]>([2, 2])];
            string input_643_pad_type_0 = const()[name = string("input_643_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_643_pad_0 = const()[name = string("input_643_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2500928)))];
            bool input_643_ceil_mode_0 = const()[name = string("input_643_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 24, 128, 128]> input_643_cast_fp16 = max_pool(ceil_mode = input_643_ceil_mode_0, kernel_sizes = var_6694, pad = input_643_pad_0, pad_type = input_643_pad_type_0, strides = var_6695, x = input_641_cast_fp16)[name = string("input_643_cast_fp16")];
            string input_649_pad_type_0 = const()[name = string("input_649_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_649_strides_0 = const()[name = string("input_649_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_649_pad_0 = const()[name = string("input_649_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2501056)))];
            tensor<int32, [2]> input_649_dilations_0 = const()[name = string("input_649_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_649_groups_0 = const()[name = string("input_649_groups_0"), val = int32(1)];
            tensor<fp16, [144, 24, 1, 1]> const_291_to_fp16 = const()[name = string("const_291_to_fp16"), val = tensor<fp16, [144, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2501184)))];
            tensor<fp16, [144]> const_292_to_fp16 = const()[name = string("const_292_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2508160)))];
            tensor<fp16, [1, 144, 128, 128]> input_651_cast_fp16 = conv(bias = const_292_to_fp16, dilations = input_649_dilations_0, groups = input_649_groups_0, pad = input_649_pad_0, pad_type = input_649_pad_type_0, strides = input_649_strides_0, weight = const_291_to_fp16, x = input_643_cast_fp16)[name = string("input_651_cast_fp16")];
            tensor<fp16, [1, 144, 128, 128]> input_653_cast_fp16 = relu(x = input_651_cast_fp16)[name = string("input_653_cast_fp16")];
            string input_655_pad_type_0 = const()[name = string("input_655_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_655_pad_0 = const()[name = string("input_655_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2508544)))];
            tensor<int32, [2]> input_655_strides_0 = const()[name = string("input_655_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_655_groups_0 = const()[name = string("input_655_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_655_dilations_0 = const()[name = string("input_655_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [144, 1, 5, 5]> const_293_to_fp16 = const()[name = string("const_293_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2508672)))];
            tensor<fp16, [144]> const_294_to_fp16 = const()[name = string("const_294_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2515968)))];
            tensor<fp16, [1, 144, 64, 64]> input_657_cast_fp16 = conv(bias = const_294_to_fp16, dilations = input_655_dilations_0, groups = input_655_groups_0, pad = input_655_pad_0, pad_type = input_655_pad_type_0, strides = input_655_strides_0, weight = const_293_to_fp16, x = input_653_cast_fp16)[name = string("input_657_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_659_cast_fp16 = relu(x = input_657_cast_fp16)[name = string("input_659_cast_fp16")];
            string input_661_pad_type_0 = const()[name = string("input_661_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_661_strides_0 = const()[name = string("input_661_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_661_pad_0 = const()[name = string("input_661_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2516352)))];
            tensor<int32, [2]> input_661_dilations_0 = const()[name = string("input_661_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_661_groups_0 = const()[name = string("input_661_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_295_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2516480))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2537280))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2537664)))];
            tensor<fp16, [144]> const_296_to_fp16 = const()[name = string("const_296_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2537920)))];
            tensor<fp16, [1, 144, 64, 64]> x_35_cast_fp16 = conv(bias = const_296_to_fp16, dilations = input_661_dilations_0, groups = input_661_groups_0, pad = input_661_pad_0, pad_type = input_661_pad_type_0, strides = input_661_strides_0, weight = const_295_to_fp16, x = input_659_cast_fp16)[name = string("x_35_cast_fp16")];
            tensor<int32, [4]> var_6733_begin_0 = const()[name = string("op_6733_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2538304)))];
            tensor<int32, [4]> var_6733_end_0 = const()[name = string("op_6733_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2538432)))];
            tensor<bool, [4]> var_6733_end_mask_0 = const()[name = string("op_6733_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_6733_cast_fp16 = slice_by_index(begin = var_6733_begin_0, end = var_6733_end_0, end_mask = var_6733_end_mask_0, x = x_35_cast_fp16)[name = string("op_6733_cast_fp16")];
            tensor<int32, [4]> var_6737_begin_0 = const()[name = string("op_6737_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2538560)))];
            tensor<int32, [4]> var_6737_end_0 = const()[name = string("op_6737_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2538688)))];
            tensor<bool, [4]> var_6737_end_mask_0 = const()[name = string("op_6737_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_6737_cast_fp16 = slice_by_index(begin = var_6737_begin_0, end = var_6737_end_0, end_mask = var_6737_end_mask_0, x = x_35_cast_fp16)[name = string("op_6737_cast_fp16")];
            tensor<int32, [4]> var_6741_begin_0 = const()[name = string("op_6741_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2538816)))];
            tensor<int32, [4]> var_6741_end_0 = const()[name = string("op_6741_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2538944)))];
            tensor<bool, [4]> var_6741_end_mask_0 = const()[name = string("op_6741_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_6741_cast_fp16 = slice_by_index(begin = var_6741_begin_0, end = var_6741_end_0, end_mask = var_6741_end_mask_0, x = x_35_cast_fp16)[name = string("op_6741_cast_fp16")];
            tensor<int32, [4]> var_6745_begin_0 = const()[name = string("op_6745_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2539072)))];
            tensor<int32, [4]> var_6745_end_0 = const()[name = string("op_6745_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2539200)))];
            tensor<bool, [4]> var_6745_end_mask_0 = const()[name = string("op_6745_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_6745_cast_fp16 = slice_by_index(begin = var_6745_begin_0, end = var_6745_end_0, end_mask = var_6745_end_mask_0, x = x_35_cast_fp16)[name = string("op_6745_cast_fp16")];
            string input_665_pad_type_0 = const()[name = string("input_665_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_665_strides_0 = const()[name = string("input_665_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_665_pad_0 = const()[name = string("input_665_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2539328)))];
            tensor<int32, [2]> input_665_dilations_0 = const()[name = string("input_665_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_665_groups_0 = const()[name = string("input_665_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_297_to_fp16 = const()[name = string("const_297_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2539456)))];
            tensor<fp16, [36]> const_298_to_fp16 = const()[name = string("const_298_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2542144)))];
            tensor<fp16, [1, 36, 64, 64]> input_667_cast_fp16 = conv(bias = const_298_to_fp16, dilations = input_665_dilations_0, groups = input_665_groups_0, pad = input_665_pad_0, pad_type = input_665_pad_type_0, strides = input_665_strides_0, weight = const_297_to_fp16, x = var_6737_cast_fp16)[name = string("input_667_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_669_cast_fp16 = relu(x = input_667_cast_fp16)[name = string("input_669_cast_fp16")];
            string input_671_pad_type_0 = const()[name = string("input_671_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_671_pad_0 = const()[name = string("input_671_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2542336)))];
            int32 input_671_groups_0 = const()[name = string("input_671_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_671_strides_0 = const()[name = string("input_671_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_671_dilations_0 = const()[name = string("input_671_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_299_to_fp16 = const()[name = string("const_299_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2542464)))];
            tensor<fp16, [36]> const_300_to_fp16 = const()[name = string("const_300_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2544384)))];
            tensor<fp16, [1, 36, 64, 64]> input_673_cast_fp16 = conv(bias = const_300_to_fp16, dilations = input_671_dilations_0, groups = input_671_groups_0, pad = input_671_pad_0, pad_type = input_671_pad_type_0, strides = input_671_strides_0, weight = const_299_to_fp16, x = input_669_cast_fp16)[name = string("input_673_cast_fp16")];
            string input_675_pad_type_0 = const()[name = string("input_675_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_675_strides_0 = const()[name = string("input_675_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_675_pad_0 = const()[name = string("input_675_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2544576)))];
            tensor<int32, [2]> input_675_dilations_0 = const()[name = string("input_675_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_675_groups_0 = const()[name = string("input_675_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_301_to_fp16 = const()[name = string("const_301_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2544704)))];
            tensor<fp16, [36]> const_302_to_fp16 = const()[name = string("const_302_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2547392)))];
            tensor<fp16, [1, 36, 64, 64]> input_677_cast_fp16 = conv(bias = const_302_to_fp16, dilations = input_675_dilations_0, groups = input_675_groups_0, pad = input_675_pad_0, pad_type = input_675_pad_type_0, strides = input_675_strides_0, weight = const_301_to_fp16, x = input_673_cast_fp16)[name = string("input_677_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_21_cast_fp16 = relu(x = input_677_cast_fp16)[name = string("out1_21_cast_fp16")];
            string input_681_pad_type_0 = const()[name = string("input_681_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_681_strides_0 = const()[name = string("input_681_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_681_pad_0 = const()[name = string("input_681_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2547584)))];
            tensor<int32, [2]> input_681_dilations_0 = const()[name = string("input_681_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_681_groups_0 = const()[name = string("input_681_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_303_to_fp16 = const()[name = string("const_303_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2547712)))];
            tensor<fp16, [36]> const_304_to_fp16 = const()[name = string("const_304_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2550400)))];
            tensor<fp16, [1, 36, 64, 64]> input_683_cast_fp16 = conv(bias = const_304_to_fp16, dilations = input_681_dilations_0, groups = input_681_groups_0, pad = input_681_pad_0, pad_type = input_681_pad_type_0, strides = input_681_strides_0, weight = const_303_to_fp16, x = var_6741_cast_fp16)[name = string("input_683_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_685_cast_fp16 = relu(x = input_683_cast_fp16)[name = string("input_685_cast_fp16")];
            string input_687_pad_type_0 = const()[name = string("input_687_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_687_pad_0 = const()[name = string("input_687_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2550592)))];
            int32 input_687_groups_0 = const()[name = string("input_687_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_687_strides_0 = const()[name = string("input_687_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_687_dilations_0 = const()[name = string("input_687_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_305_to_fp16 = const()[name = string("const_305_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2550720)))];
            tensor<fp16, [36]> const_306_to_fp16 = const()[name = string("const_306_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2552640)))];
            tensor<fp16, [1, 36, 64, 64]> input_689_cast_fp16 = conv(bias = const_306_to_fp16, dilations = input_687_dilations_0, groups = input_687_groups_0, pad = input_687_pad_0, pad_type = input_687_pad_type_0, strides = input_687_strides_0, weight = const_305_to_fp16, x = input_685_cast_fp16)[name = string("input_689_cast_fp16")];
            string input_691_pad_type_0 = const()[name = string("input_691_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_691_strides_0 = const()[name = string("input_691_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_691_pad_0 = const()[name = string("input_691_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2552832)))];
            tensor<int32, [2]> input_691_dilations_0 = const()[name = string("input_691_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_691_groups_0 = const()[name = string("input_691_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_307_to_fp16 = const()[name = string("const_307_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2552960)))];
            tensor<fp16, [36]> const_308_to_fp16 = const()[name = string("const_308_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2555648)))];
            tensor<fp16, [1, 36, 64, 64]> input_693_cast_fp16 = conv(bias = const_308_to_fp16, dilations = input_691_dilations_0, groups = input_691_groups_0, pad = input_691_pad_0, pad_type = input_691_pad_type_0, strides = input_691_strides_0, weight = const_307_to_fp16, x = input_689_cast_fp16)[name = string("input_693_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_21_cast_fp16 = relu(x = input_693_cast_fp16)[name = string("out2_21_cast_fp16")];
            string input_697_pad_type_0 = const()[name = string("input_697_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_697_strides_0 = const()[name = string("input_697_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_697_pad_0 = const()[name = string("input_697_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2555840)))];
            tensor<int32, [2]> input_697_dilations_0 = const()[name = string("input_697_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_697_groups_0 = const()[name = string("input_697_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_309_to_fp16 = const()[name = string("const_309_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2555968)))];
            tensor<fp16, [36]> const_310_to_fp16 = const()[name = string("const_310_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2558656)))];
            tensor<fp16, [1, 36, 64, 64]> input_699_cast_fp16 = conv(bias = const_310_to_fp16, dilations = input_697_dilations_0, groups = input_697_groups_0, pad = input_697_pad_0, pad_type = input_697_pad_type_0, strides = input_697_strides_0, weight = const_309_to_fp16, x = var_6745_cast_fp16)[name = string("input_699_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_701_cast_fp16 = relu(x = input_699_cast_fp16)[name = string("input_701_cast_fp16")];
            string input_703_pad_type_0 = const()[name = string("input_703_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_703_pad_0 = const()[name = string("input_703_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2558848)))];
            int32 input_703_groups_0 = const()[name = string("input_703_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_703_strides_0 = const()[name = string("input_703_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_703_dilations_0 = const()[name = string("input_703_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_311_to_fp16 = const()[name = string("const_311_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2558976)))];
            tensor<fp16, [36]> const_312_to_fp16 = const()[name = string("const_312_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2560896)))];
            tensor<fp16, [1, 36, 64, 64]> input_705_cast_fp16 = conv(bias = const_312_to_fp16, dilations = input_703_dilations_0, groups = input_703_groups_0, pad = input_703_pad_0, pad_type = input_703_pad_type_0, strides = input_703_strides_0, weight = const_311_to_fp16, x = input_701_cast_fp16)[name = string("input_705_cast_fp16")];
            string input_707_pad_type_0 = const()[name = string("input_707_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_707_strides_0 = const()[name = string("input_707_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_707_pad_0 = const()[name = string("input_707_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2561088)))];
            tensor<int32, [2]> input_707_dilations_0 = const()[name = string("input_707_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_707_groups_0 = const()[name = string("input_707_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_313_to_fp16 = const()[name = string("const_313_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2561216)))];
            tensor<fp16, [36]> const_314_to_fp16 = const()[name = string("const_314_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2563904)))];
            tensor<fp16, [1, 36, 64, 64]> input_709_cast_fp16 = conv(bias = const_314_to_fp16, dilations = input_707_dilations_0, groups = input_707_groups_0, pad = input_707_pad_0, pad_type = input_707_pad_type_0, strides = input_707_strides_0, weight = const_313_to_fp16, x = input_705_cast_fp16)[name = string("input_709_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_21_cast_fp16 = relu(x = input_709_cast_fp16)[name = string("out3_21_cast_fp16")];
            bool input_711_interleave_0 = const()[name = string("input_711_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_711_cast_fp16 = concat(axis = var_3877, interleave = input_711_interleave_0, values = (var_6733_cast_fp16, out1_21_cast_fp16, out2_21_cast_fp16, out3_21_cast_fp16))[name = string("input_711_cast_fp16")];
            string input_713_pad_type_0 = const()[name = string("input_713_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_713_strides_0 = const()[name = string("input_713_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_713_pad_0 = const()[name = string("input_713_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2564096)))];
            tensor<int32, [2]> input_713_dilations_0 = const()[name = string("input_713_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_713_groups_0 = const()[name = string("input_713_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_315_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2564224))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2585024))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2585408)))];
            tensor<fp16, [144]> const_316_to_fp16 = const()[name = string("const_316_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2585664)))];
            tensor<fp16, [1, 144, 64, 64]> input_715_cast_fp16 = conv(bias = const_316_to_fp16, dilations = input_713_dilations_0, groups = input_713_groups_0, pad = input_713_pad_0, pad_type = input_713_pad_type_0, strides = input_713_strides_0, weight = const_315_to_fp16, x = input_711_cast_fp16)[name = string("input_715_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_717_cast_fp16 = relu(x = input_715_cast_fp16)[name = string("input_717_cast_fp16")];
            string input_719_pad_type_0 = const()[name = string("input_719_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_719_pad_0 = const()[name = string("input_719_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2586048)))];
            int32 input_719_groups_0 = const()[name = string("input_719_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_719_strides_0 = const()[name = string("input_719_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_719_dilations_0 = const()[name = string("input_719_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [144, 1, 5, 5]> const_317_to_fp16 = const()[name = string("const_317_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2586176)))];
            tensor<fp16, [144]> const_318_to_fp16 = const()[name = string("const_318_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2593472)))];
            tensor<fp16, [1, 144, 64, 64]> input_721_cast_fp16 = conv(bias = const_318_to_fp16, dilations = input_719_dilations_0, groups = input_719_groups_0, pad = input_719_pad_0, pad_type = input_719_pad_type_0, strides = input_719_strides_0, weight = const_317_to_fp16, x = input_717_cast_fp16)[name = string("input_721_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_723_cast_fp16 = relu(x = input_721_cast_fp16)[name = string("input_723_cast_fp16")];
            string input_725_pad_type_0 = const()[name = string("input_725_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_725_strides_0 = const()[name = string("input_725_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_725_pad_0 = const()[name = string("input_725_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2593856)))];
            tensor<int32, [2]> input_725_dilations_0 = const()[name = string("input_725_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_725_groups_0 = const()[name = string("input_725_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_319_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2593984))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2614784))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2615168)))];
            tensor<fp16, [144]> const_320_to_fp16 = const()[name = string("const_320_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2615424)))];
            tensor<fp16, [1, 144, 64, 64]> y_15_cast_fp16 = conv(bias = const_320_to_fp16, dilations = input_725_dilations_0, groups = input_725_groups_0, pad = input_725_pad_0, pad_type = input_725_pad_type_0, strides = input_725_strides_0, weight = const_319_to_fp16, x = input_723_cast_fp16)[name = string("y_15_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> x_37_cast_fp16 = add(x = input_711_cast_fp16, y = y_15_cast_fp16)[name = string("x_37_cast_fp16")];
            tensor<int32, [4]> var_6845_begin_0 = const()[name = string("op_6845_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2615808)))];
            tensor<int32, [4]> var_6845_end_0 = const()[name = string("op_6845_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2615936)))];
            tensor<bool, [4]> var_6845_end_mask_0 = const()[name = string("op_6845_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_6845_cast_fp16 = slice_by_index(begin = var_6845_begin_0, end = var_6845_end_0, end_mask = var_6845_end_mask_0, x = x_37_cast_fp16)[name = string("op_6845_cast_fp16")];
            tensor<int32, [4]> var_6849_begin_0 = const()[name = string("op_6849_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616064)))];
            tensor<int32, [4]> var_6849_end_0 = const()[name = string("op_6849_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616192)))];
            tensor<bool, [4]> var_6849_end_mask_0 = const()[name = string("op_6849_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_6849_cast_fp16 = slice_by_index(begin = var_6849_begin_0, end = var_6849_end_0, end_mask = var_6849_end_mask_0, x = x_37_cast_fp16)[name = string("op_6849_cast_fp16")];
            tensor<int32, [4]> var_6853_begin_0 = const()[name = string("op_6853_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616320)))];
            tensor<int32, [4]> var_6853_end_0 = const()[name = string("op_6853_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616448)))];
            tensor<bool, [4]> var_6853_end_mask_0 = const()[name = string("op_6853_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_6853_cast_fp16 = slice_by_index(begin = var_6853_begin_0, end = var_6853_end_0, end_mask = var_6853_end_mask_0, x = x_37_cast_fp16)[name = string("op_6853_cast_fp16")];
            tensor<int32, [4]> var_6857_begin_0 = const()[name = string("op_6857_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616576)))];
            tensor<int32, [4]> var_6857_end_0 = const()[name = string("op_6857_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616704)))];
            tensor<bool, [4]> var_6857_end_mask_0 = const()[name = string("op_6857_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_6857_cast_fp16 = slice_by_index(begin = var_6857_begin_0, end = var_6857_end_0, end_mask = var_6857_end_mask_0, x = x_37_cast_fp16)[name = string("op_6857_cast_fp16")];
            string input_729_pad_type_0 = const()[name = string("input_729_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_729_strides_0 = const()[name = string("input_729_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_729_pad_0 = const()[name = string("input_729_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616832)))];
            tensor<int32, [2]> input_729_dilations_0 = const()[name = string("input_729_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_729_groups_0 = const()[name = string("input_729_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_321_to_fp16 = const()[name = string("const_321_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616960)))];
            tensor<fp16, [36]> const_322_to_fp16 = const()[name = string("const_322_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2619648)))];
            tensor<fp16, [1, 36, 64, 64]> input_731_cast_fp16 = conv(bias = const_322_to_fp16, dilations = input_729_dilations_0, groups = input_729_groups_0, pad = input_729_pad_0, pad_type = input_729_pad_type_0, strides = input_729_strides_0, weight = const_321_to_fp16, x = var_6849_cast_fp16)[name = string("input_731_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_733_cast_fp16 = relu(x = input_731_cast_fp16)[name = string("input_733_cast_fp16")];
            string input_735_pad_type_0 = const()[name = string("input_735_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_735_pad_0 = const()[name = string("input_735_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2619840)))];
            int32 input_735_groups_0 = const()[name = string("input_735_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_735_strides_0 = const()[name = string("input_735_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_735_dilations_0 = const()[name = string("input_735_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_323_to_fp16 = const()[name = string("const_323_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2619968)))];
            tensor<fp16, [36]> const_324_to_fp16 = const()[name = string("const_324_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2621888)))];
            tensor<fp16, [1, 36, 64, 64]> input_737_cast_fp16 = conv(bias = const_324_to_fp16, dilations = input_735_dilations_0, groups = input_735_groups_0, pad = input_735_pad_0, pad_type = input_735_pad_type_0, strides = input_735_strides_0, weight = const_323_to_fp16, x = input_733_cast_fp16)[name = string("input_737_cast_fp16")];
            string input_739_pad_type_0 = const()[name = string("input_739_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_739_strides_0 = const()[name = string("input_739_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_739_pad_0 = const()[name = string("input_739_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2622080)))];
            tensor<int32, [2]> input_739_dilations_0 = const()[name = string("input_739_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_739_groups_0 = const()[name = string("input_739_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_325_to_fp16 = const()[name = string("const_325_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2622208)))];
            tensor<fp16, [36]> const_326_to_fp16 = const()[name = string("const_326_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2624896)))];
            tensor<fp16, [1, 36, 64, 64]> input_741_cast_fp16 = conv(bias = const_326_to_fp16, dilations = input_739_dilations_0, groups = input_739_groups_0, pad = input_739_pad_0, pad_type = input_739_pad_type_0, strides = input_739_strides_0, weight = const_325_to_fp16, x = input_737_cast_fp16)[name = string("input_741_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_23_cast_fp16 = relu(x = input_741_cast_fp16)[name = string("out1_23_cast_fp16")];
            string input_745_pad_type_0 = const()[name = string("input_745_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_745_strides_0 = const()[name = string("input_745_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_745_pad_0 = const()[name = string("input_745_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2625088)))];
            tensor<int32, [2]> input_745_dilations_0 = const()[name = string("input_745_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_745_groups_0 = const()[name = string("input_745_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_327_to_fp16 = const()[name = string("const_327_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2625216)))];
            tensor<fp16, [36]> const_328_to_fp16 = const()[name = string("const_328_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2627904)))];
            tensor<fp16, [1, 36, 64, 64]> input_747_cast_fp16 = conv(bias = const_328_to_fp16, dilations = input_745_dilations_0, groups = input_745_groups_0, pad = input_745_pad_0, pad_type = input_745_pad_type_0, strides = input_745_strides_0, weight = const_327_to_fp16, x = var_6853_cast_fp16)[name = string("input_747_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_749_cast_fp16 = relu(x = input_747_cast_fp16)[name = string("input_749_cast_fp16")];
            string input_751_pad_type_0 = const()[name = string("input_751_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_751_pad_0 = const()[name = string("input_751_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2628096)))];
            int32 input_751_groups_0 = const()[name = string("input_751_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_751_strides_0 = const()[name = string("input_751_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_751_dilations_0 = const()[name = string("input_751_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_329_to_fp16 = const()[name = string("const_329_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2628224)))];
            tensor<fp16, [36]> const_330_to_fp16 = const()[name = string("const_330_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2630144)))];
            tensor<fp16, [1, 36, 64, 64]> input_753_cast_fp16 = conv(bias = const_330_to_fp16, dilations = input_751_dilations_0, groups = input_751_groups_0, pad = input_751_pad_0, pad_type = input_751_pad_type_0, strides = input_751_strides_0, weight = const_329_to_fp16, x = input_749_cast_fp16)[name = string("input_753_cast_fp16")];
            string input_755_pad_type_0 = const()[name = string("input_755_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_755_strides_0 = const()[name = string("input_755_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_755_pad_0 = const()[name = string("input_755_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2630336)))];
            tensor<int32, [2]> input_755_dilations_0 = const()[name = string("input_755_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_755_groups_0 = const()[name = string("input_755_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_331_to_fp16 = const()[name = string("const_331_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2630464)))];
            tensor<fp16, [36]> const_332_to_fp16 = const()[name = string("const_332_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2633152)))];
            tensor<fp16, [1, 36, 64, 64]> input_757_cast_fp16 = conv(bias = const_332_to_fp16, dilations = input_755_dilations_0, groups = input_755_groups_0, pad = input_755_pad_0, pad_type = input_755_pad_type_0, strides = input_755_strides_0, weight = const_331_to_fp16, x = input_753_cast_fp16)[name = string("input_757_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_23_cast_fp16 = relu(x = input_757_cast_fp16)[name = string("out2_23_cast_fp16")];
            string input_761_pad_type_0 = const()[name = string("input_761_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_761_strides_0 = const()[name = string("input_761_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_761_pad_0 = const()[name = string("input_761_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2633344)))];
            tensor<int32, [2]> input_761_dilations_0 = const()[name = string("input_761_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_761_groups_0 = const()[name = string("input_761_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_333_to_fp16 = const()[name = string("const_333_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2633472)))];
            tensor<fp16, [36]> const_334_to_fp16 = const()[name = string("const_334_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2636160)))];
            tensor<fp16, [1, 36, 64, 64]> input_763_cast_fp16 = conv(bias = const_334_to_fp16, dilations = input_761_dilations_0, groups = input_761_groups_0, pad = input_761_pad_0, pad_type = input_761_pad_type_0, strides = input_761_strides_0, weight = const_333_to_fp16, x = var_6857_cast_fp16)[name = string("input_763_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_765_cast_fp16 = relu(x = input_763_cast_fp16)[name = string("input_765_cast_fp16")];
            string input_767_pad_type_0 = const()[name = string("input_767_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_767_pad_0 = const()[name = string("input_767_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2636352)))];
            int32 input_767_groups_0 = const()[name = string("input_767_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_767_strides_0 = const()[name = string("input_767_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_767_dilations_0 = const()[name = string("input_767_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_335_to_fp16 = const()[name = string("const_335_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2636480)))];
            tensor<fp16, [36]> const_336_to_fp16 = const()[name = string("const_336_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2638400)))];
            tensor<fp16, [1, 36, 64, 64]> input_769_cast_fp16 = conv(bias = const_336_to_fp16, dilations = input_767_dilations_0, groups = input_767_groups_0, pad = input_767_pad_0, pad_type = input_767_pad_type_0, strides = input_767_strides_0, weight = const_335_to_fp16, x = input_765_cast_fp16)[name = string("input_769_cast_fp16")];
            string input_771_pad_type_0 = const()[name = string("input_771_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_771_strides_0 = const()[name = string("input_771_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_771_pad_0 = const()[name = string("input_771_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2638592)))];
            tensor<int32, [2]> input_771_dilations_0 = const()[name = string("input_771_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_771_groups_0 = const()[name = string("input_771_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_337_to_fp16 = const()[name = string("const_337_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2638720)))];
            tensor<fp16, [36]> const_338_to_fp16 = const()[name = string("const_338_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2641408)))];
            tensor<fp16, [1, 36, 64, 64]> input_773_cast_fp16 = conv(bias = const_338_to_fp16, dilations = input_771_dilations_0, groups = input_771_groups_0, pad = input_771_pad_0, pad_type = input_771_pad_type_0, strides = input_771_strides_0, weight = const_337_to_fp16, x = input_769_cast_fp16)[name = string("input_773_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_23_cast_fp16 = relu(x = input_773_cast_fp16)[name = string("out3_23_cast_fp16")];
            bool input_775_interleave_0 = const()[name = string("input_775_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_775_cast_fp16 = concat(axis = var_3877, interleave = input_775_interleave_0, values = (var_6845_cast_fp16, out1_23_cast_fp16, out2_23_cast_fp16, out3_23_cast_fp16))[name = string("input_775_cast_fp16")];
            string input_777_pad_type_0 = const()[name = string("input_777_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_777_strides_0 = const()[name = string("input_777_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_777_pad_0 = const()[name = string("input_777_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2641600)))];
            tensor<int32, [2]> input_777_dilations_0 = const()[name = string("input_777_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_777_groups_0 = const()[name = string("input_777_groups_0"), val = int32(1)];
            tensor<fp16, [256, 144, 1, 1]> const_339_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2641728))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2678656))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2679232)))];
            tensor<fp16, [256]> const_340_to_fp16 = const()[name = string("const_340_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2679552)))];
            tensor<fp16, [1, 256, 64, 64]> input_779_cast_fp16 = conv(bias = const_340_to_fp16, dilations = input_777_dilations_0, groups = input_777_groups_0, pad = input_777_pad_0, pad_type = input_777_pad_type_0, strides = input_777_strides_0, weight = const_339_to_fp16, x = input_775_cast_fp16)[name = string("input_779_cast_fp16")];
            tensor<fp16, [1, 256, 64, 64]> input_781_cast_fp16 = relu(x = input_779_cast_fp16)[name = string("input_781_cast_fp16")];
            string input_783_pad_type_0 = const()[name = string("input_783_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_783_pad_0 = const()[name = string("input_783_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2680128)))];
            tensor<int32, [2]> input_783_strides_0 = const()[name = string("input_783_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_783_groups_0 = const()[name = string("input_783_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_783_dilations_0 = const()[name = string("input_783_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_341_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2680256))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2686720))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687296)))];
            tensor<fp16, [256]> const_342_to_fp16 = const()[name = string("const_342_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687616)))];
            tensor<fp16, [1, 256, 32, 32]> input_785_cast_fp16 = conv(bias = const_342_to_fp16, dilations = input_783_dilations_0, groups = input_783_groups_0, pad = input_783_pad_0, pad_type = input_783_pad_type_0, strides = input_783_strides_0, weight = const_341_to_fp16, x = input_781_cast_fp16)[name = string("input_785_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_787_cast_fp16 = relu(x = input_785_cast_fp16)[name = string("input_787_cast_fp16")];
            string input_789_pad_type_0 = const()[name = string("input_789_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_789_strides_0 = const()[name = string("input_789_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_789_pad_0 = const()[name = string("input_789_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2688192)))];
            tensor<int32, [2]> input_789_dilations_0 = const()[name = string("input_789_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_789_groups_0 = const()[name = string("input_789_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_343_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2688320))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2753920))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2754496)))];
            tensor<fp16, [256]> const_344_to_fp16 = const()[name = string("const_344_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2754816)))];
            tensor<fp16, [1, 256, 32, 32]> x_39_cast_fp16 = conv(bias = const_344_to_fp16, dilations = input_789_dilations_0, groups = input_789_groups_0, pad = input_789_pad_0, pad_type = input_789_pad_type_0, strides = input_789_strides_0, weight = const_343_to_fp16, x = input_787_cast_fp16)[name = string("x_39_cast_fp16")];
            tensor<int32, [4]> var_6956_begin_0 = const()[name = string("op_6956_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2755392)))];
            tensor<int32, [4]> var_6956_end_0 = const()[name = string("op_6956_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2755520)))];
            tensor<bool, [4]> var_6956_end_mask_0 = const()[name = string("op_6956_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_6956_cast_fp16 = slice_by_index(begin = var_6956_begin_0, end = var_6956_end_0, end_mask = var_6956_end_mask_0, x = x_39_cast_fp16)[name = string("op_6956_cast_fp16")];
            tensor<int32, [4]> var_6960_begin_0 = const()[name = string("op_6960_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2755648)))];
            tensor<int32, [4]> var_6960_end_0 = const()[name = string("op_6960_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2755776)))];
            tensor<bool, [4]> var_6960_end_mask_0 = const()[name = string("op_6960_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_6960_cast_fp16 = slice_by_index(begin = var_6960_begin_0, end = var_6960_end_0, end_mask = var_6960_end_mask_0, x = x_39_cast_fp16)[name = string("op_6960_cast_fp16")];
            tensor<int32, [4]> var_6964_begin_0 = const()[name = string("op_6964_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2755904)))];
            tensor<int32, [4]> var_6964_end_0 = const()[name = string("op_6964_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2756032)))];
            tensor<bool, [4]> var_6964_end_mask_0 = const()[name = string("op_6964_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_6964_cast_fp16 = slice_by_index(begin = var_6964_begin_0, end = var_6964_end_0, end_mask = var_6964_end_mask_0, x = x_39_cast_fp16)[name = string("op_6964_cast_fp16")];
            tensor<int32, [4]> var_6968_begin_0 = const()[name = string("op_6968_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2756160)))];
            tensor<int32, [4]> var_6968_end_0 = const()[name = string("op_6968_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2756288)))];
            tensor<bool, [4]> var_6968_end_mask_0 = const()[name = string("op_6968_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_6968_cast_fp16 = slice_by_index(begin = var_6968_begin_0, end = var_6968_end_0, end_mask = var_6968_end_mask_0, x = x_39_cast_fp16)[name = string("op_6968_cast_fp16")];
            string input_793_pad_type_0 = const()[name = string("input_793_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_793_strides_0 = const()[name = string("input_793_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_793_pad_0 = const()[name = string("input_793_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2756416)))];
            tensor<int32, [2]> input_793_dilations_0 = const()[name = string("input_793_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_793_groups_0 = const()[name = string("input_793_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_345_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2756544))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2760704))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2760896)))];
            tensor<fp16, [64]> const_346_to_fp16 = const()[name = string("const_346_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2761024)))];
            tensor<fp16, [1, 64, 32, 32]> input_795_cast_fp16 = conv(bias = const_346_to_fp16, dilations = input_793_dilations_0, groups = input_793_groups_0, pad = input_793_pad_0, pad_type = input_793_pad_type_0, strides = input_793_strides_0, weight = const_345_to_fp16, x = var_6960_cast_fp16)[name = string("input_795_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_797_cast_fp16 = relu(x = input_795_cast_fp16)[name = string("input_797_cast_fp16")];
            string input_799_pad_type_0 = const()[name = string("input_799_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_799_pad_0 = const()[name = string("input_799_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2761216)))];
            int32 input_799_groups_0 = const()[name = string("input_799_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_799_strides_0 = const()[name = string("input_799_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_799_dilations_0 = const()[name = string("input_799_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_347_to_fp16 = const()[name = string("const_347_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2761344)))];
            tensor<fp16, [64]> const_348_to_fp16 = const()[name = string("const_348_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2764608)))];
            tensor<fp16, [1, 64, 32, 32]> input_801_cast_fp16 = conv(bias = const_348_to_fp16, dilations = input_799_dilations_0, groups = input_799_groups_0, pad = input_799_pad_0, pad_type = input_799_pad_type_0, strides = input_799_strides_0, weight = const_347_to_fp16, x = input_797_cast_fp16)[name = string("input_801_cast_fp16")];
            string input_803_pad_type_0 = const()[name = string("input_803_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_803_strides_0 = const()[name = string("input_803_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_803_pad_0 = const()[name = string("input_803_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2764800)))];
            tensor<int32, [2]> input_803_dilations_0 = const()[name = string("input_803_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_803_groups_0 = const()[name = string("input_803_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_349_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2764928))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2769088))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2769280)))];
            tensor<fp16, [64]> const_350_to_fp16 = const()[name = string("const_350_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2769408)))];
            tensor<fp16, [1, 64, 32, 32]> input_805_cast_fp16 = conv(bias = const_350_to_fp16, dilations = input_803_dilations_0, groups = input_803_groups_0, pad = input_803_pad_0, pad_type = input_803_pad_type_0, strides = input_803_strides_0, weight = const_349_to_fp16, x = input_801_cast_fp16)[name = string("input_805_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_25_cast_fp16 = relu(x = input_805_cast_fp16)[name = string("out1_25_cast_fp16")];
            string input_809_pad_type_0 = const()[name = string("input_809_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_809_strides_0 = const()[name = string("input_809_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_809_pad_0 = const()[name = string("input_809_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2769600)))];
            tensor<int32, [2]> input_809_dilations_0 = const()[name = string("input_809_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_809_groups_0 = const()[name = string("input_809_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_351_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2769728))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2773888))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2774080)))];
            tensor<fp16, [64]> const_352_to_fp16 = const()[name = string("const_352_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2774208)))];
            tensor<fp16, [1, 64, 32, 32]> input_811_cast_fp16 = conv(bias = const_352_to_fp16, dilations = input_809_dilations_0, groups = input_809_groups_0, pad = input_809_pad_0, pad_type = input_809_pad_type_0, strides = input_809_strides_0, weight = const_351_to_fp16, x = var_6964_cast_fp16)[name = string("input_811_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_813_cast_fp16 = relu(x = input_811_cast_fp16)[name = string("input_813_cast_fp16")];
            string input_815_pad_type_0 = const()[name = string("input_815_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_815_pad_0 = const()[name = string("input_815_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2774400)))];
            int32 input_815_groups_0 = const()[name = string("input_815_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_815_strides_0 = const()[name = string("input_815_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_815_dilations_0 = const()[name = string("input_815_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_353_to_fp16 = const()[name = string("const_353_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2774528)))];
            tensor<fp16, [64]> const_354_to_fp16 = const()[name = string("const_354_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2777792)))];
            tensor<fp16, [1, 64, 32, 32]> input_817_cast_fp16 = conv(bias = const_354_to_fp16, dilations = input_815_dilations_0, groups = input_815_groups_0, pad = input_815_pad_0, pad_type = input_815_pad_type_0, strides = input_815_strides_0, weight = const_353_to_fp16, x = input_813_cast_fp16)[name = string("input_817_cast_fp16")];
            string input_819_pad_type_0 = const()[name = string("input_819_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_819_strides_0 = const()[name = string("input_819_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_819_pad_0 = const()[name = string("input_819_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2777984)))];
            tensor<int32, [2]> input_819_dilations_0 = const()[name = string("input_819_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_819_groups_0 = const()[name = string("input_819_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_355_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2778112))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2782272))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2782464)))];
            tensor<fp16, [64]> const_356_to_fp16 = const()[name = string("const_356_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2782592)))];
            tensor<fp16, [1, 64, 32, 32]> input_821_cast_fp16 = conv(bias = const_356_to_fp16, dilations = input_819_dilations_0, groups = input_819_groups_0, pad = input_819_pad_0, pad_type = input_819_pad_type_0, strides = input_819_strides_0, weight = const_355_to_fp16, x = input_817_cast_fp16)[name = string("input_821_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_25_cast_fp16 = relu(x = input_821_cast_fp16)[name = string("out2_25_cast_fp16")];
            string input_825_pad_type_0 = const()[name = string("input_825_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_825_strides_0 = const()[name = string("input_825_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_825_pad_0 = const()[name = string("input_825_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2782784)))];
            tensor<int32, [2]> input_825_dilations_0 = const()[name = string("input_825_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_825_groups_0 = const()[name = string("input_825_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_357_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2782912))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2787072))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2787264)))];
            tensor<fp16, [64]> const_358_to_fp16 = const()[name = string("const_358_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2787392)))];
            tensor<fp16, [1, 64, 32, 32]> input_827_cast_fp16 = conv(bias = const_358_to_fp16, dilations = input_825_dilations_0, groups = input_825_groups_0, pad = input_825_pad_0, pad_type = input_825_pad_type_0, strides = input_825_strides_0, weight = const_357_to_fp16, x = var_6968_cast_fp16)[name = string("input_827_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_829_cast_fp16 = relu(x = input_827_cast_fp16)[name = string("input_829_cast_fp16")];
            string input_831_pad_type_0 = const()[name = string("input_831_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_831_pad_0 = const()[name = string("input_831_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2787584)))];
            int32 input_831_groups_0 = const()[name = string("input_831_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_831_strides_0 = const()[name = string("input_831_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_831_dilations_0 = const()[name = string("input_831_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_359_to_fp16 = const()[name = string("const_359_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2787712)))];
            tensor<fp16, [64]> const_360_to_fp16 = const()[name = string("const_360_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2790976)))];
            tensor<fp16, [1, 64, 32, 32]> input_833_cast_fp16 = conv(bias = const_360_to_fp16, dilations = input_831_dilations_0, groups = input_831_groups_0, pad = input_831_pad_0, pad_type = input_831_pad_type_0, strides = input_831_strides_0, weight = const_359_to_fp16, x = input_829_cast_fp16)[name = string("input_833_cast_fp16")];
            string input_835_pad_type_0 = const()[name = string("input_835_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_835_strides_0 = const()[name = string("input_835_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_835_pad_0 = const()[name = string("input_835_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2791168)))];
            tensor<int32, [2]> input_835_dilations_0 = const()[name = string("input_835_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_835_groups_0 = const()[name = string("input_835_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_361_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2791296))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2795456))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2795648)))];
            tensor<fp16, [64]> const_362_to_fp16 = const()[name = string("const_362_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2795776)))];
            tensor<fp16, [1, 64, 32, 32]> input_837_cast_fp16 = conv(bias = const_362_to_fp16, dilations = input_835_dilations_0, groups = input_835_groups_0, pad = input_835_pad_0, pad_type = input_835_pad_type_0, strides = input_835_strides_0, weight = const_361_to_fp16, x = input_833_cast_fp16)[name = string("input_837_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_25_cast_fp16 = relu(x = input_837_cast_fp16)[name = string("out3_25_cast_fp16")];
            bool input_839_interleave_0 = const()[name = string("input_839_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_839_cast_fp16 = concat(axis = var_3877, interleave = input_839_interleave_0, values = (var_6956_cast_fp16, out1_25_cast_fp16, out2_25_cast_fp16, out3_25_cast_fp16))[name = string("input_839_cast_fp16")];
            string input_841_pad_type_0 = const()[name = string("input_841_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_841_strides_0 = const()[name = string("input_841_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_841_pad_0 = const()[name = string("input_841_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2795968)))];
            tensor<int32, [2]> input_841_dilations_0 = const()[name = string("input_841_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_841_groups_0 = const()[name = string("input_841_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_363_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2796096))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2861696))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2862272)))];
            tensor<fp16, [256]> const_364_to_fp16 = const()[name = string("const_364_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2862592)))];
            tensor<fp16, [1, 256, 32, 32]> input_843_cast_fp16 = conv(bias = const_364_to_fp16, dilations = input_841_dilations_0, groups = input_841_groups_0, pad = input_841_pad_0, pad_type = input_841_pad_type_0, strides = input_841_strides_0, weight = const_363_to_fp16, x = input_839_cast_fp16)[name = string("input_843_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_845_cast_fp16 = relu(x = input_843_cast_fp16)[name = string("input_845_cast_fp16")];
            string input_847_pad_type_0 = const()[name = string("input_847_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_847_pad_0 = const()[name = string("input_847_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2863168)))];
            int32 input_847_groups_0 = const()[name = string("input_847_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_847_strides_0 = const()[name = string("input_847_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_847_dilations_0 = const()[name = string("input_847_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_365_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2863296))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2869760))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2870336)))];
            tensor<fp16, [256]> const_366_to_fp16 = const()[name = string("const_366_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2870656)))];
            tensor<fp16, [1, 256, 32, 32]> input_849_cast_fp16 = conv(bias = const_366_to_fp16, dilations = input_847_dilations_0, groups = input_847_groups_0, pad = input_847_pad_0, pad_type = input_847_pad_type_0, strides = input_847_strides_0, weight = const_365_to_fp16, x = input_845_cast_fp16)[name = string("input_849_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_851_cast_fp16 = relu(x = input_849_cast_fp16)[name = string("input_851_cast_fp16")];
            string input_853_pad_type_0 = const()[name = string("input_853_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_853_strides_0 = const()[name = string("input_853_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_853_pad_0 = const()[name = string("input_853_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2871232)))];
            tensor<int32, [2]> input_853_dilations_0 = const()[name = string("input_853_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_853_groups_0 = const()[name = string("input_853_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_367_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2871360))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2936960))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2937536)))];
            tensor<fp16, [256]> const_368_to_fp16 = const()[name = string("const_368_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2937856)))];
            tensor<fp16, [1, 256, 32, 32]> y_17_cast_fp16 = conv(bias = const_368_to_fp16, dilations = input_853_dilations_0, groups = input_853_groups_0, pad = input_853_pad_0, pad_type = input_853_pad_type_0, strides = input_853_strides_0, weight = const_367_to_fp16, x = input_851_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_41_cast_fp16 = add(x = input_839_cast_fp16, y = y_17_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [4]> var_7068_begin_0 = const()[name = string("op_7068_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2938432)))];
            tensor<int32, [4]> var_7068_end_0 = const()[name = string("op_7068_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2938560)))];
            tensor<bool, [4]> var_7068_end_mask_0 = const()[name = string("op_7068_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7068_cast_fp16 = slice_by_index(begin = var_7068_begin_0, end = var_7068_end_0, end_mask = var_7068_end_mask_0, x = x_41_cast_fp16)[name = string("op_7068_cast_fp16")];
            tensor<int32, [4]> var_7072_begin_0 = const()[name = string("op_7072_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2938688)))];
            tensor<int32, [4]> var_7072_end_0 = const()[name = string("op_7072_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2938816)))];
            tensor<bool, [4]> var_7072_end_mask_0 = const()[name = string("op_7072_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7072_cast_fp16 = slice_by_index(begin = var_7072_begin_0, end = var_7072_end_0, end_mask = var_7072_end_mask_0, x = x_41_cast_fp16)[name = string("op_7072_cast_fp16")];
            tensor<int32, [4]> var_7076_begin_0 = const()[name = string("op_7076_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2938944)))];
            tensor<int32, [4]> var_7076_end_0 = const()[name = string("op_7076_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2939072)))];
            tensor<bool, [4]> var_7076_end_mask_0 = const()[name = string("op_7076_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7076_cast_fp16 = slice_by_index(begin = var_7076_begin_0, end = var_7076_end_0, end_mask = var_7076_end_mask_0, x = x_41_cast_fp16)[name = string("op_7076_cast_fp16")];
            tensor<int32, [4]> var_7080_begin_0 = const()[name = string("op_7080_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2939200)))];
            tensor<int32, [4]> var_7080_end_0 = const()[name = string("op_7080_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2939328)))];
            tensor<bool, [4]> var_7080_end_mask_0 = const()[name = string("op_7080_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7080_cast_fp16 = slice_by_index(begin = var_7080_begin_0, end = var_7080_end_0, end_mask = var_7080_end_mask_0, x = x_41_cast_fp16)[name = string("op_7080_cast_fp16")];
            string input_857_pad_type_0 = const()[name = string("input_857_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_857_strides_0 = const()[name = string("input_857_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_857_pad_0 = const()[name = string("input_857_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2939456)))];
            tensor<int32, [2]> input_857_dilations_0 = const()[name = string("input_857_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_857_groups_0 = const()[name = string("input_857_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_369_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2939584))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2943744))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2943936)))];
            tensor<fp16, [64]> const_370_to_fp16 = const()[name = string("const_370_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2944064)))];
            tensor<fp16, [1, 64, 32, 32]> input_859_cast_fp16 = conv(bias = const_370_to_fp16, dilations = input_857_dilations_0, groups = input_857_groups_0, pad = input_857_pad_0, pad_type = input_857_pad_type_0, strides = input_857_strides_0, weight = const_369_to_fp16, x = var_7072_cast_fp16)[name = string("input_859_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_861_cast_fp16 = relu(x = input_859_cast_fp16)[name = string("input_861_cast_fp16")];
            string input_863_pad_type_0 = const()[name = string("input_863_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_863_pad_0 = const()[name = string("input_863_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2944256)))];
            int32 input_863_groups_0 = const()[name = string("input_863_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_863_strides_0 = const()[name = string("input_863_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_863_dilations_0 = const()[name = string("input_863_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_371_to_fp16 = const()[name = string("const_371_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2944384)))];
            tensor<fp16, [64]> const_372_to_fp16 = const()[name = string("const_372_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2947648)))];
            tensor<fp16, [1, 64, 32, 32]> input_865_cast_fp16 = conv(bias = const_372_to_fp16, dilations = input_863_dilations_0, groups = input_863_groups_0, pad = input_863_pad_0, pad_type = input_863_pad_type_0, strides = input_863_strides_0, weight = const_371_to_fp16, x = input_861_cast_fp16)[name = string("input_865_cast_fp16")];
            string input_867_pad_type_0 = const()[name = string("input_867_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_867_strides_0 = const()[name = string("input_867_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_867_pad_0 = const()[name = string("input_867_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2947840)))];
            tensor<int32, [2]> input_867_dilations_0 = const()[name = string("input_867_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_867_groups_0 = const()[name = string("input_867_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_373_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2947968))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2952128))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2952320)))];
            tensor<fp16, [64]> const_374_to_fp16 = const()[name = string("const_374_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2952448)))];
            tensor<fp16, [1, 64, 32, 32]> input_869_cast_fp16 = conv(bias = const_374_to_fp16, dilations = input_867_dilations_0, groups = input_867_groups_0, pad = input_867_pad_0, pad_type = input_867_pad_type_0, strides = input_867_strides_0, weight = const_373_to_fp16, x = input_865_cast_fp16)[name = string("input_869_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_27_cast_fp16 = relu(x = input_869_cast_fp16)[name = string("out1_27_cast_fp16")];
            string input_873_pad_type_0 = const()[name = string("input_873_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_873_strides_0 = const()[name = string("input_873_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_873_pad_0 = const()[name = string("input_873_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2952640)))];
            tensor<int32, [2]> input_873_dilations_0 = const()[name = string("input_873_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_873_groups_0 = const()[name = string("input_873_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_375_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2952768))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2956928))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2957120)))];
            tensor<fp16, [64]> const_376_to_fp16 = const()[name = string("const_376_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2957248)))];
            tensor<fp16, [1, 64, 32, 32]> input_875_cast_fp16 = conv(bias = const_376_to_fp16, dilations = input_873_dilations_0, groups = input_873_groups_0, pad = input_873_pad_0, pad_type = input_873_pad_type_0, strides = input_873_strides_0, weight = const_375_to_fp16, x = var_7076_cast_fp16)[name = string("input_875_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_877_cast_fp16 = relu(x = input_875_cast_fp16)[name = string("input_877_cast_fp16")];
            string input_879_pad_type_0 = const()[name = string("input_879_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_879_pad_0 = const()[name = string("input_879_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2957440)))];
            int32 input_879_groups_0 = const()[name = string("input_879_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_879_strides_0 = const()[name = string("input_879_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_879_dilations_0 = const()[name = string("input_879_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_377_to_fp16 = const()[name = string("const_377_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2957568)))];
            tensor<fp16, [64]> const_378_to_fp16 = const()[name = string("const_378_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2960832)))];
            tensor<fp16, [1, 64, 32, 32]> input_881_cast_fp16 = conv(bias = const_378_to_fp16, dilations = input_879_dilations_0, groups = input_879_groups_0, pad = input_879_pad_0, pad_type = input_879_pad_type_0, strides = input_879_strides_0, weight = const_377_to_fp16, x = input_877_cast_fp16)[name = string("input_881_cast_fp16")];
            string input_883_pad_type_0 = const()[name = string("input_883_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_883_strides_0 = const()[name = string("input_883_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_883_pad_0 = const()[name = string("input_883_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2961024)))];
            tensor<int32, [2]> input_883_dilations_0 = const()[name = string("input_883_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_883_groups_0 = const()[name = string("input_883_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_379_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2961152))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2965312))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2965504)))];
            tensor<fp16, [64]> const_380_to_fp16 = const()[name = string("const_380_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2965632)))];
            tensor<fp16, [1, 64, 32, 32]> input_885_cast_fp16 = conv(bias = const_380_to_fp16, dilations = input_883_dilations_0, groups = input_883_groups_0, pad = input_883_pad_0, pad_type = input_883_pad_type_0, strides = input_883_strides_0, weight = const_379_to_fp16, x = input_881_cast_fp16)[name = string("input_885_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_27_cast_fp16 = relu(x = input_885_cast_fp16)[name = string("out2_27_cast_fp16")];
            string input_889_pad_type_0 = const()[name = string("input_889_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_889_strides_0 = const()[name = string("input_889_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_889_pad_0 = const()[name = string("input_889_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2965824)))];
            tensor<int32, [2]> input_889_dilations_0 = const()[name = string("input_889_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_889_groups_0 = const()[name = string("input_889_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_381_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2965952))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2970112))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2970304)))];
            tensor<fp16, [64]> const_382_to_fp16 = const()[name = string("const_382_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2970432)))];
            tensor<fp16, [1, 64, 32, 32]> input_891_cast_fp16 = conv(bias = const_382_to_fp16, dilations = input_889_dilations_0, groups = input_889_groups_0, pad = input_889_pad_0, pad_type = input_889_pad_type_0, strides = input_889_strides_0, weight = const_381_to_fp16, x = var_7080_cast_fp16)[name = string("input_891_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_893_cast_fp16 = relu(x = input_891_cast_fp16)[name = string("input_893_cast_fp16")];
            string input_895_pad_type_0 = const()[name = string("input_895_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_895_pad_0 = const()[name = string("input_895_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2970624)))];
            int32 input_895_groups_0 = const()[name = string("input_895_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_895_strides_0 = const()[name = string("input_895_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_895_dilations_0 = const()[name = string("input_895_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_383_to_fp16 = const()[name = string("const_383_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2970752)))];
            tensor<fp16, [64]> const_384_to_fp16 = const()[name = string("const_384_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2974016)))];
            tensor<fp16, [1, 64, 32, 32]> input_897_cast_fp16 = conv(bias = const_384_to_fp16, dilations = input_895_dilations_0, groups = input_895_groups_0, pad = input_895_pad_0, pad_type = input_895_pad_type_0, strides = input_895_strides_0, weight = const_383_to_fp16, x = input_893_cast_fp16)[name = string("input_897_cast_fp16")];
            string input_899_pad_type_0 = const()[name = string("input_899_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_899_strides_0 = const()[name = string("input_899_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_899_pad_0 = const()[name = string("input_899_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2974208)))];
            tensor<int32, [2]> input_899_dilations_0 = const()[name = string("input_899_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_899_groups_0 = const()[name = string("input_899_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_385_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2974336))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2978496))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2978688)))];
            tensor<fp16, [64]> const_386_to_fp16 = const()[name = string("const_386_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2978816)))];
            tensor<fp16, [1, 64, 32, 32]> input_901_cast_fp16 = conv(bias = const_386_to_fp16, dilations = input_899_dilations_0, groups = input_899_groups_0, pad = input_899_pad_0, pad_type = input_899_pad_type_0, strides = input_899_strides_0, weight = const_385_to_fp16, x = input_897_cast_fp16)[name = string("input_901_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_27_cast_fp16 = relu(x = input_901_cast_fp16)[name = string("out3_27_cast_fp16")];
            bool input_903_interleave_0 = const()[name = string("input_903_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_903_cast_fp16 = concat(axis = var_3877, interleave = input_903_interleave_0, values = (var_7068_cast_fp16, out1_27_cast_fp16, out2_27_cast_fp16, out3_27_cast_fp16))[name = string("input_903_cast_fp16")];
            string input_905_pad_type_0 = const()[name = string("input_905_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_905_strides_0 = const()[name = string("input_905_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_905_pad_0 = const()[name = string("input_905_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2979008)))];
            tensor<int32, [2]> input_905_dilations_0 = const()[name = string("input_905_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_905_groups_0 = const()[name = string("input_905_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_387_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2979136))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3044736))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3045312)))];
            tensor<fp16, [256]> const_388_to_fp16 = const()[name = string("const_388_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3045632)))];
            tensor<fp16, [1, 256, 32, 32]> input_907_cast_fp16 = conv(bias = const_388_to_fp16, dilations = input_905_dilations_0, groups = input_905_groups_0, pad = input_905_pad_0, pad_type = input_905_pad_type_0, strides = input_905_strides_0, weight = const_387_to_fp16, x = input_903_cast_fp16)[name = string("input_907_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_909_cast_fp16 = relu(x = input_907_cast_fp16)[name = string("input_909_cast_fp16")];
            string input_911_pad_type_0 = const()[name = string("input_911_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_911_pad_0 = const()[name = string("input_911_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3046208)))];
            int32 input_911_groups_0 = const()[name = string("input_911_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_911_strides_0 = const()[name = string("input_911_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_911_dilations_0 = const()[name = string("input_911_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_389_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3046336))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052800))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053376)))];
            tensor<fp16, [256]> const_390_to_fp16 = const()[name = string("const_390_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053696)))];
            tensor<fp16, [1, 256, 32, 32]> input_913_cast_fp16 = conv(bias = const_390_to_fp16, dilations = input_911_dilations_0, groups = input_911_groups_0, pad = input_911_pad_0, pad_type = input_911_pad_type_0, strides = input_911_strides_0, weight = const_389_to_fp16, x = input_909_cast_fp16)[name = string("input_913_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_915_cast_fp16 = relu(x = input_913_cast_fp16)[name = string("input_915_cast_fp16")];
            string input_917_pad_type_0 = const()[name = string("input_917_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_917_strides_0 = const()[name = string("input_917_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_917_pad_0 = const()[name = string("input_917_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3054272)))];
            tensor<int32, [2]> input_917_dilations_0 = const()[name = string("input_917_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_917_groups_0 = const()[name = string("input_917_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_391_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3054400))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3120000))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3120576)))];
            tensor<fp16, [256]> const_392_to_fp16 = const()[name = string("const_392_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3120896)))];
            tensor<fp16, [1, 256, 32, 32]> y_19_cast_fp16 = conv(bias = const_392_to_fp16, dilations = input_917_dilations_0, groups = input_917_groups_0, pad = input_917_pad_0, pad_type = input_917_pad_type_0, strides = input_917_strides_0, weight = const_391_to_fp16, x = input_915_cast_fp16)[name = string("y_19_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_43_cast_fp16 = add(x = input_903_cast_fp16, y = y_19_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [4]> var_7180_begin_0 = const()[name = string("op_7180_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3121472)))];
            tensor<int32, [4]> var_7180_end_0 = const()[name = string("op_7180_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3121600)))];
            tensor<bool, [4]> var_7180_end_mask_0 = const()[name = string("op_7180_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7180_cast_fp16 = slice_by_index(begin = var_7180_begin_0, end = var_7180_end_0, end_mask = var_7180_end_mask_0, x = x_43_cast_fp16)[name = string("op_7180_cast_fp16")];
            tensor<int32, [4]> var_7184_begin_0 = const()[name = string("op_7184_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3121728)))];
            tensor<int32, [4]> var_7184_end_0 = const()[name = string("op_7184_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3121856)))];
            tensor<bool, [4]> var_7184_end_mask_0 = const()[name = string("op_7184_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7184_cast_fp16 = slice_by_index(begin = var_7184_begin_0, end = var_7184_end_0, end_mask = var_7184_end_mask_0, x = x_43_cast_fp16)[name = string("op_7184_cast_fp16")];
            tensor<int32, [4]> var_7188_begin_0 = const()[name = string("op_7188_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3121984)))];
            tensor<int32, [4]> var_7188_end_0 = const()[name = string("op_7188_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3122112)))];
            tensor<bool, [4]> var_7188_end_mask_0 = const()[name = string("op_7188_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7188_cast_fp16 = slice_by_index(begin = var_7188_begin_0, end = var_7188_end_0, end_mask = var_7188_end_mask_0, x = x_43_cast_fp16)[name = string("op_7188_cast_fp16")];
            tensor<int32, [4]> var_7192_begin_0 = const()[name = string("op_7192_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3122240)))];
            tensor<int32, [4]> var_7192_end_0 = const()[name = string("op_7192_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3122368)))];
            tensor<bool, [4]> var_7192_end_mask_0 = const()[name = string("op_7192_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7192_cast_fp16 = slice_by_index(begin = var_7192_begin_0, end = var_7192_end_0, end_mask = var_7192_end_mask_0, x = x_43_cast_fp16)[name = string("op_7192_cast_fp16")];
            string input_921_pad_type_0 = const()[name = string("input_921_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_921_strides_0 = const()[name = string("input_921_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_921_pad_0 = const()[name = string("input_921_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3122496)))];
            tensor<int32, [2]> input_921_dilations_0 = const()[name = string("input_921_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_921_groups_0 = const()[name = string("input_921_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_393_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3122624))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3126784))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3126976)))];
            tensor<fp16, [64]> const_394_to_fp16 = const()[name = string("const_394_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3127104)))];
            tensor<fp16, [1, 64, 32, 32]> input_923_cast_fp16 = conv(bias = const_394_to_fp16, dilations = input_921_dilations_0, groups = input_921_groups_0, pad = input_921_pad_0, pad_type = input_921_pad_type_0, strides = input_921_strides_0, weight = const_393_to_fp16, x = var_7184_cast_fp16)[name = string("input_923_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_925_cast_fp16 = relu(x = input_923_cast_fp16)[name = string("input_925_cast_fp16")];
            string input_927_pad_type_0 = const()[name = string("input_927_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_927_pad_0 = const()[name = string("input_927_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3127296)))];
            int32 input_927_groups_0 = const()[name = string("input_927_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_927_strides_0 = const()[name = string("input_927_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_927_dilations_0 = const()[name = string("input_927_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_395_to_fp16 = const()[name = string("const_395_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3127424)))];
            tensor<fp16, [64]> const_396_to_fp16 = const()[name = string("const_396_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3130688)))];
            tensor<fp16, [1, 64, 32, 32]> input_929_cast_fp16 = conv(bias = const_396_to_fp16, dilations = input_927_dilations_0, groups = input_927_groups_0, pad = input_927_pad_0, pad_type = input_927_pad_type_0, strides = input_927_strides_0, weight = const_395_to_fp16, x = input_925_cast_fp16)[name = string("input_929_cast_fp16")];
            string input_931_pad_type_0 = const()[name = string("input_931_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_931_strides_0 = const()[name = string("input_931_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_931_pad_0 = const()[name = string("input_931_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3130880)))];
            tensor<int32, [2]> input_931_dilations_0 = const()[name = string("input_931_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_931_groups_0 = const()[name = string("input_931_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_397_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3131008))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3135168))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3135360)))];
            tensor<fp16, [64]> const_398_to_fp16 = const()[name = string("const_398_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3135488)))];
            tensor<fp16, [1, 64, 32, 32]> input_933_cast_fp16 = conv(bias = const_398_to_fp16, dilations = input_931_dilations_0, groups = input_931_groups_0, pad = input_931_pad_0, pad_type = input_931_pad_type_0, strides = input_931_strides_0, weight = const_397_to_fp16, x = input_929_cast_fp16)[name = string("input_933_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_29_cast_fp16 = relu(x = input_933_cast_fp16)[name = string("out1_29_cast_fp16")];
            string input_937_pad_type_0 = const()[name = string("input_937_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_937_strides_0 = const()[name = string("input_937_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_937_pad_0 = const()[name = string("input_937_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3135680)))];
            tensor<int32, [2]> input_937_dilations_0 = const()[name = string("input_937_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_937_groups_0 = const()[name = string("input_937_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_399_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3135808))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3139968))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3140160)))];
            tensor<fp16, [64]> const_400_to_fp16 = const()[name = string("const_400_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3140288)))];
            tensor<fp16, [1, 64, 32, 32]> input_939_cast_fp16 = conv(bias = const_400_to_fp16, dilations = input_937_dilations_0, groups = input_937_groups_0, pad = input_937_pad_0, pad_type = input_937_pad_type_0, strides = input_937_strides_0, weight = const_399_to_fp16, x = var_7188_cast_fp16)[name = string("input_939_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_941_cast_fp16 = relu(x = input_939_cast_fp16)[name = string("input_941_cast_fp16")];
            string input_943_pad_type_0 = const()[name = string("input_943_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_943_pad_0 = const()[name = string("input_943_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3140480)))];
            int32 input_943_groups_0 = const()[name = string("input_943_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_943_strides_0 = const()[name = string("input_943_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_943_dilations_0 = const()[name = string("input_943_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_401_to_fp16 = const()[name = string("const_401_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3140608)))];
            tensor<fp16, [64]> const_402_to_fp16 = const()[name = string("const_402_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3143872)))];
            tensor<fp16, [1, 64, 32, 32]> input_945_cast_fp16 = conv(bias = const_402_to_fp16, dilations = input_943_dilations_0, groups = input_943_groups_0, pad = input_943_pad_0, pad_type = input_943_pad_type_0, strides = input_943_strides_0, weight = const_401_to_fp16, x = input_941_cast_fp16)[name = string("input_945_cast_fp16")];
            string input_947_pad_type_0 = const()[name = string("input_947_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_947_strides_0 = const()[name = string("input_947_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_947_pad_0 = const()[name = string("input_947_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3144064)))];
            tensor<int32, [2]> input_947_dilations_0 = const()[name = string("input_947_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_947_groups_0 = const()[name = string("input_947_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_403_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3144192))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148352))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148544)))];
            tensor<fp16, [64]> const_404_to_fp16 = const()[name = string("const_404_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148672)))];
            tensor<fp16, [1, 64, 32, 32]> input_949_cast_fp16 = conv(bias = const_404_to_fp16, dilations = input_947_dilations_0, groups = input_947_groups_0, pad = input_947_pad_0, pad_type = input_947_pad_type_0, strides = input_947_strides_0, weight = const_403_to_fp16, x = input_945_cast_fp16)[name = string("input_949_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_29_cast_fp16 = relu(x = input_949_cast_fp16)[name = string("out2_29_cast_fp16")];
            string input_953_pad_type_0 = const()[name = string("input_953_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_953_strides_0 = const()[name = string("input_953_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_953_pad_0 = const()[name = string("input_953_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148864)))];
            tensor<int32, [2]> input_953_dilations_0 = const()[name = string("input_953_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_953_groups_0 = const()[name = string("input_953_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_405_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148992))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3153152))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3153344)))];
            tensor<fp16, [64]> const_406_to_fp16 = const()[name = string("const_406_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3153472)))];
            tensor<fp16, [1, 64, 32, 32]> input_955_cast_fp16 = conv(bias = const_406_to_fp16, dilations = input_953_dilations_0, groups = input_953_groups_0, pad = input_953_pad_0, pad_type = input_953_pad_type_0, strides = input_953_strides_0, weight = const_405_to_fp16, x = var_7192_cast_fp16)[name = string("input_955_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_957_cast_fp16 = relu(x = input_955_cast_fp16)[name = string("input_957_cast_fp16")];
            string input_959_pad_type_0 = const()[name = string("input_959_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_959_pad_0 = const()[name = string("input_959_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3153664)))];
            int32 input_959_groups_0 = const()[name = string("input_959_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_959_strides_0 = const()[name = string("input_959_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_959_dilations_0 = const()[name = string("input_959_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_407_to_fp16 = const()[name = string("const_407_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3153792)))];
            tensor<fp16, [64]> const_408_to_fp16 = const()[name = string("const_408_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3157056)))];
            tensor<fp16, [1, 64, 32, 32]> input_961_cast_fp16 = conv(bias = const_408_to_fp16, dilations = input_959_dilations_0, groups = input_959_groups_0, pad = input_959_pad_0, pad_type = input_959_pad_type_0, strides = input_959_strides_0, weight = const_407_to_fp16, x = input_957_cast_fp16)[name = string("input_961_cast_fp16")];
            string input_963_pad_type_0 = const()[name = string("input_963_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_963_strides_0 = const()[name = string("input_963_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_963_pad_0 = const()[name = string("input_963_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3157248)))];
            tensor<int32, [2]> input_963_dilations_0 = const()[name = string("input_963_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_963_groups_0 = const()[name = string("input_963_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_409_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3157376))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3161536))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3161728)))];
            tensor<fp16, [64]> const_410_to_fp16 = const()[name = string("const_410_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3161856)))];
            tensor<fp16, [1, 64, 32, 32]> input_965_cast_fp16 = conv(bias = const_410_to_fp16, dilations = input_963_dilations_0, groups = input_963_groups_0, pad = input_963_pad_0, pad_type = input_963_pad_type_0, strides = input_963_strides_0, weight = const_409_to_fp16, x = input_961_cast_fp16)[name = string("input_965_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_29_cast_fp16 = relu(x = input_965_cast_fp16)[name = string("out3_29_cast_fp16")];
            bool input_967_interleave_0 = const()[name = string("input_967_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_967_cast_fp16 = concat(axis = var_3877, interleave = input_967_interleave_0, values = (var_7180_cast_fp16, out1_29_cast_fp16, out2_29_cast_fp16, out3_29_cast_fp16))[name = string("input_967_cast_fp16")];
            string input_969_pad_type_0 = const()[name = string("input_969_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_969_strides_0 = const()[name = string("input_969_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_969_pad_0 = const()[name = string("input_969_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3162048)))];
            tensor<int32, [2]> input_969_dilations_0 = const()[name = string("input_969_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_969_groups_0 = const()[name = string("input_969_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_411_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3162176))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3227776))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3228352)))];
            tensor<fp16, [256]> const_412_to_fp16 = const()[name = string("const_412_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3228672)))];
            tensor<fp16, [1, 256, 32, 32]> input_971_cast_fp16 = conv(bias = const_412_to_fp16, dilations = input_969_dilations_0, groups = input_969_groups_0, pad = input_969_pad_0, pad_type = input_969_pad_type_0, strides = input_969_strides_0, weight = const_411_to_fp16, x = input_967_cast_fp16)[name = string("input_971_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_973_cast_fp16 = relu(x = input_971_cast_fp16)[name = string("input_973_cast_fp16")];
            string input_975_pad_type_0 = const()[name = string("input_975_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_975_pad_0 = const()[name = string("input_975_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3229248)))];
            int32 input_975_groups_0 = const()[name = string("input_975_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_975_strides_0 = const()[name = string("input_975_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_975_dilations_0 = const()[name = string("input_975_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_413_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3229376))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3235840))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3236416)))];
            tensor<fp16, [256]> const_414_to_fp16 = const()[name = string("const_414_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3236736)))];
            tensor<fp16, [1, 256, 32, 32]> input_977_cast_fp16 = conv(bias = const_414_to_fp16, dilations = input_975_dilations_0, groups = input_975_groups_0, pad = input_975_pad_0, pad_type = input_975_pad_type_0, strides = input_975_strides_0, weight = const_413_to_fp16, x = input_973_cast_fp16)[name = string("input_977_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_979_cast_fp16 = relu(x = input_977_cast_fp16)[name = string("input_979_cast_fp16")];
            string input_981_pad_type_0 = const()[name = string("input_981_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_981_strides_0 = const()[name = string("input_981_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_981_pad_0 = const()[name = string("input_981_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3237312)))];
            tensor<int32, [2]> input_981_dilations_0 = const()[name = string("input_981_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_981_groups_0 = const()[name = string("input_981_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_415_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3237440))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3303040))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3303616)))];
            tensor<fp16, [256]> const_416_to_fp16 = const()[name = string("const_416_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3303936)))];
            tensor<fp16, [1, 256, 32, 32]> y_21_cast_fp16 = conv(bias = const_416_to_fp16, dilations = input_981_dilations_0, groups = input_981_groups_0, pad = input_981_pad_0, pad_type = input_981_pad_type_0, strides = input_981_strides_0, weight = const_415_to_fp16, x = input_979_cast_fp16)[name = string("y_21_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_45_cast_fp16 = add(x = input_967_cast_fp16, y = y_21_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<int32, [4]> var_7292_begin_0 = const()[name = string("op_7292_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3304512)))];
            tensor<int32, [4]> var_7292_end_0 = const()[name = string("op_7292_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3304640)))];
            tensor<bool, [4]> var_7292_end_mask_0 = const()[name = string("op_7292_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7292_cast_fp16 = slice_by_index(begin = var_7292_begin_0, end = var_7292_end_0, end_mask = var_7292_end_mask_0, x = x_45_cast_fp16)[name = string("op_7292_cast_fp16")];
            tensor<int32, [4]> var_7296_begin_0 = const()[name = string("op_7296_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3304768)))];
            tensor<int32, [4]> var_7296_end_0 = const()[name = string("op_7296_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3304896)))];
            tensor<bool, [4]> var_7296_end_mask_0 = const()[name = string("op_7296_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7296_cast_fp16 = slice_by_index(begin = var_7296_begin_0, end = var_7296_end_0, end_mask = var_7296_end_mask_0, x = x_45_cast_fp16)[name = string("op_7296_cast_fp16")];
            tensor<int32, [4]> var_7300_begin_0 = const()[name = string("op_7300_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3305024)))];
            tensor<int32, [4]> var_7300_end_0 = const()[name = string("op_7300_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3305152)))];
            tensor<bool, [4]> var_7300_end_mask_0 = const()[name = string("op_7300_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7300_cast_fp16 = slice_by_index(begin = var_7300_begin_0, end = var_7300_end_0, end_mask = var_7300_end_mask_0, x = x_45_cast_fp16)[name = string("op_7300_cast_fp16")];
            tensor<int32, [4]> var_7304_begin_0 = const()[name = string("op_7304_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3305280)))];
            tensor<int32, [4]> var_7304_end_0 = const()[name = string("op_7304_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3305408)))];
            tensor<bool, [4]> var_7304_end_mask_0 = const()[name = string("op_7304_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7304_cast_fp16 = slice_by_index(begin = var_7304_begin_0, end = var_7304_end_0, end_mask = var_7304_end_mask_0, x = x_45_cast_fp16)[name = string("op_7304_cast_fp16")];
            string input_985_pad_type_0 = const()[name = string("input_985_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_985_strides_0 = const()[name = string("input_985_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_985_pad_0 = const()[name = string("input_985_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3305536)))];
            tensor<int32, [2]> input_985_dilations_0 = const()[name = string("input_985_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_985_groups_0 = const()[name = string("input_985_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_417_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3305664))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3309824))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3310016)))];
            tensor<fp16, [64]> const_418_to_fp16 = const()[name = string("const_418_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3310144)))];
            tensor<fp16, [1, 64, 32, 32]> input_987_cast_fp16 = conv(bias = const_418_to_fp16, dilations = input_985_dilations_0, groups = input_985_groups_0, pad = input_985_pad_0, pad_type = input_985_pad_type_0, strides = input_985_strides_0, weight = const_417_to_fp16, x = var_7296_cast_fp16)[name = string("input_987_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_989_cast_fp16 = relu(x = input_987_cast_fp16)[name = string("input_989_cast_fp16")];
            string input_991_pad_type_0 = const()[name = string("input_991_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_991_pad_0 = const()[name = string("input_991_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3310336)))];
            int32 input_991_groups_0 = const()[name = string("input_991_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_991_strides_0 = const()[name = string("input_991_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_991_dilations_0 = const()[name = string("input_991_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_419_to_fp16 = const()[name = string("const_419_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3310464)))];
            tensor<fp16, [64]> const_420_to_fp16 = const()[name = string("const_420_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3313728)))];
            tensor<fp16, [1, 64, 32, 32]> input_993_cast_fp16 = conv(bias = const_420_to_fp16, dilations = input_991_dilations_0, groups = input_991_groups_0, pad = input_991_pad_0, pad_type = input_991_pad_type_0, strides = input_991_strides_0, weight = const_419_to_fp16, x = input_989_cast_fp16)[name = string("input_993_cast_fp16")];
            string input_995_pad_type_0 = const()[name = string("input_995_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_995_strides_0 = const()[name = string("input_995_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_995_pad_0 = const()[name = string("input_995_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3313920)))];
            tensor<int32, [2]> input_995_dilations_0 = const()[name = string("input_995_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_995_groups_0 = const()[name = string("input_995_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_421_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3314048))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3318208))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3318400)))];
            tensor<fp16, [64]> const_422_to_fp16 = const()[name = string("const_422_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3318528)))];
            tensor<fp16, [1, 64, 32, 32]> input_997_cast_fp16 = conv(bias = const_422_to_fp16, dilations = input_995_dilations_0, groups = input_995_groups_0, pad = input_995_pad_0, pad_type = input_995_pad_type_0, strides = input_995_strides_0, weight = const_421_to_fp16, x = input_993_cast_fp16)[name = string("input_997_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_31_cast_fp16 = relu(x = input_997_cast_fp16)[name = string("out1_31_cast_fp16")];
            string input_1001_pad_type_0 = const()[name = string("input_1001_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1001_strides_0 = const()[name = string("input_1001_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1001_pad_0 = const()[name = string("input_1001_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3318720)))];
            tensor<int32, [2]> input_1001_dilations_0 = const()[name = string("input_1001_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1001_groups_0 = const()[name = string("input_1001_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_423_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3318848))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3323008))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3323200)))];
            tensor<fp16, [64]> const_424_to_fp16 = const()[name = string("const_424_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3323328)))];
            tensor<fp16, [1, 64, 32, 32]> input_1003_cast_fp16 = conv(bias = const_424_to_fp16, dilations = input_1001_dilations_0, groups = input_1001_groups_0, pad = input_1001_pad_0, pad_type = input_1001_pad_type_0, strides = input_1001_strides_0, weight = const_423_to_fp16, x = var_7300_cast_fp16)[name = string("input_1003_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1005_cast_fp16 = relu(x = input_1003_cast_fp16)[name = string("input_1005_cast_fp16")];
            string input_1007_pad_type_0 = const()[name = string("input_1007_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1007_pad_0 = const()[name = string("input_1007_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3323520)))];
            int32 input_1007_groups_0 = const()[name = string("input_1007_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_1007_strides_0 = const()[name = string("input_1007_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1007_dilations_0 = const()[name = string("input_1007_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_425_to_fp16 = const()[name = string("const_425_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3323648)))];
            tensor<fp16, [64]> const_426_to_fp16 = const()[name = string("const_426_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3326912)))];
            tensor<fp16, [1, 64, 32, 32]> input_1009_cast_fp16 = conv(bias = const_426_to_fp16, dilations = input_1007_dilations_0, groups = input_1007_groups_0, pad = input_1007_pad_0, pad_type = input_1007_pad_type_0, strides = input_1007_strides_0, weight = const_425_to_fp16, x = input_1005_cast_fp16)[name = string("input_1009_cast_fp16")];
            string input_1011_pad_type_0 = const()[name = string("input_1011_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1011_strides_0 = const()[name = string("input_1011_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1011_pad_0 = const()[name = string("input_1011_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3327104)))];
            tensor<int32, [2]> input_1011_dilations_0 = const()[name = string("input_1011_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1011_groups_0 = const()[name = string("input_1011_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_427_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3327232))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3331392))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3331584)))];
            tensor<fp16, [64]> const_428_to_fp16 = const()[name = string("const_428_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3331712)))];
            tensor<fp16, [1, 64, 32, 32]> input_1013_cast_fp16 = conv(bias = const_428_to_fp16, dilations = input_1011_dilations_0, groups = input_1011_groups_0, pad = input_1011_pad_0, pad_type = input_1011_pad_type_0, strides = input_1011_strides_0, weight = const_427_to_fp16, x = input_1009_cast_fp16)[name = string("input_1013_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_31_cast_fp16 = relu(x = input_1013_cast_fp16)[name = string("out2_31_cast_fp16")];
            string input_1017_pad_type_0 = const()[name = string("input_1017_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1017_strides_0 = const()[name = string("input_1017_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1017_pad_0 = const()[name = string("input_1017_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3331904)))];
            tensor<int32, [2]> input_1017_dilations_0 = const()[name = string("input_1017_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1017_groups_0 = const()[name = string("input_1017_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_429_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3332032))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3336192))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3336384)))];
            tensor<fp16, [64]> const_430_to_fp16 = const()[name = string("const_430_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3336512)))];
            tensor<fp16, [1, 64, 32, 32]> input_1019_cast_fp16 = conv(bias = const_430_to_fp16, dilations = input_1017_dilations_0, groups = input_1017_groups_0, pad = input_1017_pad_0, pad_type = input_1017_pad_type_0, strides = input_1017_strides_0, weight = const_429_to_fp16, x = var_7304_cast_fp16)[name = string("input_1019_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1021_cast_fp16 = relu(x = input_1019_cast_fp16)[name = string("input_1021_cast_fp16")];
            string input_1023_pad_type_0 = const()[name = string("input_1023_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1023_pad_0 = const()[name = string("input_1023_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3336704)))];
            int32 input_1023_groups_0 = const()[name = string("input_1023_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_1023_strides_0 = const()[name = string("input_1023_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1023_dilations_0 = const()[name = string("input_1023_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_431_to_fp16 = const()[name = string("const_431_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3336832)))];
            tensor<fp16, [64]> const_432_to_fp16 = const()[name = string("const_432_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3340096)))];
            tensor<fp16, [1, 64, 32, 32]> input_1025_cast_fp16 = conv(bias = const_432_to_fp16, dilations = input_1023_dilations_0, groups = input_1023_groups_0, pad = input_1023_pad_0, pad_type = input_1023_pad_type_0, strides = input_1023_strides_0, weight = const_431_to_fp16, x = input_1021_cast_fp16)[name = string("input_1025_cast_fp16")];
            string input_1027_pad_type_0 = const()[name = string("input_1027_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1027_strides_0 = const()[name = string("input_1027_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1027_pad_0 = const()[name = string("input_1027_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3340288)))];
            tensor<int32, [2]> input_1027_dilations_0 = const()[name = string("input_1027_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1027_groups_0 = const()[name = string("input_1027_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_433_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3340416))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3344576))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3344768)))];
            tensor<fp16, [64]> const_434_to_fp16 = const()[name = string("const_434_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3344896)))];
            tensor<fp16, [1, 64, 32, 32]> input_1029_cast_fp16 = conv(bias = const_434_to_fp16, dilations = input_1027_dilations_0, groups = input_1027_groups_0, pad = input_1027_pad_0, pad_type = input_1027_pad_type_0, strides = input_1027_strides_0, weight = const_433_to_fp16, x = input_1025_cast_fp16)[name = string("input_1029_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_31_cast_fp16 = relu(x = input_1029_cast_fp16)[name = string("out3_31_cast_fp16")];
            bool input_1031_interleave_0 = const()[name = string("input_1031_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_1031_cast_fp16 = concat(axis = var_3877, interleave = input_1031_interleave_0, values = (var_7292_cast_fp16, out1_31_cast_fp16, out2_31_cast_fp16, out3_31_cast_fp16))[name = string("input_1031_cast_fp16")];
            string input_1033_pad_type_0 = const()[name = string("input_1033_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1033_strides_0 = const()[name = string("input_1033_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1033_pad_0 = const()[name = string("input_1033_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3345088)))];
            tensor<int32, [2]> input_1033_dilations_0 = const()[name = string("input_1033_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1033_groups_0 = const()[name = string("input_1033_groups_0"), val = int32(1)];
            tensor<fp16, [512, 256, 1, 1]> const_435_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3345216))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3476352))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3477440)))];
            tensor<fp16, [512]> const_436_to_fp16 = const()[name = string("const_436_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3478016)))];
            tensor<fp16, [1, 512, 32, 32]> input_1035_cast_fp16 = conv(bias = const_436_to_fp16, dilations = input_1033_dilations_0, groups = input_1033_groups_0, pad = input_1033_pad_0, pad_type = input_1033_pad_type_0, strides = input_1033_strides_0, weight = const_435_to_fp16, x = input_1031_cast_fp16)[name = string("input_1035_cast_fp16")];
            tensor<fp16, [1, 512, 32, 32]> input_1037_cast_fp16 = relu(x = input_1035_cast_fp16)[name = string("input_1037_cast_fp16")];
            string input_1039_pad_type_0 = const()[name = string("input_1039_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1039_pad_0 = const()[name = string("input_1039_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3479104)))];
            tensor<int32, [2]> input_1039_strides_0 = const()[name = string("input_1039_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_1039_groups_0 = const()[name = string("input_1039_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_1039_dilations_0 = const()[name = string("input_1039_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [512, 1, 5, 5]> const_437_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3479232))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3492096))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3493184)))];
            tensor<fp16, [512]> const_438_to_fp16 = const()[name = string("const_438_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3493760)))];
            tensor<fp16, [1, 512, 16, 16]> input_1041_cast_fp16 = conv(bias = const_438_to_fp16, dilations = input_1039_dilations_0, groups = input_1039_groups_0, pad = input_1039_pad_0, pad_type = input_1039_pad_type_0, strides = input_1039_strides_0, weight = const_437_to_fp16, x = input_1037_cast_fp16)[name = string("input_1041_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_1043_cast_fp16 = relu(x = input_1041_cast_fp16)[name = string("input_1043_cast_fp16")];
            string input_1045_pad_type_0 = const()[name = string("input_1045_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1045_strides_0 = const()[name = string("input_1045_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1045_pad_0 = const()[name = string("input_1045_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3494848)))];
            tensor<int32, [2]> input_1045_dilations_0 = const()[name = string("input_1045_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1045_groups_0 = const()[name = string("input_1045_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_439_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3494976))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3757184))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3758272)))];
            tensor<fp16, [512]> const_440_to_fp16 = const()[name = string("const_440_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3758848)))];
            tensor<fp16, [1, 512, 16, 16]> x_47_cast_fp16 = conv(bias = const_440_to_fp16, dilations = input_1045_dilations_0, groups = input_1045_groups_0, pad = input_1045_pad_0, pad_type = input_1045_pad_type_0, strides = input_1045_strides_0, weight = const_439_to_fp16, x = input_1043_cast_fp16)[name = string("x_47_cast_fp16")];
            tensor<int32, [4]> var_7403_begin_0 = const()[name = string("op_7403_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3759936)))];
            tensor<int32, [4]> var_7403_end_0 = const()[name = string("op_7403_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3760064)))];
            tensor<bool, [4]> var_7403_end_mask_0 = const()[name = string("op_7403_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_7403_cast_fp16 = slice_by_index(begin = var_7403_begin_0, end = var_7403_end_0, end_mask = var_7403_end_mask_0, x = x_47_cast_fp16)[name = string("op_7403_cast_fp16")];
            tensor<int32, [4]> var_7407_begin_0 = const()[name = string("op_7407_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3760192)))];
            tensor<int32, [4]> var_7407_end_0 = const()[name = string("op_7407_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3760320)))];
            tensor<bool, [4]> var_7407_end_mask_0 = const()[name = string("op_7407_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_7407_cast_fp16 = slice_by_index(begin = var_7407_begin_0, end = var_7407_end_0, end_mask = var_7407_end_mask_0, x = x_47_cast_fp16)[name = string("op_7407_cast_fp16")];
            tensor<int32, [4]> var_7411_begin_0 = const()[name = string("op_7411_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3760448)))];
            tensor<int32, [4]> var_7411_end_0 = const()[name = string("op_7411_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3760576)))];
            tensor<bool, [4]> var_7411_end_mask_0 = const()[name = string("op_7411_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_7411_cast_fp16 = slice_by_index(begin = var_7411_begin_0, end = var_7411_end_0, end_mask = var_7411_end_mask_0, x = x_47_cast_fp16)[name = string("op_7411_cast_fp16")];
            tensor<int32, [4]> var_7415_begin_0 = const()[name = string("op_7415_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3760704)))];
            tensor<int32, [4]> var_7415_end_0 = const()[name = string("op_7415_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3760832)))];
            tensor<bool, [4]> var_7415_end_mask_0 = const()[name = string("op_7415_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_7415_cast_fp16 = slice_by_index(begin = var_7415_begin_0, end = var_7415_end_0, end_mask = var_7415_end_mask_0, x = x_47_cast_fp16)[name = string("op_7415_cast_fp16")];
            string input_1049_pad_type_0 = const()[name = string("input_1049_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1049_strides_0 = const()[name = string("input_1049_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1049_pad_0 = const()[name = string("input_1049_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3760960)))];
            tensor<int32, [2]> input_1049_dilations_0 = const()[name = string("input_1049_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1049_groups_0 = const()[name = string("input_1049_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_441_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3761088))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3777536))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3777856)))];
            tensor<fp16, [128]> const_442_to_fp16 = const()[name = string("const_442_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778048)))];
            tensor<fp16, [1, 128, 16, 16]> input_1051_cast_fp16 = conv(bias = const_442_to_fp16, dilations = input_1049_dilations_0, groups = input_1049_groups_0, pad = input_1049_pad_0, pad_type = input_1049_pad_type_0, strides = input_1049_strides_0, weight = const_441_to_fp16, x = var_7407_cast_fp16)[name = string("input_1051_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_1053_cast_fp16 = relu(x = input_1051_cast_fp16)[name = string("input_1053_cast_fp16")];
            string input_1055_pad_type_0 = const()[name = string("input_1055_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1055_pad_0 = const()[name = string("input_1055_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778368)))];
            int32 input_1055_groups_0 = const()[name = string("input_1055_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1055_strides_0 = const()[name = string("input_1055_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1055_dilations_0 = const()[name = string("input_1055_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_443_to_fp16 = const()[name = string("const_443_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778496)))];
            tensor<fp16, [128]> const_444_to_fp16 = const()[name = string("const_444_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3784960)))];
            tensor<fp16, [1, 128, 16, 16]> input_1057_cast_fp16 = conv(bias = const_444_to_fp16, dilations = input_1055_dilations_0, groups = input_1055_groups_0, pad = input_1055_pad_0, pad_type = input_1055_pad_type_0, strides = input_1055_strides_0, weight = const_443_to_fp16, x = input_1053_cast_fp16)[name = string("input_1057_cast_fp16")];
            string input_1059_pad_type_0 = const()[name = string("input_1059_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1059_strides_0 = const()[name = string("input_1059_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1059_pad_0 = const()[name = string("input_1059_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3785280)))];
            tensor<int32, [2]> input_1059_dilations_0 = const()[name = string("input_1059_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1059_groups_0 = const()[name = string("input_1059_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_445_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3785408))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3801856))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3802176)))];
            tensor<fp16, [128]> const_446_to_fp16 = const()[name = string("const_446_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3802368)))];
            tensor<fp16, [1, 128, 16, 16]> input_1061_cast_fp16 = conv(bias = const_446_to_fp16, dilations = input_1059_dilations_0, groups = input_1059_groups_0, pad = input_1059_pad_0, pad_type = input_1059_pad_type_0, strides = input_1059_strides_0, weight = const_445_to_fp16, x = input_1057_cast_fp16)[name = string("input_1061_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_33_cast_fp16 = relu(x = input_1061_cast_fp16)[name = string("out1_33_cast_fp16")];
            string input_1065_pad_type_0 = const()[name = string("input_1065_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1065_strides_0 = const()[name = string("input_1065_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1065_pad_0 = const()[name = string("input_1065_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3802688)))];
            tensor<int32, [2]> input_1065_dilations_0 = const()[name = string("input_1065_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1065_groups_0 = const()[name = string("input_1065_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_447_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3802816))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3819264))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3819584)))];
            tensor<fp16, [128]> const_448_to_fp16 = const()[name = string("const_448_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3819776)))];
            tensor<fp16, [1, 128, 16, 16]> input_1067_cast_fp16 = conv(bias = const_448_to_fp16, dilations = input_1065_dilations_0, groups = input_1065_groups_0, pad = input_1065_pad_0, pad_type = input_1065_pad_type_0, strides = input_1065_strides_0, weight = const_447_to_fp16, x = var_7411_cast_fp16)[name = string("input_1067_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_1069_cast_fp16 = relu(x = input_1067_cast_fp16)[name = string("input_1069_cast_fp16")];
            string input_1071_pad_type_0 = const()[name = string("input_1071_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1071_pad_0 = const()[name = string("input_1071_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3820096)))];
            int32 input_1071_groups_0 = const()[name = string("input_1071_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1071_strides_0 = const()[name = string("input_1071_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1071_dilations_0 = const()[name = string("input_1071_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_449_to_fp16 = const()[name = string("const_449_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3820224)))];
            tensor<fp16, [128]> const_450_to_fp16 = const()[name = string("const_450_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3826688)))];
            tensor<fp16, [1, 128, 16, 16]> input_1073_cast_fp16 = conv(bias = const_450_to_fp16, dilations = input_1071_dilations_0, groups = input_1071_groups_0, pad = input_1071_pad_0, pad_type = input_1071_pad_type_0, strides = input_1071_strides_0, weight = const_449_to_fp16, x = input_1069_cast_fp16)[name = string("input_1073_cast_fp16")];
            string input_1075_pad_type_0 = const()[name = string("input_1075_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1075_strides_0 = const()[name = string("input_1075_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1075_pad_0 = const()[name = string("input_1075_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3827008)))];
            tensor<int32, [2]> input_1075_dilations_0 = const()[name = string("input_1075_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1075_groups_0 = const()[name = string("input_1075_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_451_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3827136))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3843584))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3843904)))];
            tensor<fp16, [128]> const_452_to_fp16 = const()[name = string("const_452_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3844096)))];
            tensor<fp16, [1, 128, 16, 16]> input_1077_cast_fp16 = conv(bias = const_452_to_fp16, dilations = input_1075_dilations_0, groups = input_1075_groups_0, pad = input_1075_pad_0, pad_type = input_1075_pad_type_0, strides = input_1075_strides_0, weight = const_451_to_fp16, x = input_1073_cast_fp16)[name = string("input_1077_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_33_cast_fp16 = relu(x = input_1077_cast_fp16)[name = string("out2_33_cast_fp16")];
            string input_1081_pad_type_0 = const()[name = string("input_1081_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1081_strides_0 = const()[name = string("input_1081_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1081_pad_0 = const()[name = string("input_1081_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3844416)))];
            tensor<int32, [2]> input_1081_dilations_0 = const()[name = string("input_1081_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1081_groups_0 = const()[name = string("input_1081_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_453_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3844544))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3860992))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3861312)))];
            tensor<fp16, [128]> const_454_to_fp16 = const()[name = string("const_454_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3861504)))];
            tensor<fp16, [1, 128, 16, 16]> input_1083_cast_fp16 = conv(bias = const_454_to_fp16, dilations = input_1081_dilations_0, groups = input_1081_groups_0, pad = input_1081_pad_0, pad_type = input_1081_pad_type_0, strides = input_1081_strides_0, weight = const_453_to_fp16, x = var_7415_cast_fp16)[name = string("input_1083_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_1085_cast_fp16 = relu(x = input_1083_cast_fp16)[name = string("input_1085_cast_fp16")];
            string input_1087_pad_type_0 = const()[name = string("input_1087_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1087_pad_0 = const()[name = string("input_1087_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3861824)))];
            int32 input_1087_groups_0 = const()[name = string("input_1087_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1087_strides_0 = const()[name = string("input_1087_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1087_dilations_0 = const()[name = string("input_1087_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_455_to_fp16 = const()[name = string("const_455_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3861952)))];
            tensor<fp16, [128]> const_456_to_fp16 = const()[name = string("const_456_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3868416)))];
            tensor<fp16, [1, 128, 16, 16]> input_1089_cast_fp16 = conv(bias = const_456_to_fp16, dilations = input_1087_dilations_0, groups = input_1087_groups_0, pad = input_1087_pad_0, pad_type = input_1087_pad_type_0, strides = input_1087_strides_0, weight = const_455_to_fp16, x = input_1085_cast_fp16)[name = string("input_1089_cast_fp16")];
            string input_1091_pad_type_0 = const()[name = string("input_1091_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1091_strides_0 = const()[name = string("input_1091_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1091_pad_0 = const()[name = string("input_1091_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3868736)))];
            tensor<int32, [2]> input_1091_dilations_0 = const()[name = string("input_1091_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1091_groups_0 = const()[name = string("input_1091_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_457_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3868864))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3885312))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3885632)))];
            tensor<fp16, [128]> const_458_to_fp16 = const()[name = string("const_458_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3885824)))];
            tensor<fp16, [1, 128, 16, 16]> input_1093_cast_fp16 = conv(bias = const_458_to_fp16, dilations = input_1091_dilations_0, groups = input_1091_groups_0, pad = input_1091_pad_0, pad_type = input_1091_pad_type_0, strides = input_1091_strides_0, weight = const_457_to_fp16, x = input_1089_cast_fp16)[name = string("input_1093_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_33_cast_fp16 = relu(x = input_1093_cast_fp16)[name = string("out3_33_cast_fp16")];
            bool input_1095_interleave_0 = const()[name = string("input_1095_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_1095_cast_fp16 = concat(axis = var_3877, interleave = input_1095_interleave_0, values = (var_7403_cast_fp16, out1_33_cast_fp16, out2_33_cast_fp16, out3_33_cast_fp16))[name = string("input_1095_cast_fp16")];
            string input_1097_pad_type_0 = const()[name = string("input_1097_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1097_strides_0 = const()[name = string("input_1097_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1097_pad_0 = const()[name = string("input_1097_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3886144)))];
            tensor<int32, [2]> input_1097_dilations_0 = const()[name = string("input_1097_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1097_groups_0 = const()[name = string("input_1097_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_459_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3886272))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4148480))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4149568)))];
            tensor<fp16, [512]> const_460_to_fp16 = const()[name = string("const_460_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4150144)))];
            tensor<fp16, [1, 512, 16, 16]> input_1099_cast_fp16 = conv(bias = const_460_to_fp16, dilations = input_1097_dilations_0, groups = input_1097_groups_0, pad = input_1097_pad_0, pad_type = input_1097_pad_type_0, strides = input_1097_strides_0, weight = const_459_to_fp16, x = input_1095_cast_fp16)[name = string("input_1099_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_1101_cast_fp16 = relu(x = input_1099_cast_fp16)[name = string("input_1101_cast_fp16")];
            string input_1103_pad_type_0 = const()[name = string("input_1103_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1103_pad_0 = const()[name = string("input_1103_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4151232)))];
            int32 input_1103_groups_0 = const()[name = string("input_1103_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_1103_strides_0 = const()[name = string("input_1103_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1103_dilations_0 = const()[name = string("input_1103_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [512, 1, 5, 5]> const_461_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4151360))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4164224))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4165312)))];
            tensor<fp16, [512]> const_462_to_fp16 = const()[name = string("const_462_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4165888)))];
            tensor<fp16, [1, 512, 16, 16]> input_1105_cast_fp16 = conv(bias = const_462_to_fp16, dilations = input_1103_dilations_0, groups = input_1103_groups_0, pad = input_1103_pad_0, pad_type = input_1103_pad_type_0, strides = input_1103_strides_0, weight = const_461_to_fp16, x = input_1101_cast_fp16)[name = string("input_1105_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_1107_cast_fp16 = relu(x = input_1105_cast_fp16)[name = string("input_1107_cast_fp16")];
            string input_1109_pad_type_0 = const()[name = string("input_1109_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1109_strides_0 = const()[name = string("input_1109_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1109_pad_0 = const()[name = string("input_1109_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4166976)))];
            tensor<int32, [2]> input_1109_dilations_0 = const()[name = string("input_1109_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1109_groups_0 = const()[name = string("input_1109_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_463_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4167104))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4429312))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430400)))];
            tensor<fp16, [512]> const_464_to_fp16 = const()[name = string("const_464_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430976)))];
            tensor<fp16, [1, 512, 16, 16]> y_23_cast_fp16 = conv(bias = const_464_to_fp16, dilations = input_1109_dilations_0, groups = input_1109_groups_0, pad = input_1109_pad_0, pad_type = input_1109_pad_type_0, strides = input_1109_strides_0, weight = const_463_to_fp16, x = input_1107_cast_fp16)[name = string("y_23_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> x_49_cast_fp16 = add(x = input_1095_cast_fp16, y = y_23_cast_fp16)[name = string("x_49_cast_fp16")];
            tensor<int32, [4]> var_7515_begin_0 = const()[name = string("op_7515_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4432064)))];
            tensor<int32, [4]> var_7515_end_0 = const()[name = string("op_7515_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4432192)))];
            tensor<bool, [4]> var_7515_end_mask_0 = const()[name = string("op_7515_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_7515_cast_fp16 = slice_by_index(begin = var_7515_begin_0, end = var_7515_end_0, end_mask = var_7515_end_mask_0, x = x_49_cast_fp16)[name = string("op_7515_cast_fp16")];
            tensor<int32, [4]> var_7519_begin_0 = const()[name = string("op_7519_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4432320)))];
            tensor<int32, [4]> var_7519_end_0 = const()[name = string("op_7519_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4432448)))];
            tensor<bool, [4]> var_7519_end_mask_0 = const()[name = string("op_7519_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_7519_cast_fp16 = slice_by_index(begin = var_7519_begin_0, end = var_7519_end_0, end_mask = var_7519_end_mask_0, x = x_49_cast_fp16)[name = string("op_7519_cast_fp16")];
            tensor<int32, [4]> var_7523_begin_0 = const()[name = string("op_7523_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4432576)))];
            tensor<int32, [4]> var_7523_end_0 = const()[name = string("op_7523_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4432704)))];
            tensor<bool, [4]> var_7523_end_mask_0 = const()[name = string("op_7523_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_7523_cast_fp16 = slice_by_index(begin = var_7523_begin_0, end = var_7523_end_0, end_mask = var_7523_end_mask_0, x = x_49_cast_fp16)[name = string("op_7523_cast_fp16")];
            tensor<int32, [4]> var_7527_begin_0 = const()[name = string("op_7527_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4432832)))];
            tensor<int32, [4]> var_7527_end_0 = const()[name = string("op_7527_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4432960)))];
            tensor<bool, [4]> var_7527_end_mask_0 = const()[name = string("op_7527_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_7527_cast_fp16 = slice_by_index(begin = var_7527_begin_0, end = var_7527_end_0, end_mask = var_7527_end_mask_0, x = x_49_cast_fp16)[name = string("op_7527_cast_fp16")];
            string input_1113_pad_type_0 = const()[name = string("input_1113_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1113_strides_0 = const()[name = string("input_1113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1113_pad_0 = const()[name = string("input_1113_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4433088)))];
            tensor<int32, [2]> input_1113_dilations_0 = const()[name = string("input_1113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1113_groups_0 = const()[name = string("input_1113_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_465_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4433216))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4449664))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4449984)))];
            tensor<fp16, [128]> const_466_to_fp16 = const()[name = string("const_466_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4450176)))];
            tensor<fp16, [1, 128, 16, 16]> input_1115_cast_fp16 = conv(bias = const_466_to_fp16, dilations = input_1113_dilations_0, groups = input_1113_groups_0, pad = input_1113_pad_0, pad_type = input_1113_pad_type_0, strides = input_1113_strides_0, weight = const_465_to_fp16, x = var_7519_cast_fp16)[name = string("input_1115_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_1117_cast_fp16 = relu(x = input_1115_cast_fp16)[name = string("input_1117_cast_fp16")];
            string input_1119_pad_type_0 = const()[name = string("input_1119_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1119_pad_0 = const()[name = string("input_1119_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4450496)))];
            int32 input_1119_groups_0 = const()[name = string("input_1119_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1119_strides_0 = const()[name = string("input_1119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1119_dilations_0 = const()[name = string("input_1119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_467_to_fp16 = const()[name = string("const_467_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4450624)))];
            tensor<fp16, [128]> const_468_to_fp16 = const()[name = string("const_468_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4457088)))];
            tensor<fp16, [1, 128, 16, 16]> input_1121_cast_fp16 = conv(bias = const_468_to_fp16, dilations = input_1119_dilations_0, groups = input_1119_groups_0, pad = input_1119_pad_0, pad_type = input_1119_pad_type_0, strides = input_1119_strides_0, weight = const_467_to_fp16, x = input_1117_cast_fp16)[name = string("input_1121_cast_fp16")];
            string input_1123_pad_type_0 = const()[name = string("input_1123_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1123_strides_0 = const()[name = string("input_1123_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1123_pad_0 = const()[name = string("input_1123_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4457408)))];
            tensor<int32, [2]> input_1123_dilations_0 = const()[name = string("input_1123_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1123_groups_0 = const()[name = string("input_1123_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_469_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4457536))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4473984))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4474304)))];
            tensor<fp16, [128]> const_470_to_fp16 = const()[name = string("const_470_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4474496)))];
            tensor<fp16, [1, 128, 16, 16]> input_1125_cast_fp16 = conv(bias = const_470_to_fp16, dilations = input_1123_dilations_0, groups = input_1123_groups_0, pad = input_1123_pad_0, pad_type = input_1123_pad_type_0, strides = input_1123_strides_0, weight = const_469_to_fp16, x = input_1121_cast_fp16)[name = string("input_1125_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_35_cast_fp16 = relu(x = input_1125_cast_fp16)[name = string("out1_35_cast_fp16")];
            string input_1129_pad_type_0 = const()[name = string("input_1129_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1129_strides_0 = const()[name = string("input_1129_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1129_pad_0 = const()[name = string("input_1129_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4474816)))];
            tensor<int32, [2]> input_1129_dilations_0 = const()[name = string("input_1129_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1129_groups_0 = const()[name = string("input_1129_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_471_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4474944))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4491392))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4491712)))];
            tensor<fp16, [128]> const_472_to_fp16 = const()[name = string("const_472_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4491904)))];
            tensor<fp16, [1, 128, 16, 16]> input_1131_cast_fp16 = conv(bias = const_472_to_fp16, dilations = input_1129_dilations_0, groups = input_1129_groups_0, pad = input_1129_pad_0, pad_type = input_1129_pad_type_0, strides = input_1129_strides_0, weight = const_471_to_fp16, x = var_7523_cast_fp16)[name = string("input_1131_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_1133_cast_fp16 = relu(x = input_1131_cast_fp16)[name = string("input_1133_cast_fp16")];
            string input_1135_pad_type_0 = const()[name = string("input_1135_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1135_pad_0 = const()[name = string("input_1135_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4492224)))];
            int32 input_1135_groups_0 = const()[name = string("input_1135_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1135_strides_0 = const()[name = string("input_1135_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1135_dilations_0 = const()[name = string("input_1135_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_473_to_fp16 = const()[name = string("const_473_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4492352)))];
            tensor<fp16, [128]> const_474_to_fp16 = const()[name = string("const_474_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4498816)))];
            tensor<fp16, [1, 128, 16, 16]> input_1137_cast_fp16 = conv(bias = const_474_to_fp16, dilations = input_1135_dilations_0, groups = input_1135_groups_0, pad = input_1135_pad_0, pad_type = input_1135_pad_type_0, strides = input_1135_strides_0, weight = const_473_to_fp16, x = input_1133_cast_fp16)[name = string("input_1137_cast_fp16")];
            string input_1139_pad_type_0 = const()[name = string("input_1139_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1139_strides_0 = const()[name = string("input_1139_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1139_pad_0 = const()[name = string("input_1139_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4499136)))];
            tensor<int32, [2]> input_1139_dilations_0 = const()[name = string("input_1139_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1139_groups_0 = const()[name = string("input_1139_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_475_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4499264))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4515712))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4516032)))];
            tensor<fp16, [128]> const_476_to_fp16 = const()[name = string("const_476_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4516224)))];
            tensor<fp16, [1, 128, 16, 16]> input_1141_cast_fp16 = conv(bias = const_476_to_fp16, dilations = input_1139_dilations_0, groups = input_1139_groups_0, pad = input_1139_pad_0, pad_type = input_1139_pad_type_0, strides = input_1139_strides_0, weight = const_475_to_fp16, x = input_1137_cast_fp16)[name = string("input_1141_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_35_cast_fp16 = relu(x = input_1141_cast_fp16)[name = string("out2_35_cast_fp16")];
            string input_1145_pad_type_0 = const()[name = string("input_1145_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1145_strides_0 = const()[name = string("input_1145_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1145_pad_0 = const()[name = string("input_1145_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4516544)))];
            tensor<int32, [2]> input_1145_dilations_0 = const()[name = string("input_1145_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1145_groups_0 = const()[name = string("input_1145_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_477_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4516672))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4533120))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4533440)))];
            tensor<fp16, [128]> const_478_to_fp16 = const()[name = string("const_478_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4533632)))];
            tensor<fp16, [1, 128, 16, 16]> input_1147_cast_fp16 = conv(bias = const_478_to_fp16, dilations = input_1145_dilations_0, groups = input_1145_groups_0, pad = input_1145_pad_0, pad_type = input_1145_pad_type_0, strides = input_1145_strides_0, weight = const_477_to_fp16, x = var_7527_cast_fp16)[name = string("input_1147_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_1149_cast_fp16 = relu(x = input_1147_cast_fp16)[name = string("input_1149_cast_fp16")];
            string input_1151_pad_type_0 = const()[name = string("input_1151_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1151_pad_0 = const()[name = string("input_1151_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4533952)))];
            int32 input_1151_groups_0 = const()[name = string("input_1151_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1151_strides_0 = const()[name = string("input_1151_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1151_dilations_0 = const()[name = string("input_1151_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_479_to_fp16 = const()[name = string("const_479_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4534080)))];
            tensor<fp16, [128]> const_480_to_fp16 = const()[name = string("const_480_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4540544)))];
            tensor<fp16, [1, 128, 16, 16]> input_1153_cast_fp16 = conv(bias = const_480_to_fp16, dilations = input_1151_dilations_0, groups = input_1151_groups_0, pad = input_1151_pad_0, pad_type = input_1151_pad_type_0, strides = input_1151_strides_0, weight = const_479_to_fp16, x = input_1149_cast_fp16)[name = string("input_1153_cast_fp16")];
            string input_1155_pad_type_0 = const()[name = string("input_1155_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1155_strides_0 = const()[name = string("input_1155_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1155_pad_0 = const()[name = string("input_1155_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4540864)))];
            tensor<int32, [2]> input_1155_dilations_0 = const()[name = string("input_1155_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1155_groups_0 = const()[name = string("input_1155_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_481_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4540992))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4557440))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4557760)))];
            tensor<fp16, [128]> const_482_to_fp16 = const()[name = string("const_482_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4557952)))];
            tensor<fp16, [1, 128, 16, 16]> input_1157_cast_fp16 = conv(bias = const_482_to_fp16, dilations = input_1155_dilations_0, groups = input_1155_groups_0, pad = input_1155_pad_0, pad_type = input_1155_pad_type_0, strides = input_1155_strides_0, weight = const_481_to_fp16, x = input_1153_cast_fp16)[name = string("input_1157_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_35_cast_fp16 = relu(x = input_1157_cast_fp16)[name = string("out3_35_cast_fp16")];
            bool input_1159_interleave_0 = const()[name = string("input_1159_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_1159_cast_fp16 = concat(axis = var_3877, interleave = input_1159_interleave_0, values = (var_7515_cast_fp16, out1_35_cast_fp16, out2_35_cast_fp16, out3_35_cast_fp16))[name = string("input_1159_cast_fp16")];
            string input_1161_pad_type_0 = const()[name = string("input_1161_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1161_strides_0 = const()[name = string("input_1161_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1161_pad_0 = const()[name = string("input_1161_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4558272)))];
            tensor<int32, [2]> input_1161_dilations_0 = const()[name = string("input_1161_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1161_groups_0 = const()[name = string("input_1161_groups_0"), val = int32(1)];
            tensor<fp16, [128, 512, 1, 1]> model_value_encoder_backbone_xfpn_p5_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4558400))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4624000))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4624320)))];
            tensor<fp16, [1, 128, 16, 16]> input_1161_cast_fp16 = conv(dilations = input_1161_dilations_0, groups = input_1161_groups_0, pad = input_1161_pad_0, pad_type = input_1161_pad_type_0, strides = input_1161_strides_0, weight = model_value_encoder_backbone_xfpn_p5_1x1_weight_to_fp16, x = input_1159_cast_fp16)[name = string("input_1161_cast_fp16")];
            fp32 y_25_scale_factor_height_0 = const()[name = string("y_25_scale_factor_height_0"), val = fp32(2)];
            fp32 y_25_scale_factor_width_0 = const()[name = string("y_25_scale_factor_width_0"), val = fp32(2)];
            tensor<fp16, [1, 128, 32, 32]> y_25_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = y_25_scale_factor_height_0, scale_factor_width = y_25_scale_factor_width_0, x = input_1161_cast_fp16)[name = string("y_25_cast_fp16")];
            string x_51_pad_type_0 = const()[name = string("x_51_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_51_strides_0 = const()[name = string("x_51_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_51_pad_0 = const()[name = string("x_51_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4624512)))];
            tensor<int32, [2]> x_51_dilations_0 = const()[name = string("x_51_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_51_groups_0 = const()[name = string("x_51_groups_0"), val = int32(1)];
            tensor<fp16, [128, 256, 1, 1]> model_value_encoder_backbone_xfpn_p4_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4624640))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4657472))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4657792)))];
            tensor<fp16, [1, 128, 32, 32]> x_51_cast_fp16 = conv(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 = model_value_encoder_backbone_xfpn_p4_1x1_weight_to_fp16, x = input_1031_cast_fp16)[name = string("x_51_cast_fp16")];
            tensor<fp16, [1, 128, 32, 32]> input_1163_cast_fp16 = add(x = x_51_cast_fp16, y = y_25_cast_fp16)[name = string("input_1163_cast_fp16")];
            string input_1263_pad_type_0 = const()[name = string("input_1263_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1263_pad_0 = const()[name = string("input_1263_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4657984)))];
            int32 input_1263_groups_0 = const()[name = string("input_1263_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1263_strides_0 = const()[name = string("input_1263_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1263_dilations_0 = const()[name = string("input_1263_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> model_value_encoder_backbone_xfpn_fpn_output4_weight_to_fp16 = const()[name = string("model_value_encoder_backbone_xfpn_fpn_output4_weight_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4658112)))];
            tensor<fp16, [1, 128, 32, 32]> input_1263_cast_fp16 = conv(dilations = input_1263_dilations_0, groups = input_1263_groups_0, pad = input_1263_pad_0, pad_type = input_1263_pad_type_0, strides = input_1263_strides_0, weight = model_value_encoder_backbone_xfpn_fpn_output4_weight_to_fp16, x = input_1163_cast_fp16)[name = string("input_1263_cast_fp16")];
            string input_1265_pad_type_0 = const()[name = string("input_1265_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1265_strides_0 = const()[name = string("input_1265_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1265_pad_0 = const()[name = string("input_1265_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4660480)))];
            tensor<int32, [2]> input_1265_dilations_0 = const()[name = string("input_1265_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1265_groups_0 = const()[name = string("input_1265_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> model_value_encoder_fuser_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4660608))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4677056))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4677376)))];
            tensor<fp16, [128]> model_value_encoder_fuser_bias_to_fp16 = const()[name = string("model_value_encoder_fuser_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4677568)))];
            tensor<fp16, [1, 128, 32, 32]> input_1265_cast_fp16 = conv(bias = model_value_encoder_fuser_bias_to_fp16, dilations = input_1265_dilations_0, groups = input_1265_groups_0, pad = input_1265_pad_0, pad_type = input_1265_pad_type_0, strides = input_1265_strides_0, weight = model_value_encoder_fuser_weight_to_fp16, x = input_1263_cast_fp16)[name = string("input_1265_cast_fp16")];
            string var_7651_pad_type_0 = const()[name = string("op_7651_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> var_7651_pad_0 = const()[name = string("op_7651_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4677888)))];
            tensor<int32, [2]> var_7651_strides_0 = const()[name = string("op_7651_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_7651_dilations_0 = const()[name = string("op_7651_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_7651_groups_0 = const()[name = string("op_7651_groups_0"), val = int32(1)];
            tensor<fp16, [192, 128, 3, 3]> model_value_encoder_hidden_reinforce_transform1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [192, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4678016))), scale = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4899264))), zero_point = tensor<int8, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4899712)))];
            tensor<fp16, [192]> model_value_encoder_hidden_reinforce_transform1_bias_to_fp16 = const()[name = string("model_value_encoder_hidden_reinforce_transform1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4899968)))];
            tensor<fp16, [1, 192, 32, 32]> var_7651_cast_fp16 = conv(bias = model_value_encoder_hidden_reinforce_transform1_bias_to_fp16, dilations = var_7651_dilations_0, groups = var_7651_groups_0, pad = var_7651_pad_0, pad_type = var_7651_pad_type_0, strides = var_7651_strides_0, weight = model_value_encoder_hidden_reinforce_transform1_weight_to_fp16, x = input_1265_cast_fp16)[name = string("op_7651_cast_fp16")];
            string var_7657_pad_type_0 = const()[name = string("op_7657_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> var_7657_pad_0 = const()[name = string("op_7657_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4900416)))];
            tensor<int32, [2]> var_7657_strides_0 = const()[name = string("op_7657_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_7657_dilations_0 = const()[name = string("op_7657_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_7657_groups_0 = const()[name = string("op_7657_groups_0"), val = int32(1)];
            tensor<fp16, [192, 64, 3, 3]> model_value_encoder_hidden_reinforce_transform2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [192, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4900544))), scale = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5011200))), zero_point = tensor<int8, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5011648)))];
            tensor<fp16, [1, 192, 32, 32]> var_7657_cast_fp16 = conv(dilations = var_7657_dilations_0, groups = var_7657_groups_0, pad = var_7657_pad_0, pad_type = var_7657_pad_type_0, strides = var_7657_strides_0, weight = model_value_encoder_hidden_reinforce_transform2_weight_to_fp16, x = hidden_state)[name = string("op_7657_cast_fp16")];
            tensor<fp16, [1, 192, 32, 32]> values_1_cast_fp16 = add(x = var_7651_cast_fp16, y = var_7657_cast_fp16)[name = string("values_1_cast_fp16")];
            tensor<int32, [4]> var_7660_begin_0 = const()[name = string("op_7660_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5011904)))];
            tensor<int32, [4]> var_7660_end_0 = const()[name = string("op_7660_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5012032)))];
            tensor<bool, [4]> var_7660_end_mask_0 = const()[name = string("op_7660_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7660_cast_fp16 = slice_by_index(begin = var_7660_begin_0, end = var_7660_end_0, end_mask = var_7660_end_mask_0, x = values_1_cast_fp16)[name = string("op_7660_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> forget_gate_1_cast_fp16 = sigmoid(x = var_7660_cast_fp16)[name = string("forget_gate_1_cast_fp16")];
            tensor<int32, [4]> var_7663_begin_0 = const()[name = string("op_7663_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5012160)))];
            tensor<int32, [4]> var_7663_end_0 = const()[name = string("op_7663_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5012288)))];
            tensor<bool, [4]> var_7663_end_mask_0 = const()[name = string("op_7663_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7663_cast_fp16 = slice_by_index(begin = var_7663_begin_0, end = var_7663_end_0, end_mask = var_7663_end_mask_0, x = values_1_cast_fp16)[name = string("op_7663_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> update_gate_1_cast_fp16 = sigmoid(x = var_7663_cast_fp16)[name = string("update_gate_1_cast_fp16")];
            tensor<int32, [4]> var_7666_begin_0 = const()[name = string("op_7666_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5012416)))];
            tensor<int32, [4]> var_7666_end_0 = const()[name = string("op_7666_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5012544)))];
            tensor<bool, [4]> var_7666_end_mask_0 = const()[name = string("op_7666_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_7666_cast_fp16 = slice_by_index(begin = var_7666_begin_0, end = var_7666_end_0, end_mask = var_7666_end_mask_0, x = values_1_cast_fp16)[name = string("op_7666_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> new_value_1_cast_fp16 = tanh(x = var_7666_cast_fp16)[name = string("new_value_1_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> var_7668_cast_fp16 = mul(x = forget_gate_1_cast_fp16, y = hidden_state)[name = string("op_7668_cast_fp16")];
            fp16 var_3877_promoted_to_fp16 = const()[name = string("op_3877_promoted_to_fp16"), val = fp16(1)];
            tensor<fp16, [1, 64, 32, 32]> var_7669_cast_fp16 = sub(x = var_3877_promoted_to_fp16, y = update_gate_1_cast_fp16)[name = string("op_7669_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> var_7670_cast_fp16 = mul(x = var_7668_cast_fp16, y = var_7669_cast_fp16)[name = string("op_7670_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> var_7671_cast_fp16 = mul(x = update_gate_1_cast_fp16, y = new_value_1_cast_fp16)[name = string("op_7671_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> init_h = add(x = var_7670_cast_fp16, y = var_7671_cast_fp16)[name = string("op_7672_cast_fp16")];
            int32 var_7677 = const()[name = string("op_7677"), val = int32(2)];
            bool k_cat_interleave_0 = const()[name = string("k_cat_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 64, 64, 32]> k_cat_cast_fp16 = concat(axis = var_7677, interleave = k_cat_interleave_0, values = (key_k_cast_fp16, key_k_cast_fp16))[name = string("k_cat_cast_fp16")];
            int32 var_7680 = const()[name = string("op_7680"), val = int32(2)];
            bool v_cat_interleave_0 = const()[name = string("v_cat_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 64, 32]> v_cat_cast_fp16 = concat(axis = var_7680, interleave = v_cat_interleave_0, values = (input_1265_cast_fp16, input_1265_cast_fp16))[name = string("v_cat_cast_fp16")];
            tensor<int32, [4]> var_7696 = const()[name = string("op_7696"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5012672)))];
            tensor<fp16, [1, 64, 1, 2048]> var_7697_cast_fp16 = reshape(shape = var_7696, x = k_cat_cast_fp16)[name = string("op_7697_cast_fp16")];
            tensor<int32, [4]> var_7700_perm_0 = const()[name = string("op_7700_perm_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5012800)))];
            tensor<int32, [4]> var_7715 = const()[name = string("op_7715"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5012928)))];
            tensor<fp16, [1, 128, 1, 2048]> init_v = reshape(shape = var_7715, x = v_cat_cast_fp16)[name = string("op_7716_cast_fp16")];
            tensor<fp16, [1, 2048, 1, 64]> init_k = transpose(perm = var_7700_perm_0, x = var_7697_cast_fp16)[name = string("transpose_3")];
        } -> (init_h, init_k, init_v);
    func regularFrame<ios18>(tensor<fp16, [1, 64, 32, 32]> hidden_state, pixel_buffer<FMT_32BGRA, shape=[512, 512]> input_image, tensor<fp16, [1, 1, 512, 512]> mask, tensor<fp16, [1, 2048, 1, 64]> prev_key, tensor<fp16, [1, 128, 1, 2048]> prev_value) [E5_FlagsEir = dict<string, string>({{"allowSoftmaxApproximation", "1"}, {"early_arch_extended_reshape", "1"}, {"experimental.ane.early_arch_transposes", "1"}, {"experimental.ane.enable_rsqrt", "1"}, {"experimental.ane.reduce_mean_spatial", "1"}, {"experimental.aot.enable_surface_desc", "1"}})] {
            tensor<fp16, [1, 3, 1, 1]> var_47_to_fp16 = const()[name = string("op_47_to_fp16"), val = tensor<fp16, [1, 3, 1, 1]>([[[[123.6875]], [[116.25]], [[103.5]]]])];
            tensor<uint8, [4, 512, 512]> images_tensor_bgra_uint8 = pixel_buffer_to_tensor(input = input_image);
            tensor<fp16, [4, 512, 512]> images_tensor_bgra_fp16 = cast(dtype = string("fp16"), x = images_tensor_bgra_uint8);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_b = slice_by_index(begin = tensor<int32, [3]>([0, 0, 0]), end = tensor<int32, [3]>([1, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_g = slice_by_index(begin = tensor<int32, [3]>([1, 0, 0]), end = tensor<int32, [3]>([2, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_r = slice_by_index(begin = tensor<int32, [3]>([2, 0, 0]), end = tensor<int32, [3]>([3, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [3, 512, 512]> images_tensor_rgb_fp16 = concat(axis = int32(0), interleave = bool(false), values = (images_tensor_slice_r, images_tensor_slice_g, images_tensor_slice_b));
            tensor<fp16, [1, 3, 512, 512]> images_tensor_tensor = expand_dims(axes = tensor<int32, [1]>([0]), x = images_tensor_rgb_fp16);
            tensor<fp16, [1, 3, 512, 512]> tensor_5_cast_fp16 = sub(x = images_tensor_tensor, y = var_47_to_fp16)[name = string("tensor_5_cast_fp16")];
            tensor<fp16, [1, 3, 1, 1]> _inversed_input_1_y_0_to_fp16 = const()[name = string("_inversed_input_1_y_0_to_fp16"), val = tensor<fp16, [1, 3, 1, 1]>([[[[0.0171203613]], [[0.0175018311]], [[0.0174255371]]]])];
            tensor<fp16, [1, 3, 512, 512]> _inversed_input_1_cast_fp16 = mul(x = tensor_5_cast_fp16, y = _inversed_input_1_y_0_to_fp16)[name = string("_inversed_input_1_cast_fp16")];
            int32 var_86 = const()[name = string("op_86"), val = int32(1)];
            tensor<int32, [8]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [8]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("constant")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0)];
            tensor<fp16, [1, 3, 513, 513]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = _inversed_input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<int32, [2]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [24, 3, 3, 3]> const_95_to_fp16 = const()[name = string("const_95_to_fp16"), val = tensor<fp16, [24, 3, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [24]> const_96_to_fp16 = const()[name = string("const_96_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1728)))];
            tensor<fp16, [1, 24, 256, 256]> input_7_cast_fp16 = conv(bias = const_96_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = const_95_to_fp16, x = input_3_cast_fp16)[name = string("input_7_cast_fp16")];
            tensor<fp16, [1, 24, 256, 256]> input_9_cast_fp16 = relu(x = input_7_cast_fp16)[name = string("input_9_cast_fp16")];
            tensor<int32, [2]> var_2890 = const()[name = string("op_2890"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_2891 = const()[name = string("op_2891"), val = tensor<int32, [2]>([2, 2])];
            string input_11_pad_type_0 = const()[name = string("input_11_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_11_pad_0 = const()[name = string("input_11_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1856)))];
            bool input_11_ceil_mode_0 = const()[name = string("input_11_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 24, 128, 128]> input_11_cast_fp16 = max_pool(ceil_mode = input_11_ceil_mode_0, kernel_sizes = var_2890, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = var_2891, x = input_9_cast_fp16)[name = string("input_11_cast_fp16")];
            string input_17_pad_type_0 = const()[name = string("input_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_17_strides_0 = const()[name = string("input_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1984)))];
            tensor<int32, [2]> input_17_dilations_0 = const()[name = string("input_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_17_groups_0 = const()[name = string("input_17_groups_0"), val = int32(1)];
            tensor<fp16, [144, 24, 1, 1]> const_97_to_fp16 = const()[name = string("const_97_to_fp16"), val = tensor<fp16, [144, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2112)))];
            tensor<fp16, [144]> const_98_to_fp16 = const()[name = string("const_98_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9088)))];
            tensor<fp16, [1, 144, 128, 128]> input_19_cast_fp16 = conv(bias = const_98_to_fp16, dilations = input_17_dilations_0, groups = input_17_groups_0, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = input_17_strides_0, weight = const_97_to_fp16, x = input_11_cast_fp16)[name = string("input_19_cast_fp16")];
            tensor<fp16, [1, 144, 128, 128]> input_21_cast_fp16 = relu(x = input_19_cast_fp16)[name = string("input_21_cast_fp16")];
            string input_23_pad_type_0 = const()[name = string("input_23_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9472)))];
            tensor<int32, [2]> input_23_strides_0 = const()[name = string("input_23_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_23_groups_0 = const()[name = string("input_23_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_23_dilations_0 = const()[name = string("input_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [144, 1, 5, 5]> const_99_to_fp16 = const()[name = string("const_99_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9600)))];
            tensor<fp16, [144]> const_100_to_fp16 = const()[name = string("const_100_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16896)))];
            tensor<fp16, [1, 144, 64, 64]> input_25_cast_fp16 = conv(bias = const_100_to_fp16, dilations = input_23_dilations_0, groups = input_23_groups_0, pad = input_23_pad_0, pad_type = input_23_pad_type_0, strides = input_23_strides_0, weight = const_99_to_fp16, x = input_21_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_27_cast_fp16 = relu(x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_29_pad_type_0 = const()[name = string("input_29_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_29_strides_0 = const()[name = string("input_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_29_pad_0 = const()[name = string("input_29_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17280)))];
            tensor<int32, [2]> input_29_dilations_0 = const()[name = string("input_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_29_groups_0 = const()[name = string("input_29_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_101_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17408))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38208))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38592)))];
            tensor<fp16, [144]> const_102_to_fp16 = const()[name = string("const_102_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38848)))];
            tensor<fp16, [1, 144, 64, 64]> x_1_cast_fp16 = conv(bias = const_102_to_fp16, dilations = input_29_dilations_0, groups = input_29_groups_0, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = input_29_strides_0, weight = const_101_to_fp16, x = input_27_cast_fp16)[name = string("x_1_cast_fp16")];
            tensor<int32, [4]> var_2929_begin_0 = const()[name = string("op_2929_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39232)))];
            tensor<int32, [4]> var_2929_end_0 = const()[name = string("op_2929_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39360)))];
            tensor<bool, [4]> var_2929_end_mask_0 = const()[name = string("op_2929_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2929_cast_fp16 = slice_by_index(begin = var_2929_begin_0, end = var_2929_end_0, end_mask = var_2929_end_mask_0, x = x_1_cast_fp16)[name = string("op_2929_cast_fp16")];
            tensor<int32, [4]> var_2933_begin_0 = const()[name = string("op_2933_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39488)))];
            tensor<int32, [4]> var_2933_end_0 = const()[name = string("op_2933_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39616)))];
            tensor<bool, [4]> var_2933_end_mask_0 = const()[name = string("op_2933_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2933_cast_fp16 = slice_by_index(begin = var_2933_begin_0, end = var_2933_end_0, end_mask = var_2933_end_mask_0, x = x_1_cast_fp16)[name = string("op_2933_cast_fp16")];
            tensor<int32, [4]> var_2937_begin_0 = const()[name = string("op_2937_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39744)))];
            tensor<int32, [4]> var_2937_end_0 = const()[name = string("op_2937_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39872)))];
            tensor<bool, [4]> var_2937_end_mask_0 = const()[name = string("op_2937_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2937_cast_fp16 = slice_by_index(begin = var_2937_begin_0, end = var_2937_end_0, end_mask = var_2937_end_mask_0, x = x_1_cast_fp16)[name = string("op_2937_cast_fp16")];
            tensor<int32, [4]> var_2941_begin_0 = const()[name = string("op_2941_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40000)))];
            tensor<int32, [4]> var_2941_end_0 = const()[name = string("op_2941_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40128)))];
            tensor<bool, [4]> var_2941_end_mask_0 = const()[name = string("op_2941_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2941_cast_fp16 = slice_by_index(begin = var_2941_begin_0, end = var_2941_end_0, end_mask = var_2941_end_mask_0, x = x_1_cast_fp16)[name = string("op_2941_cast_fp16")];
            string input_33_pad_type_0 = const()[name = string("input_33_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_33_strides_0 = const()[name = string("input_33_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40256)))];
            tensor<int32, [2]> input_33_dilations_0 = const()[name = string("input_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_33_groups_0 = const()[name = string("input_33_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_103_to_fp16 = const()[name = string("const_103_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40384)))];
            tensor<fp16, [36]> const_104_to_fp16 = const()[name = string("const_104_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43072)))];
            tensor<fp16, [1, 36, 64, 64]> input_35_cast_fp16 = conv(bias = const_104_to_fp16, dilations = input_33_dilations_0, groups = input_33_groups_0, pad = input_33_pad_0, pad_type = input_33_pad_type_0, strides = input_33_strides_0, weight = const_103_to_fp16, x = var_2933_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_37_cast_fp16 = relu(x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_39_pad_type_0 = const()[name = string("input_39_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_39_pad_0 = const()[name = string("input_39_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43264)))];
            int32 input_39_groups_0 = const()[name = string("input_39_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_39_strides_0 = const()[name = string("input_39_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_39_dilations_0 = const()[name = string("input_39_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_105_to_fp16 = const()[name = string("const_105_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43392)))];
            tensor<fp16, [36]> const_106_to_fp16 = const()[name = string("const_106_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45312)))];
            tensor<fp16, [1, 36, 64, 64]> input_41_cast_fp16 = conv(bias = const_106_to_fp16, dilations = input_39_dilations_0, groups = input_39_groups_0, pad = input_39_pad_0, pad_type = input_39_pad_type_0, strides = input_39_strides_0, weight = const_105_to_fp16, x = input_37_cast_fp16)[name = string("input_41_cast_fp16")];
            string input_43_pad_type_0 = const()[name = string("input_43_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_43_strides_0 = const()[name = string("input_43_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45504)))];
            tensor<int32, [2]> input_43_dilations_0 = const()[name = string("input_43_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_43_groups_0 = const()[name = string("input_43_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45632)))];
            tensor<fp16, [36]> const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48320)))];
            tensor<fp16, [1, 36, 64, 64]> input_45_cast_fp16 = conv(bias = const_108_to_fp16, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_107_to_fp16, x = input_41_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_1_cast_fp16 = relu(x = input_45_cast_fp16)[name = string("out1_1_cast_fp16")];
            string input_49_pad_type_0 = const()[name = string("input_49_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_49_strides_0 = const()[name = string("input_49_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_49_pad_0 = const()[name = string("input_49_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48512)))];
            tensor<int32, [2]> input_49_dilations_0 = const()[name = string("input_49_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_49_groups_0 = const()[name = string("input_49_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_109_to_fp16 = const()[name = string("const_109_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48640)))];
            tensor<fp16, [36]> const_110_to_fp16 = const()[name = string("const_110_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51328)))];
            tensor<fp16, [1, 36, 64, 64]> input_51_cast_fp16 = conv(bias = const_110_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_109_to_fp16, x = var_2937_cast_fp16)[name = string("input_51_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_53_cast_fp16 = relu(x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string input_55_pad_type_0 = const()[name = string("input_55_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_55_pad_0 = const()[name = string("input_55_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51520)))];
            int32 input_55_groups_0 = const()[name = string("input_55_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_55_strides_0 = const()[name = string("input_55_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_55_dilations_0 = const()[name = string("input_55_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_111_to_fp16 = const()[name = string("const_111_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51648)))];
            tensor<fp16, [36]> const_112_to_fp16 = const()[name = string("const_112_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53568)))];
            tensor<fp16, [1, 36, 64, 64]> input_57_cast_fp16 = conv(bias = const_112_to_fp16, dilations = input_55_dilations_0, groups = input_55_groups_0, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = input_55_strides_0, weight = const_111_to_fp16, x = input_53_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_59_pad_type_0 = const()[name = string("input_59_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_59_strides_0 = const()[name = string("input_59_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_59_pad_0 = const()[name = string("input_59_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53760)))];
            tensor<int32, [2]> input_59_dilations_0 = const()[name = string("input_59_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_59_groups_0 = const()[name = string("input_59_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_113_to_fp16 = const()[name = string("const_113_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53888)))];
            tensor<fp16, [36]> const_114_to_fp16 = const()[name = string("const_114_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56576)))];
            tensor<fp16, [1, 36, 64, 64]> input_61_cast_fp16 = conv(bias = const_114_to_fp16, dilations = input_59_dilations_0, groups = input_59_groups_0, pad = input_59_pad_0, pad_type = input_59_pad_type_0, strides = input_59_strides_0, weight = const_113_to_fp16, x = input_57_cast_fp16)[name = string("input_61_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_1_cast_fp16 = relu(x = input_61_cast_fp16)[name = string("out2_1_cast_fp16")];
            string input_65_pad_type_0 = const()[name = string("input_65_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_65_strides_0 = const()[name = string("input_65_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_65_pad_0 = const()[name = string("input_65_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56768)))];
            tensor<int32, [2]> input_65_dilations_0 = const()[name = string("input_65_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_65_groups_0 = const()[name = string("input_65_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56896)))];
            tensor<fp16, [36]> const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59584)))];
            tensor<fp16, [1, 36, 64, 64]> input_67_cast_fp16 = conv(bias = const_116_to_fp16, dilations = input_65_dilations_0, groups = input_65_groups_0, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = input_65_strides_0, weight = const_115_to_fp16, x = var_2941_cast_fp16)[name = string("input_67_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_69_cast_fp16 = relu(x = input_67_cast_fp16)[name = string("input_69_cast_fp16")];
            string input_71_pad_type_0 = const()[name = string("input_71_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_71_pad_0 = const()[name = string("input_71_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59776)))];
            int32 input_71_groups_0 = const()[name = string("input_71_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_71_strides_0 = const()[name = string("input_71_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_71_dilations_0 = const()[name = string("input_71_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_117_to_fp16 = const()[name = string("const_117_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59904)))];
            tensor<fp16, [36]> const_118_to_fp16 = const()[name = string("const_118_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61824)))];
            tensor<fp16, [1, 36, 64, 64]> input_73_cast_fp16 = conv(bias = const_118_to_fp16, dilations = input_71_dilations_0, groups = input_71_groups_0, pad = input_71_pad_0, pad_type = input_71_pad_type_0, strides = input_71_strides_0, weight = const_117_to_fp16, x = input_69_cast_fp16)[name = string("input_73_cast_fp16")];
            string input_75_pad_type_0 = const()[name = string("input_75_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_75_strides_0 = const()[name = string("input_75_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_75_pad_0 = const()[name = string("input_75_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(62016)))];
            tensor<int32, [2]> input_75_dilations_0 = const()[name = string("input_75_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_75_groups_0 = const()[name = string("input_75_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_119_to_fp16 = const()[name = string("const_119_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(62144)))];
            tensor<fp16, [36]> const_120_to_fp16 = const()[name = string("const_120_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64832)))];
            tensor<fp16, [1, 36, 64, 64]> input_77_cast_fp16 = conv(bias = const_120_to_fp16, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = const_119_to_fp16, x = input_73_cast_fp16)[name = string("input_77_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_1_cast_fp16 = relu(x = input_77_cast_fp16)[name = string("out3_1_cast_fp16")];
            bool input_79_interleave_0 = const()[name = string("input_79_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_79_cast_fp16 = concat(axis = var_86, interleave = input_79_interleave_0, values = (var_2929_cast_fp16, out1_1_cast_fp16, out2_1_cast_fp16, out3_1_cast_fp16))[name = string("input_79_cast_fp16")];
            string input_81_pad_type_0 = const()[name = string("input_81_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_81_strides_0 = const()[name = string("input_81_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_81_pad_0 = const()[name = string("input_81_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(65024)))];
            tensor<int32, [2]> input_81_dilations_0 = const()[name = string("input_81_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_81_groups_0 = const()[name = string("input_81_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_121_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(65152))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85952))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86336)))];
            tensor<fp16, [144]> const_122_to_fp16 = const()[name = string("const_122_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86592)))];
            tensor<fp16, [1, 144, 64, 64]> input_83_cast_fp16 = conv(bias = const_122_to_fp16, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = const_121_to_fp16, x = input_79_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_85_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("input_85_cast_fp16")];
            string input_87_pad_type_0 = const()[name = string("input_87_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86976)))];
            int32 input_87_groups_0 = const()[name = string("input_87_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_87_strides_0 = const()[name = string("input_87_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_87_dilations_0 = const()[name = string("input_87_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [144, 1, 5, 5]> const_123_to_fp16 = const()[name = string("const_123_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(87104)))];
            tensor<fp16, [144]> const_124_to_fp16 = const()[name = string("const_124_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94400)))];
            tensor<fp16, [1, 144, 64, 64]> input_89_cast_fp16 = conv(bias = const_124_to_fp16, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = const_123_to_fp16, x = input_85_cast_fp16)[name = string("input_89_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_91_cast_fp16 = relu(x = input_89_cast_fp16)[name = string("input_91_cast_fp16")];
            string input_93_pad_type_0 = const()[name = string("input_93_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_93_strides_0 = const()[name = string("input_93_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_93_pad_0 = const()[name = string("input_93_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94784)))];
            tensor<int32, [2]> input_93_dilations_0 = const()[name = string("input_93_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_93_groups_0 = const()[name = string("input_93_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_125_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94912))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(115712))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116096)))];
            tensor<fp16, [144]> const_126_to_fp16 = const()[name = string("const_126_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116352)))];
            tensor<fp16, [1, 144, 64, 64]> y_1_cast_fp16 = conv(bias = const_126_to_fp16, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = const_125_to_fp16, x = input_91_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> x_3_cast_fp16 = add(x = input_79_cast_fp16, y = y_1_cast_fp16)[name = string("x_3_cast_fp16")];
            tensor<int32, [4]> var_3041_begin_0 = const()[name = string("op_3041_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116736)))];
            tensor<int32, [4]> var_3041_end_0 = const()[name = string("op_3041_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116864)))];
            tensor<bool, [4]> var_3041_end_mask_0 = const()[name = string("op_3041_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3041_cast_fp16 = slice_by_index(begin = var_3041_begin_0, end = var_3041_end_0, end_mask = var_3041_end_mask_0, x = x_3_cast_fp16)[name = string("op_3041_cast_fp16")];
            tensor<int32, [4]> var_3045_begin_0 = const()[name = string("op_3045_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116992)))];
            tensor<int32, [4]> var_3045_end_0 = const()[name = string("op_3045_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117120)))];
            tensor<bool, [4]> var_3045_end_mask_0 = const()[name = string("op_3045_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3045_cast_fp16 = slice_by_index(begin = var_3045_begin_0, end = var_3045_end_0, end_mask = var_3045_end_mask_0, x = x_3_cast_fp16)[name = string("op_3045_cast_fp16")];
            tensor<int32, [4]> var_3049_begin_0 = const()[name = string("op_3049_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117248)))];
            tensor<int32, [4]> var_3049_end_0 = const()[name = string("op_3049_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117376)))];
            tensor<bool, [4]> var_3049_end_mask_0 = const()[name = string("op_3049_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3049_cast_fp16 = slice_by_index(begin = var_3049_begin_0, end = var_3049_end_0, end_mask = var_3049_end_mask_0, x = x_3_cast_fp16)[name = string("op_3049_cast_fp16")];
            tensor<int32, [4]> var_3053_begin_0 = const()[name = string("op_3053_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117504)))];
            tensor<int32, [4]> var_3053_end_0 = const()[name = string("op_3053_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117632)))];
            tensor<bool, [4]> var_3053_end_mask_0 = const()[name = string("op_3053_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3053_cast_fp16 = slice_by_index(begin = var_3053_begin_0, end = var_3053_end_0, end_mask = var_3053_end_mask_0, x = x_3_cast_fp16)[name = string("op_3053_cast_fp16")];
            string input_97_pad_type_0 = const()[name = string("input_97_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_97_strides_0 = const()[name = string("input_97_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117760)))];
            tensor<int32, [2]> input_97_dilations_0 = const()[name = string("input_97_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_97_groups_0 = const()[name = string("input_97_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_127_to_fp16 = const()[name = string("const_127_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117888)))];
            tensor<fp16, [36]> const_128_to_fp16 = const()[name = string("const_128_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120576)))];
            tensor<fp16, [1, 36, 64, 64]> input_99_cast_fp16 = conv(bias = const_128_to_fp16, dilations = input_97_dilations_0, groups = input_97_groups_0, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = input_97_strides_0, weight = const_127_to_fp16, x = var_3045_cast_fp16)[name = string("input_99_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_101_cast_fp16 = relu(x = input_99_cast_fp16)[name = string("input_101_cast_fp16")];
            string input_103_pad_type_0 = const()[name = string("input_103_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_103_pad_0 = const()[name = string("input_103_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120768)))];
            int32 input_103_groups_0 = const()[name = string("input_103_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_103_strides_0 = const()[name = string("input_103_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_103_dilations_0 = const()[name = string("input_103_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_129_to_fp16 = const()[name = string("const_129_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120896)))];
            tensor<fp16, [36]> const_130_to_fp16 = const()[name = string("const_130_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(122816)))];
            tensor<fp16, [1, 36, 64, 64]> input_105_cast_fp16 = conv(bias = const_130_to_fp16, dilations = input_103_dilations_0, groups = input_103_groups_0, pad = input_103_pad_0, pad_type = input_103_pad_type_0, strides = input_103_strides_0, weight = const_129_to_fp16, x = input_101_cast_fp16)[name = string("input_105_cast_fp16")];
            string input_107_pad_type_0 = const()[name = string("input_107_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_107_strides_0 = const()[name = string("input_107_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_107_pad_0 = const()[name = string("input_107_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123008)))];
            tensor<int32, [2]> input_107_dilations_0 = const()[name = string("input_107_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_107_groups_0 = const()[name = string("input_107_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_131_to_fp16 = const()[name = string("const_131_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123136)))];
            tensor<fp16, [36]> const_132_to_fp16 = const()[name = string("const_132_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(125824)))];
            tensor<fp16, [1, 36, 64, 64]> input_109_cast_fp16 = conv(bias = const_132_to_fp16, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = const_131_to_fp16, x = input_105_cast_fp16)[name = string("input_109_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_3_cast_fp16 = relu(x = input_109_cast_fp16)[name = string("out1_3_cast_fp16")];
            string input_113_pad_type_0 = const()[name = string("input_113_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_113_strides_0 = const()[name = string("input_113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_113_pad_0 = const()[name = string("input_113_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(126016)))];
            tensor<int32, [2]> input_113_dilations_0 = const()[name = string("input_113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_113_groups_0 = const()[name = string("input_113_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_133_to_fp16 = const()[name = string("const_133_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(126144)))];
            tensor<fp16, [36]> const_134_to_fp16 = const()[name = string("const_134_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(128832)))];
            tensor<fp16, [1, 36, 64, 64]> input_115_cast_fp16 = conv(bias = const_134_to_fp16, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = const_133_to_fp16, x = var_3049_cast_fp16)[name = string("input_115_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_117_cast_fp16 = relu(x = input_115_cast_fp16)[name = string("input_117_cast_fp16")];
            string input_119_pad_type_0 = const()[name = string("input_119_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_119_pad_0 = const()[name = string("input_119_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(129024)))];
            int32 input_119_groups_0 = const()[name = string("input_119_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_119_strides_0 = const()[name = string("input_119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_119_dilations_0 = const()[name = string("input_119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_135_to_fp16 = const()[name = string("const_135_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(129152)))];
            tensor<fp16, [36]> const_136_to_fp16 = const()[name = string("const_136_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131072)))];
            tensor<fp16, [1, 36, 64, 64]> input_121_cast_fp16 = conv(bias = const_136_to_fp16, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = const_135_to_fp16, x = input_117_cast_fp16)[name = string("input_121_cast_fp16")];
            string input_123_pad_type_0 = const()[name = string("input_123_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_123_strides_0 = const()[name = string("input_123_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_123_pad_0 = const()[name = string("input_123_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131264)))];
            tensor<int32, [2]> input_123_dilations_0 = const()[name = string("input_123_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_123_groups_0 = const()[name = string("input_123_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_137_to_fp16 = const()[name = string("const_137_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131392)))];
            tensor<fp16, [36]> const_138_to_fp16 = const()[name = string("const_138_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134080)))];
            tensor<fp16, [1, 36, 64, 64]> input_125_cast_fp16 = conv(bias = const_138_to_fp16, dilations = input_123_dilations_0, groups = input_123_groups_0, pad = input_123_pad_0, pad_type = input_123_pad_type_0, strides = input_123_strides_0, weight = const_137_to_fp16, x = input_121_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_3_cast_fp16 = relu(x = input_125_cast_fp16)[name = string("out2_3_cast_fp16")];
            string input_129_pad_type_0 = const()[name = string("input_129_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_129_strides_0 = const()[name = string("input_129_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_129_pad_0 = const()[name = string("input_129_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134272)))];
            tensor<int32, [2]> input_129_dilations_0 = const()[name = string("input_129_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_129_groups_0 = const()[name = string("input_129_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_139_to_fp16 = const()[name = string("const_139_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134400)))];
            tensor<fp16, [36]> const_140_to_fp16 = const()[name = string("const_140_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137088)))];
            tensor<fp16, [1, 36, 64, 64]> input_131_cast_fp16 = conv(bias = const_140_to_fp16, dilations = input_129_dilations_0, groups = input_129_groups_0, pad = input_129_pad_0, pad_type = input_129_pad_type_0, strides = input_129_strides_0, weight = const_139_to_fp16, x = var_3053_cast_fp16)[name = string("input_131_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_133_cast_fp16 = relu(x = input_131_cast_fp16)[name = string("input_133_cast_fp16")];
            string input_135_pad_type_0 = const()[name = string("input_135_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_135_pad_0 = const()[name = string("input_135_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137280)))];
            int32 input_135_groups_0 = const()[name = string("input_135_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_135_strides_0 = const()[name = string("input_135_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_135_dilations_0 = const()[name = string("input_135_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_141_to_fp16 = const()[name = string("const_141_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137408)))];
            tensor<fp16, [36]> const_142_to_fp16 = const()[name = string("const_142_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139328)))];
            tensor<fp16, [1, 36, 64, 64]> input_137_cast_fp16 = conv(bias = const_142_to_fp16, dilations = input_135_dilations_0, groups = input_135_groups_0, pad = input_135_pad_0, pad_type = input_135_pad_type_0, strides = input_135_strides_0, weight = const_141_to_fp16, x = input_133_cast_fp16)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139520)))];
            tensor<int32, [2]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_143_to_fp16 = const()[name = string("const_143_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139648)))];
            tensor<fp16, [36]> const_144_to_fp16 = const()[name = string("const_144_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142336)))];
            tensor<fp16, [1, 36, 64, 64]> input_141_cast_fp16 = conv(bias = const_144_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = const_143_to_fp16, x = input_137_cast_fp16)[name = string("input_141_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_3_cast_fp16 = relu(x = input_141_cast_fp16)[name = string("out3_3_cast_fp16")];
            bool input_143_interleave_0 = const()[name = string("input_143_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_143_cast_fp16 = concat(axis = var_86, interleave = input_143_interleave_0, values = (var_3041_cast_fp16, out1_3_cast_fp16, out2_3_cast_fp16, out3_3_cast_fp16))[name = string("input_143_cast_fp16")];
            string input_145_pad_type_0 = const()[name = string("input_145_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_145_strides_0 = const()[name = string("input_145_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_145_pad_0 = const()[name = string("input_145_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142528)))];
            tensor<int32, [2]> input_145_dilations_0 = const()[name = string("input_145_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_145_groups_0 = const()[name = string("input_145_groups_0"), val = int32(1)];
            tensor<fp16, [256, 144, 1, 1]> const_145_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142656))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(179584))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180160)))];
            tensor<fp16, [256]> const_146_to_fp16 = const()[name = string("const_146_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180480)))];
            tensor<fp16, [1, 256, 64, 64]> input_147_cast_fp16 = conv(bias = const_146_to_fp16, dilations = input_145_dilations_0, groups = input_145_groups_0, pad = input_145_pad_0, pad_type = input_145_pad_type_0, strides = input_145_strides_0, weight = const_145_to_fp16, x = input_143_cast_fp16)[name = string("input_147_cast_fp16")];
            tensor<fp16, [1, 256, 64, 64]> input_149_cast_fp16 = relu(x = input_147_cast_fp16)[name = string("input_149_cast_fp16")];
            string input_151_pad_type_0 = const()[name = string("input_151_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_151_pad_0 = const()[name = string("input_151_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181056)))];
            tensor<int32, [2]> input_151_strides_0 = const()[name = string("input_151_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_151_groups_0 = const()[name = string("input_151_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_151_dilations_0 = const()[name = string("input_151_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_147_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181184))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(187648))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(188224)))];
            tensor<fp16, [256]> const_148_to_fp16 = const()[name = string("const_148_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(188544)))];
            tensor<fp16, [1, 256, 32, 32]> input_153_cast_fp16 = conv(bias = const_148_to_fp16, dilations = input_151_dilations_0, groups = input_151_groups_0, pad = input_151_pad_0, pad_type = input_151_pad_type_0, strides = input_151_strides_0, weight = const_147_to_fp16, x = input_149_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_155_cast_fp16 = relu(x = input_153_cast_fp16)[name = string("input_155_cast_fp16")];
            string input_157_pad_type_0 = const()[name = string("input_157_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_157_strides_0 = const()[name = string("input_157_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_157_pad_0 = const()[name = string("input_157_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189120)))];
            tensor<int32, [2]> input_157_dilations_0 = const()[name = string("input_157_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_157_groups_0 = const()[name = string("input_157_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_149_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189248))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(254848))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(255424)))];
            tensor<fp16, [256]> const_150_to_fp16 = const()[name = string("const_150_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(255744)))];
            tensor<fp16, [1, 256, 32, 32]> x_5_cast_fp16 = conv(bias = const_150_to_fp16, dilations = input_157_dilations_0, groups = input_157_groups_0, pad = input_157_pad_0, pad_type = input_157_pad_type_0, strides = input_157_strides_0, weight = const_149_to_fp16, x = input_155_cast_fp16)[name = string("x_5_cast_fp16")];
            tensor<int32, [4]> var_3152_begin_0 = const()[name = string("op_3152_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256320)))];
            tensor<int32, [4]> var_3152_end_0 = const()[name = string("op_3152_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256448)))];
            tensor<bool, [4]> var_3152_end_mask_0 = const()[name = string("op_3152_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3152_cast_fp16 = slice_by_index(begin = var_3152_begin_0, end = var_3152_end_0, end_mask = var_3152_end_mask_0, x = x_5_cast_fp16)[name = string("op_3152_cast_fp16")];
            tensor<int32, [4]> var_3156_begin_0 = const()[name = string("op_3156_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256576)))];
            tensor<int32, [4]> var_3156_end_0 = const()[name = string("op_3156_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256704)))];
            tensor<bool, [4]> var_3156_end_mask_0 = const()[name = string("op_3156_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3156_cast_fp16 = slice_by_index(begin = var_3156_begin_0, end = var_3156_end_0, end_mask = var_3156_end_mask_0, x = x_5_cast_fp16)[name = string("op_3156_cast_fp16")];
            tensor<int32, [4]> var_3160_begin_0 = const()[name = string("op_3160_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256832)))];
            tensor<int32, [4]> var_3160_end_0 = const()[name = string("op_3160_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256960)))];
            tensor<bool, [4]> var_3160_end_mask_0 = const()[name = string("op_3160_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3160_cast_fp16 = slice_by_index(begin = var_3160_begin_0, end = var_3160_end_0, end_mask = var_3160_end_mask_0, x = x_5_cast_fp16)[name = string("op_3160_cast_fp16")];
            tensor<int32, [4]> var_3164_begin_0 = const()[name = string("op_3164_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257088)))];
            tensor<int32, [4]> var_3164_end_0 = const()[name = string("op_3164_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257216)))];
            tensor<bool, [4]> var_3164_end_mask_0 = const()[name = string("op_3164_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3164_cast_fp16 = slice_by_index(begin = var_3164_begin_0, end = var_3164_end_0, end_mask = var_3164_end_mask_0, x = x_5_cast_fp16)[name = string("op_3164_cast_fp16")];
            string input_161_pad_type_0 = const()[name = string("input_161_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_161_strides_0 = const()[name = string("input_161_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_161_pad_0 = const()[name = string("input_161_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257344)))];
            tensor<int32, [2]> input_161_dilations_0 = const()[name = string("input_161_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_161_groups_0 = const()[name = string("input_161_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_151_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257472))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261632))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261824)))];
            tensor<fp16, [64]> const_152_to_fp16 = const()[name = string("const_152_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261952)))];
            tensor<fp16, [1, 64, 32, 32]> input_163_cast_fp16 = conv(bias = const_152_to_fp16, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_151_to_fp16, x = var_3156_cast_fp16)[name = string("input_163_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_165_cast_fp16 = relu(x = input_163_cast_fp16)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262144)))];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_153_to_fp16 = const()[name = string("const_153_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262272)))];
            tensor<fp16, [64]> const_154_to_fp16 = const()[name = string("const_154_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265536)))];
            tensor<fp16, [1, 64, 32, 32]> input_169_cast_fp16 = conv(bias = const_154_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_153_to_fp16, x = input_165_cast_fp16)[name = string("input_169_cast_fp16")];
            string input_171_pad_type_0 = const()[name = string("input_171_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_171_strides_0 = const()[name = string("input_171_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_171_pad_0 = const()[name = string("input_171_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265728)))];
            tensor<int32, [2]> input_171_dilations_0 = const()[name = string("input_171_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_171_groups_0 = const()[name = string("input_171_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_155_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265856))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270016))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270208)))];
            tensor<fp16, [64]> const_156_to_fp16 = const()[name = string("const_156_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270336)))];
            tensor<fp16, [1, 64, 32, 32]> input_173_cast_fp16 = conv(bias = const_156_to_fp16, dilations = input_171_dilations_0, groups = input_171_groups_0, pad = input_171_pad_0, pad_type = input_171_pad_type_0, strides = input_171_strides_0, weight = const_155_to_fp16, x = input_169_cast_fp16)[name = string("input_173_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_5_cast_fp16 = relu(x = input_173_cast_fp16)[name = string("out1_5_cast_fp16")];
            string input_177_pad_type_0 = const()[name = string("input_177_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_177_strides_0 = const()[name = string("input_177_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_177_pad_0 = const()[name = string("input_177_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270528)))];
            tensor<int32, [2]> input_177_dilations_0 = const()[name = string("input_177_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_177_groups_0 = const()[name = string("input_177_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_157_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270656))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274816))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275008)))];
            tensor<fp16, [64]> const_158_to_fp16 = const()[name = string("const_158_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275136)))];
            tensor<fp16, [1, 64, 32, 32]> input_179_cast_fp16 = conv(bias = const_158_to_fp16, dilations = input_177_dilations_0, groups = input_177_groups_0, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = input_177_strides_0, weight = const_157_to_fp16, x = var_3160_cast_fp16)[name = string("input_179_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_181_cast_fp16 = relu(x = input_179_cast_fp16)[name = string("input_181_cast_fp16")];
            string input_183_pad_type_0 = const()[name = string("input_183_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_183_pad_0 = const()[name = string("input_183_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275328)))];
            int32 input_183_groups_0 = const()[name = string("input_183_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_183_strides_0 = const()[name = string("input_183_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_183_dilations_0 = const()[name = string("input_183_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_159_to_fp16 = const()[name = string("const_159_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275456)))];
            tensor<fp16, [64]> const_160_to_fp16 = const()[name = string("const_160_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278720)))];
            tensor<fp16, [1, 64, 32, 32]> input_185_cast_fp16 = conv(bias = const_160_to_fp16, dilations = input_183_dilations_0, groups = input_183_groups_0, pad = input_183_pad_0, pad_type = input_183_pad_type_0, strides = input_183_strides_0, weight = const_159_to_fp16, x = input_181_cast_fp16)[name = string("input_185_cast_fp16")];
            string input_187_pad_type_0 = const()[name = string("input_187_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_187_strides_0 = const()[name = string("input_187_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_187_pad_0 = const()[name = string("input_187_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278912)))];
            tensor<int32, [2]> input_187_dilations_0 = const()[name = string("input_187_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_187_groups_0 = const()[name = string("input_187_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_161_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(279040))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283200))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283392)))];
            tensor<fp16, [64]> const_162_to_fp16 = const()[name = string("const_162_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283520)))];
            tensor<fp16, [1, 64, 32, 32]> input_189_cast_fp16 = conv(bias = const_162_to_fp16, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = const_161_to_fp16, x = input_185_cast_fp16)[name = string("input_189_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_5_cast_fp16 = relu(x = input_189_cast_fp16)[name = string("out2_5_cast_fp16")];
            string input_193_pad_type_0 = const()[name = string("input_193_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_193_strides_0 = const()[name = string("input_193_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_193_pad_0 = const()[name = string("input_193_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283712)))];
            tensor<int32, [2]> input_193_dilations_0 = const()[name = string("input_193_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_193_groups_0 = const()[name = string("input_193_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_163_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283840))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288000))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288192)))];
            tensor<fp16, [64]> const_164_to_fp16 = const()[name = string("const_164_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288320)))];
            tensor<fp16, [1, 64, 32, 32]> input_195_cast_fp16 = conv(bias = const_164_to_fp16, dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = const_163_to_fp16, x = var_3164_cast_fp16)[name = string("input_195_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_197_cast_fp16 = relu(x = input_195_cast_fp16)[name = string("input_197_cast_fp16")];
            string input_199_pad_type_0 = const()[name = string("input_199_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_199_pad_0 = const()[name = string("input_199_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288512)))];
            int32 input_199_groups_0 = const()[name = string("input_199_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_199_strides_0 = const()[name = string("input_199_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_199_dilations_0 = const()[name = string("input_199_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_165_to_fp16 = const()[name = string("const_165_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288640)))];
            tensor<fp16, [64]> const_166_to_fp16 = const()[name = string("const_166_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(291904)))];
            tensor<fp16, [1, 64, 32, 32]> input_201_cast_fp16 = conv(bias = const_166_to_fp16, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_165_to_fp16, x = input_197_cast_fp16)[name = string("input_201_cast_fp16")];
            string input_203_pad_type_0 = const()[name = string("input_203_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_203_strides_0 = const()[name = string("input_203_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_203_pad_0 = const()[name = string("input_203_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(292096)))];
            tensor<int32, [2]> input_203_dilations_0 = const()[name = string("input_203_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_203_groups_0 = const()[name = string("input_203_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_167_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(292224))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296384))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296576)))];
            tensor<fp16, [64]> const_168_to_fp16 = const()[name = string("const_168_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296704)))];
            tensor<fp16, [1, 64, 32, 32]> input_205_cast_fp16 = conv(bias = const_168_to_fp16, dilations = input_203_dilations_0, groups = input_203_groups_0, pad = input_203_pad_0, pad_type = input_203_pad_type_0, strides = input_203_strides_0, weight = const_167_to_fp16, x = input_201_cast_fp16)[name = string("input_205_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_5_cast_fp16 = relu(x = input_205_cast_fp16)[name = string("out3_5_cast_fp16")];
            bool input_207_interleave_0 = const()[name = string("input_207_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_207_cast_fp16 = concat(axis = var_86, interleave = input_207_interleave_0, values = (var_3152_cast_fp16, out1_5_cast_fp16, out2_5_cast_fp16, out3_5_cast_fp16))[name = string("input_207_cast_fp16")];
            string input_209_pad_type_0 = const()[name = string("input_209_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_209_strides_0 = const()[name = string("input_209_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_209_pad_0 = const()[name = string("input_209_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296896)))];
            tensor<int32, [2]> input_209_dilations_0 = const()[name = string("input_209_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_209_groups_0 = const()[name = string("input_209_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_169_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(297024))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(362624))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(363200)))];
            tensor<fp16, [256]> const_170_to_fp16 = const()[name = string("const_170_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(363520)))];
            tensor<fp16, [1, 256, 32, 32]> input_211_cast_fp16 = conv(bias = const_170_to_fp16, dilations = input_209_dilations_0, groups = input_209_groups_0, pad = input_209_pad_0, pad_type = input_209_pad_type_0, strides = input_209_strides_0, weight = const_169_to_fp16, x = input_207_cast_fp16)[name = string("input_211_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_213_cast_fp16 = relu(x = input_211_cast_fp16)[name = string("input_213_cast_fp16")];
            string input_215_pad_type_0 = const()[name = string("input_215_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_215_pad_0 = const()[name = string("input_215_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(364096)))];
            int32 input_215_groups_0 = const()[name = string("input_215_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_215_strides_0 = const()[name = string("input_215_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_215_dilations_0 = const()[name = string("input_215_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_171_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(364224))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(370688))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(371264)))];
            tensor<fp16, [256]> const_172_to_fp16 = const()[name = string("const_172_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(371584)))];
            tensor<fp16, [1, 256, 32, 32]> input_217_cast_fp16 = conv(bias = const_172_to_fp16, dilations = input_215_dilations_0, groups = input_215_groups_0, pad = input_215_pad_0, pad_type = input_215_pad_type_0, strides = input_215_strides_0, weight = const_171_to_fp16, x = input_213_cast_fp16)[name = string("input_217_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_219_cast_fp16 = relu(x = input_217_cast_fp16)[name = string("input_219_cast_fp16")];
            string input_221_pad_type_0 = const()[name = string("input_221_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_221_strides_0 = const()[name = string("input_221_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_221_pad_0 = const()[name = string("input_221_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(372160)))];
            tensor<int32, [2]> input_221_dilations_0 = const()[name = string("input_221_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_221_groups_0 = const()[name = string("input_221_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_173_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(372288))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(437888))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(438464)))];
            tensor<fp16, [256]> const_174_to_fp16 = const()[name = string("const_174_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(438784)))];
            tensor<fp16, [1, 256, 32, 32]> y_3_cast_fp16 = conv(bias = const_174_to_fp16, dilations = input_221_dilations_0, groups = input_221_groups_0, pad = input_221_pad_0, pad_type = input_221_pad_type_0, strides = input_221_strides_0, weight = const_173_to_fp16, x = input_219_cast_fp16)[name = string("y_3_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_7_cast_fp16 = add(x = input_207_cast_fp16, y = y_3_cast_fp16)[name = string("x_7_cast_fp16")];
            tensor<int32, [4]> var_3264_begin_0 = const()[name = string("op_3264_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439360)))];
            tensor<int32, [4]> var_3264_end_0 = const()[name = string("op_3264_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439488)))];
            tensor<bool, [4]> var_3264_end_mask_0 = const()[name = string("op_3264_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3264_cast_fp16 = slice_by_index(begin = var_3264_begin_0, end = var_3264_end_0, end_mask = var_3264_end_mask_0, x = x_7_cast_fp16)[name = string("op_3264_cast_fp16")];
            tensor<int32, [4]> var_3268_begin_0 = const()[name = string("op_3268_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439616)))];
            tensor<int32, [4]> var_3268_end_0 = const()[name = string("op_3268_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439744)))];
            tensor<bool, [4]> var_3268_end_mask_0 = const()[name = string("op_3268_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3268_cast_fp16 = slice_by_index(begin = var_3268_begin_0, end = var_3268_end_0, end_mask = var_3268_end_mask_0, x = x_7_cast_fp16)[name = string("op_3268_cast_fp16")];
            tensor<int32, [4]> var_3272_begin_0 = const()[name = string("op_3272_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439872)))];
            tensor<int32, [4]> var_3272_end_0 = const()[name = string("op_3272_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440000)))];
            tensor<bool, [4]> var_3272_end_mask_0 = const()[name = string("op_3272_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3272_cast_fp16 = slice_by_index(begin = var_3272_begin_0, end = var_3272_end_0, end_mask = var_3272_end_mask_0, x = x_7_cast_fp16)[name = string("op_3272_cast_fp16")];
            tensor<int32, [4]> var_3276_begin_0 = const()[name = string("op_3276_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440128)))];
            tensor<int32, [4]> var_3276_end_0 = const()[name = string("op_3276_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440256)))];
            tensor<bool, [4]> var_3276_end_mask_0 = const()[name = string("op_3276_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3276_cast_fp16 = slice_by_index(begin = var_3276_begin_0, end = var_3276_end_0, end_mask = var_3276_end_mask_0, x = x_7_cast_fp16)[name = string("op_3276_cast_fp16")];
            string input_225_pad_type_0 = const()[name = string("input_225_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_225_strides_0 = const()[name = string("input_225_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_225_pad_0 = const()[name = string("input_225_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440384)))];
            tensor<int32, [2]> input_225_dilations_0 = const()[name = string("input_225_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_225_groups_0 = const()[name = string("input_225_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_175_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440512))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444672))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444864)))];
            tensor<fp16, [64]> const_176_to_fp16 = const()[name = string("const_176_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444992)))];
            tensor<fp16, [1, 64, 32, 32]> input_227_cast_fp16 = conv(bias = const_176_to_fp16, dilations = input_225_dilations_0, groups = input_225_groups_0, pad = input_225_pad_0, pad_type = input_225_pad_type_0, strides = input_225_strides_0, weight = const_175_to_fp16, x = var_3268_cast_fp16)[name = string("input_227_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_229_cast_fp16 = relu(x = input_227_cast_fp16)[name = string("input_229_cast_fp16")];
            string input_231_pad_type_0 = const()[name = string("input_231_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_231_pad_0 = const()[name = string("input_231_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(445184)))];
            int32 input_231_groups_0 = const()[name = string("input_231_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_231_strides_0 = const()[name = string("input_231_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_231_dilations_0 = const()[name = string("input_231_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_177_to_fp16 = const()[name = string("const_177_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(445312)))];
            tensor<fp16, [64]> const_178_to_fp16 = const()[name = string("const_178_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448576)))];
            tensor<fp16, [1, 64, 32, 32]> input_233_cast_fp16 = conv(bias = const_178_to_fp16, dilations = input_231_dilations_0, groups = input_231_groups_0, pad = input_231_pad_0, pad_type = input_231_pad_type_0, strides = input_231_strides_0, weight = const_177_to_fp16, x = input_229_cast_fp16)[name = string("input_233_cast_fp16")];
            string input_235_pad_type_0 = const()[name = string("input_235_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_235_strides_0 = const()[name = string("input_235_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_235_pad_0 = const()[name = string("input_235_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448768)))];
            tensor<int32, [2]> input_235_dilations_0 = const()[name = string("input_235_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_235_groups_0 = const()[name = string("input_235_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_179_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448896))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453056))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453248)))];
            tensor<fp16, [64]> const_180_to_fp16 = const()[name = string("const_180_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453376)))];
            tensor<fp16, [1, 64, 32, 32]> input_237_cast_fp16 = conv(bias = const_180_to_fp16, dilations = input_235_dilations_0, groups = input_235_groups_0, pad = input_235_pad_0, pad_type = input_235_pad_type_0, strides = input_235_strides_0, weight = const_179_to_fp16, x = input_233_cast_fp16)[name = string("input_237_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_7_cast_fp16 = relu(x = input_237_cast_fp16)[name = string("out1_7_cast_fp16")];
            string input_241_pad_type_0 = const()[name = string("input_241_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_241_strides_0 = const()[name = string("input_241_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_241_pad_0 = const()[name = string("input_241_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453568)))];
            tensor<int32, [2]> input_241_dilations_0 = const()[name = string("input_241_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_241_groups_0 = const()[name = string("input_241_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_181_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453696))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(457856))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458048)))];
            tensor<fp16, [64]> const_182_to_fp16 = const()[name = string("const_182_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458176)))];
            tensor<fp16, [1, 64, 32, 32]> input_243_cast_fp16 = conv(bias = const_182_to_fp16, dilations = input_241_dilations_0, groups = input_241_groups_0, pad = input_241_pad_0, pad_type = input_241_pad_type_0, strides = input_241_strides_0, weight = const_181_to_fp16, x = var_3272_cast_fp16)[name = string("input_243_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_245_cast_fp16 = relu(x = input_243_cast_fp16)[name = string("input_245_cast_fp16")];
            string input_247_pad_type_0 = const()[name = string("input_247_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_247_pad_0 = const()[name = string("input_247_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458368)))];
            int32 input_247_groups_0 = const()[name = string("input_247_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_247_strides_0 = const()[name = string("input_247_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_247_dilations_0 = const()[name = string("input_247_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_183_to_fp16 = const()[name = string("const_183_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458496)))];
            tensor<fp16, [64]> const_184_to_fp16 = const()[name = string("const_184_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(461760)))];
            tensor<fp16, [1, 64, 32, 32]> input_249_cast_fp16 = conv(bias = const_184_to_fp16, dilations = input_247_dilations_0, groups = input_247_groups_0, pad = input_247_pad_0, pad_type = input_247_pad_type_0, strides = input_247_strides_0, weight = const_183_to_fp16, x = input_245_cast_fp16)[name = string("input_249_cast_fp16")];
            string input_251_pad_type_0 = const()[name = string("input_251_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_251_strides_0 = const()[name = string("input_251_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_251_pad_0 = const()[name = string("input_251_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(461952)))];
            tensor<int32, [2]> input_251_dilations_0 = const()[name = string("input_251_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_251_groups_0 = const()[name = string("input_251_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_185_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(462080))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466240))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466432)))];
            tensor<fp16, [64]> const_186_to_fp16 = const()[name = string("const_186_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466560)))];
            tensor<fp16, [1, 64, 32, 32]> input_253_cast_fp16 = conv(bias = const_186_to_fp16, dilations = input_251_dilations_0, groups = input_251_groups_0, pad = input_251_pad_0, pad_type = input_251_pad_type_0, strides = input_251_strides_0, weight = const_185_to_fp16, x = input_249_cast_fp16)[name = string("input_253_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_7_cast_fp16 = relu(x = input_253_cast_fp16)[name = string("out2_7_cast_fp16")];
            string input_257_pad_type_0 = const()[name = string("input_257_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_257_strides_0 = const()[name = string("input_257_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_257_pad_0 = const()[name = string("input_257_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466752)))];
            tensor<int32, [2]> input_257_dilations_0 = const()[name = string("input_257_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_257_groups_0 = const()[name = string("input_257_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_187_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466880))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471040))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471232)))];
            tensor<fp16, [64]> const_188_to_fp16 = const()[name = string("const_188_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471360)))];
            tensor<fp16, [1, 64, 32, 32]> input_259_cast_fp16 = conv(bias = const_188_to_fp16, dilations = input_257_dilations_0, groups = input_257_groups_0, pad = input_257_pad_0, pad_type = input_257_pad_type_0, strides = input_257_strides_0, weight = const_187_to_fp16, x = var_3276_cast_fp16)[name = string("input_259_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_261_cast_fp16 = relu(x = input_259_cast_fp16)[name = string("input_261_cast_fp16")];
            string input_263_pad_type_0 = const()[name = string("input_263_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_263_pad_0 = const()[name = string("input_263_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471552)))];
            int32 input_263_groups_0 = const()[name = string("input_263_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_263_strides_0 = const()[name = string("input_263_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_263_dilations_0 = const()[name = string("input_263_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_189_to_fp16 = const()[name = string("const_189_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471680)))];
            tensor<fp16, [64]> const_190_to_fp16 = const()[name = string("const_190_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(474944)))];
            tensor<fp16, [1, 64, 32, 32]> input_265_cast_fp16 = conv(bias = const_190_to_fp16, dilations = input_263_dilations_0, groups = input_263_groups_0, pad = input_263_pad_0, pad_type = input_263_pad_type_0, strides = input_263_strides_0, weight = const_189_to_fp16, x = input_261_cast_fp16)[name = string("input_265_cast_fp16")];
            string input_267_pad_type_0 = const()[name = string("input_267_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_267_strides_0 = const()[name = string("input_267_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_267_pad_0 = const()[name = string("input_267_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(475136)))];
            tensor<int32, [2]> input_267_dilations_0 = const()[name = string("input_267_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_267_groups_0 = const()[name = string("input_267_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_191_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(475264))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479424))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479616)))];
            tensor<fp16, [64]> const_192_to_fp16 = const()[name = string("const_192_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479744)))];
            tensor<fp16, [1, 64, 32, 32]> input_269_cast_fp16 = conv(bias = const_192_to_fp16, dilations = input_267_dilations_0, groups = input_267_groups_0, pad = input_267_pad_0, pad_type = input_267_pad_type_0, strides = input_267_strides_0, weight = const_191_to_fp16, x = input_265_cast_fp16)[name = string("input_269_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_7_cast_fp16 = relu(x = input_269_cast_fp16)[name = string("out3_7_cast_fp16")];
            bool input_271_interleave_0 = const()[name = string("input_271_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_271_cast_fp16 = concat(axis = var_86, interleave = input_271_interleave_0, values = (var_3264_cast_fp16, out1_7_cast_fp16, out2_7_cast_fp16, out3_7_cast_fp16))[name = string("input_271_cast_fp16")];
            string input_273_pad_type_0 = const()[name = string("input_273_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_273_strides_0 = const()[name = string("input_273_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_273_pad_0 = const()[name = string("input_273_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479936)))];
            tensor<int32, [2]> input_273_dilations_0 = const()[name = string("input_273_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_273_groups_0 = const()[name = string("input_273_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_193_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(480064))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(545664))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(546240)))];
            tensor<fp16, [256]> const_194_to_fp16 = const()[name = string("const_194_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(546560)))];
            tensor<fp16, [1, 256, 32, 32]> input_275_cast_fp16 = conv(bias = const_194_to_fp16, dilations = input_273_dilations_0, groups = input_273_groups_0, pad = input_273_pad_0, pad_type = input_273_pad_type_0, strides = input_273_strides_0, weight = const_193_to_fp16, x = input_271_cast_fp16)[name = string("input_275_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_277_cast_fp16 = relu(x = input_275_cast_fp16)[name = string("input_277_cast_fp16")];
            string input_279_pad_type_0 = const()[name = string("input_279_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_279_pad_0 = const()[name = string("input_279_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(547136)))];
            int32 input_279_groups_0 = const()[name = string("input_279_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_279_strides_0 = const()[name = string("input_279_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_279_dilations_0 = const()[name = string("input_279_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_195_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(547264))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(553728))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(554304)))];
            tensor<fp16, [256]> const_196_to_fp16 = const()[name = string("const_196_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(554624)))];
            tensor<fp16, [1, 256, 32, 32]> input_281_cast_fp16 = conv(bias = const_196_to_fp16, dilations = input_279_dilations_0, groups = input_279_groups_0, pad = input_279_pad_0, pad_type = input_279_pad_type_0, strides = input_279_strides_0, weight = const_195_to_fp16, x = input_277_cast_fp16)[name = string("input_281_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_283_cast_fp16 = relu(x = input_281_cast_fp16)[name = string("input_283_cast_fp16")];
            string input_285_pad_type_0 = const()[name = string("input_285_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_285_strides_0 = const()[name = string("input_285_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_285_pad_0 = const()[name = string("input_285_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(555200)))];
            tensor<int32, [2]> input_285_dilations_0 = const()[name = string("input_285_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_285_groups_0 = const()[name = string("input_285_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_197_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(555328))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(620928))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(621504)))];
            tensor<fp16, [256]> const_198_to_fp16 = const()[name = string("const_198_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(621824)))];
            tensor<fp16, [1, 256, 32, 32]> y_5_cast_fp16 = conv(bias = const_198_to_fp16, dilations = input_285_dilations_0, groups = input_285_groups_0, pad = input_285_pad_0, pad_type = input_285_pad_type_0, strides = input_285_strides_0, weight = const_197_to_fp16, x = input_283_cast_fp16)[name = string("y_5_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_9_cast_fp16 = add(x = input_271_cast_fp16, y = y_5_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<int32, [4]> var_3376_begin_0 = const()[name = string("op_3376_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622400)))];
            tensor<int32, [4]> var_3376_end_0 = const()[name = string("op_3376_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622528)))];
            tensor<bool, [4]> var_3376_end_mask_0 = const()[name = string("op_3376_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3376_cast_fp16 = slice_by_index(begin = var_3376_begin_0, end = var_3376_end_0, end_mask = var_3376_end_mask_0, x = x_9_cast_fp16)[name = string("op_3376_cast_fp16")];
            tensor<int32, [4]> var_3380_begin_0 = const()[name = string("op_3380_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622656)))];
            tensor<int32, [4]> var_3380_end_0 = const()[name = string("op_3380_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622784)))];
            tensor<bool, [4]> var_3380_end_mask_0 = const()[name = string("op_3380_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3380_cast_fp16 = slice_by_index(begin = var_3380_begin_0, end = var_3380_end_0, end_mask = var_3380_end_mask_0, x = x_9_cast_fp16)[name = string("op_3380_cast_fp16")];
            tensor<int32, [4]> var_3384_begin_0 = const()[name = string("op_3384_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622912)))];
            tensor<int32, [4]> var_3384_end_0 = const()[name = string("op_3384_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623040)))];
            tensor<bool, [4]> var_3384_end_mask_0 = const()[name = string("op_3384_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3384_cast_fp16 = slice_by_index(begin = var_3384_begin_0, end = var_3384_end_0, end_mask = var_3384_end_mask_0, x = x_9_cast_fp16)[name = string("op_3384_cast_fp16")];
            tensor<int32, [4]> var_3388_begin_0 = const()[name = string("op_3388_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623168)))];
            tensor<int32, [4]> var_3388_end_0 = const()[name = string("op_3388_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623296)))];
            tensor<bool, [4]> var_3388_end_mask_0 = const()[name = string("op_3388_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3388_cast_fp16 = slice_by_index(begin = var_3388_begin_0, end = var_3388_end_0, end_mask = var_3388_end_mask_0, x = x_9_cast_fp16)[name = string("op_3388_cast_fp16")];
            string input_289_pad_type_0 = const()[name = string("input_289_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_289_strides_0 = const()[name = string("input_289_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_289_pad_0 = const()[name = string("input_289_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623424)))];
            tensor<int32, [2]> input_289_dilations_0 = const()[name = string("input_289_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_289_groups_0 = const()[name = string("input_289_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_199_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623552))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627712))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627904)))];
            tensor<fp16, [64]> const_200_to_fp16 = const()[name = string("const_200_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628032)))];
            tensor<fp16, [1, 64, 32, 32]> input_291_cast_fp16 = conv(bias = const_200_to_fp16, dilations = input_289_dilations_0, groups = input_289_groups_0, pad = input_289_pad_0, pad_type = input_289_pad_type_0, strides = input_289_strides_0, weight = const_199_to_fp16, x = var_3380_cast_fp16)[name = string("input_291_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_293_cast_fp16 = relu(x = input_291_cast_fp16)[name = string("input_293_cast_fp16")];
            string input_295_pad_type_0 = const()[name = string("input_295_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_295_pad_0 = const()[name = string("input_295_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628224)))];
            int32 input_295_groups_0 = const()[name = string("input_295_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_295_strides_0 = const()[name = string("input_295_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_295_dilations_0 = const()[name = string("input_295_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_201_to_fp16 = const()[name = string("const_201_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628352)))];
            tensor<fp16, [64]> const_202_to_fp16 = const()[name = string("const_202_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631616)))];
            tensor<fp16, [1, 64, 32, 32]> input_297_cast_fp16 = conv(bias = const_202_to_fp16, dilations = input_295_dilations_0, groups = input_295_groups_0, pad = input_295_pad_0, pad_type = input_295_pad_type_0, strides = input_295_strides_0, weight = const_201_to_fp16, x = input_293_cast_fp16)[name = string("input_297_cast_fp16")];
            string input_299_pad_type_0 = const()[name = string("input_299_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_299_strides_0 = const()[name = string("input_299_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_299_pad_0 = const()[name = string("input_299_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631808)))];
            tensor<int32, [2]> input_299_dilations_0 = const()[name = string("input_299_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_299_groups_0 = const()[name = string("input_299_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_203_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631936))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636096))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636288)))];
            tensor<fp16, [64]> const_204_to_fp16 = const()[name = string("const_204_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636416)))];
            tensor<fp16, [1, 64, 32, 32]> input_301_cast_fp16 = conv(bias = const_204_to_fp16, dilations = input_299_dilations_0, groups = input_299_groups_0, pad = input_299_pad_0, pad_type = input_299_pad_type_0, strides = input_299_strides_0, weight = const_203_to_fp16, x = input_297_cast_fp16)[name = string("input_301_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_9_cast_fp16 = relu(x = input_301_cast_fp16)[name = string("out1_9_cast_fp16")];
            string input_305_pad_type_0 = const()[name = string("input_305_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_305_strides_0 = const()[name = string("input_305_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_305_pad_0 = const()[name = string("input_305_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636608)))];
            tensor<int32, [2]> input_305_dilations_0 = const()[name = string("input_305_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_305_groups_0 = const()[name = string("input_305_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_205_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636736))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(640896))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641088)))];
            tensor<fp16, [64]> const_206_to_fp16 = const()[name = string("const_206_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641216)))];
            tensor<fp16, [1, 64, 32, 32]> input_307_cast_fp16 = conv(bias = const_206_to_fp16, dilations = input_305_dilations_0, groups = input_305_groups_0, pad = input_305_pad_0, pad_type = input_305_pad_type_0, strides = input_305_strides_0, weight = const_205_to_fp16, x = var_3384_cast_fp16)[name = string("input_307_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_309_cast_fp16 = relu(x = input_307_cast_fp16)[name = string("input_309_cast_fp16")];
            string input_311_pad_type_0 = const()[name = string("input_311_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_311_pad_0 = const()[name = string("input_311_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641408)))];
            int32 input_311_groups_0 = const()[name = string("input_311_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_311_strides_0 = const()[name = string("input_311_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_311_dilations_0 = const()[name = string("input_311_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_207_to_fp16 = const()[name = string("const_207_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641536)))];
            tensor<fp16, [64]> const_208_to_fp16 = const()[name = string("const_208_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(644800)))];
            tensor<fp16, [1, 64, 32, 32]> input_313_cast_fp16 = conv(bias = const_208_to_fp16, dilations = input_311_dilations_0, groups = input_311_groups_0, pad = input_311_pad_0, pad_type = input_311_pad_type_0, strides = input_311_strides_0, weight = const_207_to_fp16, x = input_309_cast_fp16)[name = string("input_313_cast_fp16")];
            string input_315_pad_type_0 = const()[name = string("input_315_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_315_strides_0 = const()[name = string("input_315_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_315_pad_0 = const()[name = string("input_315_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(644992)))];
            tensor<int32, [2]> input_315_dilations_0 = const()[name = string("input_315_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_315_groups_0 = const()[name = string("input_315_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_209_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(645120))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649280))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649472)))];
            tensor<fp16, [64]> const_210_to_fp16 = const()[name = string("const_210_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649600)))];
            tensor<fp16, [1, 64, 32, 32]> input_317_cast_fp16 = conv(bias = const_210_to_fp16, dilations = input_315_dilations_0, groups = input_315_groups_0, pad = input_315_pad_0, pad_type = input_315_pad_type_0, strides = input_315_strides_0, weight = const_209_to_fp16, x = input_313_cast_fp16)[name = string("input_317_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_9_cast_fp16 = relu(x = input_317_cast_fp16)[name = string("out2_9_cast_fp16")];
            string input_321_pad_type_0 = const()[name = string("input_321_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_321_strides_0 = const()[name = string("input_321_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_321_pad_0 = const()[name = string("input_321_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649792)))];
            tensor<int32, [2]> input_321_dilations_0 = const()[name = string("input_321_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_321_groups_0 = const()[name = string("input_321_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_211_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649920))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654080))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654272)))];
            tensor<fp16, [64]> const_212_to_fp16 = const()[name = string("const_212_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654400)))];
            tensor<fp16, [1, 64, 32, 32]> input_323_cast_fp16 = conv(bias = const_212_to_fp16, dilations = input_321_dilations_0, groups = input_321_groups_0, pad = input_321_pad_0, pad_type = input_321_pad_type_0, strides = input_321_strides_0, weight = const_211_to_fp16, x = var_3388_cast_fp16)[name = string("input_323_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_325_cast_fp16 = relu(x = input_323_cast_fp16)[name = string("input_325_cast_fp16")];
            string input_327_pad_type_0 = const()[name = string("input_327_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_327_pad_0 = const()[name = string("input_327_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654592)))];
            int32 input_327_groups_0 = const()[name = string("input_327_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_327_strides_0 = const()[name = string("input_327_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_327_dilations_0 = const()[name = string("input_327_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_213_to_fp16 = const()[name = string("const_213_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654720)))];
            tensor<fp16, [64]> const_214_to_fp16 = const()[name = string("const_214_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(657984)))];
            tensor<fp16, [1, 64, 32, 32]> input_329_cast_fp16 = conv(bias = const_214_to_fp16, dilations = input_327_dilations_0, groups = input_327_groups_0, pad = input_327_pad_0, pad_type = input_327_pad_type_0, strides = input_327_strides_0, weight = const_213_to_fp16, x = input_325_cast_fp16)[name = string("input_329_cast_fp16")];
            string input_331_pad_type_0 = const()[name = string("input_331_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_331_strides_0 = const()[name = string("input_331_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_331_pad_0 = const()[name = string("input_331_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658176)))];
            tensor<int32, [2]> input_331_dilations_0 = const()[name = string("input_331_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_331_groups_0 = const()[name = string("input_331_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_215_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658304))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662464))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662656)))];
            tensor<fp16, [64]> const_216_to_fp16 = const()[name = string("const_216_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662784)))];
            tensor<fp16, [1, 64, 32, 32]> input_333_cast_fp16 = conv(bias = const_216_to_fp16, dilations = input_331_dilations_0, groups = input_331_groups_0, pad = input_331_pad_0, pad_type = input_331_pad_type_0, strides = input_331_strides_0, weight = const_215_to_fp16, x = input_329_cast_fp16)[name = string("input_333_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_9_cast_fp16 = relu(x = input_333_cast_fp16)[name = string("out3_9_cast_fp16")];
            bool input_335_interleave_0 = const()[name = string("input_335_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_335_cast_fp16 = concat(axis = var_86, interleave = input_335_interleave_0, values = (var_3376_cast_fp16, out1_9_cast_fp16, out2_9_cast_fp16, out3_9_cast_fp16))[name = string("input_335_cast_fp16")];
            string input_337_pad_type_0 = const()[name = string("input_337_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_337_strides_0 = const()[name = string("input_337_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_337_pad_0 = const()[name = string("input_337_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662976)))];
            tensor<int32, [2]> input_337_dilations_0 = const()[name = string("input_337_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_337_groups_0 = const()[name = string("input_337_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_217_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(663104))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(728704))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729280)))];
            tensor<fp16, [256]> const_218_to_fp16 = const()[name = string("const_218_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729600)))];
            tensor<fp16, [1, 256, 32, 32]> input_339_cast_fp16 = conv(bias = const_218_to_fp16, dilations = input_337_dilations_0, groups = input_337_groups_0, pad = input_337_pad_0, pad_type = input_337_pad_type_0, strides = input_337_strides_0, weight = const_217_to_fp16, x = input_335_cast_fp16)[name = string("input_339_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_341_cast_fp16 = relu(x = input_339_cast_fp16)[name = string("input_341_cast_fp16")];
            string input_343_pad_type_0 = const()[name = string("input_343_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_343_pad_0 = const()[name = string("input_343_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(730176)))];
            int32 input_343_groups_0 = const()[name = string("input_343_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_343_strides_0 = const()[name = string("input_343_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_343_dilations_0 = const()[name = string("input_343_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_219_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(730304))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(736768))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(737344)))];
            tensor<fp16, [256]> const_220_to_fp16 = const()[name = string("const_220_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(737664)))];
            tensor<fp16, [1, 256, 32, 32]> input_345_cast_fp16 = conv(bias = const_220_to_fp16, dilations = input_343_dilations_0, groups = input_343_groups_0, pad = input_343_pad_0, pad_type = input_343_pad_type_0, strides = input_343_strides_0, weight = const_219_to_fp16, x = input_341_cast_fp16)[name = string("input_345_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_347_cast_fp16 = relu(x = input_345_cast_fp16)[name = string("input_347_cast_fp16")];
            string input_349_pad_type_0 = const()[name = string("input_349_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_349_strides_0 = const()[name = string("input_349_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_349_pad_0 = const()[name = string("input_349_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(738240)))];
            tensor<int32, [2]> input_349_dilations_0 = const()[name = string("input_349_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_349_groups_0 = const()[name = string("input_349_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_221_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(738368))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(803968))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(804544)))];
            tensor<fp16, [256]> const_222_to_fp16 = const()[name = string("const_222_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(804864)))];
            tensor<fp16, [1, 256, 32, 32]> y_7_cast_fp16 = conv(bias = const_222_to_fp16, dilations = input_349_dilations_0, groups = input_349_groups_0, pad = input_349_pad_0, pad_type = input_349_pad_type_0, strides = input_349_strides_0, weight = const_221_to_fp16, x = input_347_cast_fp16)[name = string("y_7_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_11_cast_fp16 = add(x = input_335_cast_fp16, y = y_7_cast_fp16)[name = string("x_11_cast_fp16")];
            tensor<int32, [4]> var_3488_begin_0 = const()[name = string("op_3488_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805440)))];
            tensor<int32, [4]> var_3488_end_0 = const()[name = string("op_3488_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805568)))];
            tensor<bool, [4]> var_3488_end_mask_0 = const()[name = string("op_3488_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3488_cast_fp16 = slice_by_index(begin = var_3488_begin_0, end = var_3488_end_0, end_mask = var_3488_end_mask_0, x = x_11_cast_fp16)[name = string("op_3488_cast_fp16")];
            tensor<int32, [4]> var_3492_begin_0 = const()[name = string("op_3492_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805696)))];
            tensor<int32, [4]> var_3492_end_0 = const()[name = string("op_3492_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805824)))];
            tensor<bool, [4]> var_3492_end_mask_0 = const()[name = string("op_3492_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3492_cast_fp16 = slice_by_index(begin = var_3492_begin_0, end = var_3492_end_0, end_mask = var_3492_end_mask_0, x = x_11_cast_fp16)[name = string("op_3492_cast_fp16")];
            tensor<int32, [4]> var_3496_begin_0 = const()[name = string("op_3496_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805952)))];
            tensor<int32, [4]> var_3496_end_0 = const()[name = string("op_3496_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806080)))];
            tensor<bool, [4]> var_3496_end_mask_0 = const()[name = string("op_3496_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3496_cast_fp16 = slice_by_index(begin = var_3496_begin_0, end = var_3496_end_0, end_mask = var_3496_end_mask_0, x = x_11_cast_fp16)[name = string("op_3496_cast_fp16")];
            tensor<int32, [4]> var_3500_begin_0 = const()[name = string("op_3500_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806208)))];
            tensor<int32, [4]> var_3500_end_0 = const()[name = string("op_3500_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806336)))];
            tensor<bool, [4]> var_3500_end_mask_0 = const()[name = string("op_3500_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3500_cast_fp16 = slice_by_index(begin = var_3500_begin_0, end = var_3500_end_0, end_mask = var_3500_end_mask_0, x = x_11_cast_fp16)[name = string("op_3500_cast_fp16")];
            string input_353_pad_type_0 = const()[name = string("input_353_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_353_strides_0 = const()[name = string("input_353_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_353_pad_0 = const()[name = string("input_353_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806464)))];
            tensor<int32, [2]> input_353_dilations_0 = const()[name = string("input_353_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_353_groups_0 = const()[name = string("input_353_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_223_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806592))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(810752))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(810944)))];
            tensor<fp16, [64]> const_224_to_fp16 = const()[name = string("const_224_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811072)))];
            tensor<fp16, [1, 64, 32, 32]> input_355_cast_fp16 = conv(bias = const_224_to_fp16, dilations = input_353_dilations_0, groups = input_353_groups_0, pad = input_353_pad_0, pad_type = input_353_pad_type_0, strides = input_353_strides_0, weight = const_223_to_fp16, x = var_3492_cast_fp16)[name = string("input_355_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_357_cast_fp16 = relu(x = input_355_cast_fp16)[name = string("input_357_cast_fp16")];
            string input_359_pad_type_0 = const()[name = string("input_359_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_359_pad_0 = const()[name = string("input_359_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811264)))];
            int32 input_359_groups_0 = const()[name = string("input_359_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_359_strides_0 = const()[name = string("input_359_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_359_dilations_0 = const()[name = string("input_359_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_225_to_fp16 = const()[name = string("const_225_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811392)))];
            tensor<fp16, [64]> const_226_to_fp16 = const()[name = string("const_226_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814656)))];
            tensor<fp16, [1, 64, 32, 32]> input_361_cast_fp16 = conv(bias = const_226_to_fp16, dilations = input_359_dilations_0, groups = input_359_groups_0, pad = input_359_pad_0, pad_type = input_359_pad_type_0, strides = input_359_strides_0, weight = const_225_to_fp16, x = input_357_cast_fp16)[name = string("input_361_cast_fp16")];
            string input_363_pad_type_0 = const()[name = string("input_363_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_363_strides_0 = const()[name = string("input_363_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_363_pad_0 = const()[name = string("input_363_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814848)))];
            tensor<int32, [2]> input_363_dilations_0 = const()[name = string("input_363_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_363_groups_0 = const()[name = string("input_363_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_227_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814976))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819136))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819328)))];
            tensor<fp16, [64]> const_228_to_fp16 = const()[name = string("const_228_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819456)))];
            tensor<fp16, [1, 64, 32, 32]> input_365_cast_fp16 = conv(bias = const_228_to_fp16, dilations = input_363_dilations_0, groups = input_363_groups_0, pad = input_363_pad_0, pad_type = input_363_pad_type_0, strides = input_363_strides_0, weight = const_227_to_fp16, x = input_361_cast_fp16)[name = string("input_365_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_11_cast_fp16 = relu(x = input_365_cast_fp16)[name = string("out1_11_cast_fp16")];
            string input_369_pad_type_0 = const()[name = string("input_369_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_369_strides_0 = const()[name = string("input_369_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_369_pad_0 = const()[name = string("input_369_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819648)))];
            tensor<int32, [2]> input_369_dilations_0 = const()[name = string("input_369_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_369_groups_0 = const()[name = string("input_369_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_229_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819776))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(823936))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824128)))];
            tensor<fp16, [64]> const_230_to_fp16 = const()[name = string("const_230_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824256)))];
            tensor<fp16, [1, 64, 32, 32]> input_371_cast_fp16 = conv(bias = const_230_to_fp16, dilations = input_369_dilations_0, groups = input_369_groups_0, pad = input_369_pad_0, pad_type = input_369_pad_type_0, strides = input_369_strides_0, weight = const_229_to_fp16, x = var_3496_cast_fp16)[name = string("input_371_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_373_cast_fp16 = relu(x = input_371_cast_fp16)[name = string("input_373_cast_fp16")];
            string input_375_pad_type_0 = const()[name = string("input_375_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_375_pad_0 = const()[name = string("input_375_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824448)))];
            int32 input_375_groups_0 = const()[name = string("input_375_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_375_strides_0 = const()[name = string("input_375_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_375_dilations_0 = const()[name = string("input_375_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_231_to_fp16 = const()[name = string("const_231_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824576)))];
            tensor<fp16, [64]> const_232_to_fp16 = const()[name = string("const_232_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(827840)))];
            tensor<fp16, [1, 64, 32, 32]> input_377_cast_fp16 = conv(bias = const_232_to_fp16, dilations = input_375_dilations_0, groups = input_375_groups_0, pad = input_375_pad_0, pad_type = input_375_pad_type_0, strides = input_375_strides_0, weight = const_231_to_fp16, x = input_373_cast_fp16)[name = string("input_377_cast_fp16")];
            string input_379_pad_type_0 = const()[name = string("input_379_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_379_strides_0 = const()[name = string("input_379_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_379_pad_0 = const()[name = string("input_379_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(828032)))];
            tensor<int32, [2]> input_379_dilations_0 = const()[name = string("input_379_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_379_groups_0 = const()[name = string("input_379_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_233_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(828160))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832320))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832512)))];
            tensor<fp16, [64]> const_234_to_fp16 = const()[name = string("const_234_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832640)))];
            tensor<fp16, [1, 64, 32, 32]> input_381_cast_fp16 = conv(bias = const_234_to_fp16, dilations = input_379_dilations_0, groups = input_379_groups_0, pad = input_379_pad_0, pad_type = input_379_pad_type_0, strides = input_379_strides_0, weight = const_233_to_fp16, x = input_377_cast_fp16)[name = string("input_381_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_11_cast_fp16 = relu(x = input_381_cast_fp16)[name = string("out2_11_cast_fp16")];
            string input_385_pad_type_0 = const()[name = string("input_385_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_385_strides_0 = const()[name = string("input_385_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_385_pad_0 = const()[name = string("input_385_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832832)))];
            tensor<int32, [2]> input_385_dilations_0 = const()[name = string("input_385_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_385_groups_0 = const()[name = string("input_385_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_235_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832960))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837120))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837312)))];
            tensor<fp16, [64]> const_236_to_fp16 = const()[name = string("const_236_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837440)))];
            tensor<fp16, [1, 64, 32, 32]> input_387_cast_fp16 = conv(bias = const_236_to_fp16, dilations = input_385_dilations_0, groups = input_385_groups_0, pad = input_385_pad_0, pad_type = input_385_pad_type_0, strides = input_385_strides_0, weight = const_235_to_fp16, x = var_3500_cast_fp16)[name = string("input_387_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_389_cast_fp16 = relu(x = input_387_cast_fp16)[name = string("input_389_cast_fp16")];
            string input_391_pad_type_0 = const()[name = string("input_391_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_391_pad_0 = const()[name = string("input_391_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837632)))];
            int32 input_391_groups_0 = const()[name = string("input_391_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_391_strides_0 = const()[name = string("input_391_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_391_dilations_0 = const()[name = string("input_391_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_237_to_fp16 = const()[name = string("const_237_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837760)))];
            tensor<fp16, [64]> const_238_to_fp16 = const()[name = string("const_238_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841024)))];
            tensor<fp16, [1, 64, 32, 32]> input_393_cast_fp16 = conv(bias = const_238_to_fp16, dilations = input_391_dilations_0, groups = input_391_groups_0, pad = input_391_pad_0, pad_type = input_391_pad_type_0, strides = input_391_strides_0, weight = const_237_to_fp16, x = input_389_cast_fp16)[name = string("input_393_cast_fp16")];
            string input_395_pad_type_0 = const()[name = string("input_395_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_395_strides_0 = const()[name = string("input_395_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_395_pad_0 = const()[name = string("input_395_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841216)))];
            tensor<int32, [2]> input_395_dilations_0 = const()[name = string("input_395_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_395_groups_0 = const()[name = string("input_395_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_239_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841344))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845504))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845696)))];
            tensor<fp16, [64]> const_240_to_fp16 = const()[name = string("const_240_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845824)))];
            tensor<fp16, [1, 64, 32, 32]> input_397_cast_fp16 = conv(bias = const_240_to_fp16, dilations = input_395_dilations_0, groups = input_395_groups_0, pad = input_395_pad_0, pad_type = input_395_pad_type_0, strides = input_395_strides_0, weight = const_239_to_fp16, x = input_393_cast_fp16)[name = string("input_397_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_11_cast_fp16 = relu(x = input_397_cast_fp16)[name = string("out3_11_cast_fp16")];
            bool input_399_interleave_0 = const()[name = string("input_399_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_399_cast_fp16 = concat(axis = var_86, interleave = input_399_interleave_0, values = (var_3488_cast_fp16, out1_11_cast_fp16, out2_11_cast_fp16, out3_11_cast_fp16))[name = string("input_399_cast_fp16")];
            string input_401_pad_type_0 = const()[name = string("input_401_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_401_strides_0 = const()[name = string("input_401_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_401_pad_0 = const()[name = string("input_401_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846016)))];
            tensor<int32, [2]> input_401_dilations_0 = const()[name = string("input_401_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_401_groups_0 = const()[name = string("input_401_groups_0"), val = int32(1)];
            tensor<fp16, [512, 256, 1, 1]> const_241_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846144))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(977280))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(978368)))];
            tensor<fp16, [512]> const_242_to_fp16 = const()[name = string("const_242_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(978944)))];
            tensor<fp16, [1, 512, 32, 32]> input_403_cast_fp16 = conv(bias = const_242_to_fp16, dilations = input_401_dilations_0, groups = input_401_groups_0, pad = input_401_pad_0, pad_type = input_401_pad_type_0, strides = input_401_strides_0, weight = const_241_to_fp16, x = input_399_cast_fp16)[name = string("input_403_cast_fp16")];
            tensor<fp16, [1, 512, 32, 32]> input_405_cast_fp16 = relu(x = input_403_cast_fp16)[name = string("input_405_cast_fp16")];
            string input_407_pad_type_0 = const()[name = string("input_407_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_407_pad_0 = const()[name = string("input_407_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(980032)))];
            tensor<int32, [2]> input_407_strides_0 = const()[name = string("input_407_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_407_groups_0 = const()[name = string("input_407_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_407_dilations_0 = const()[name = string("input_407_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [512, 1, 5, 5]> const_243_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(980160))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(993024))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(994112)))];
            tensor<fp16, [512]> const_244_to_fp16 = const()[name = string("const_244_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(994688)))];
            tensor<fp16, [1, 512, 16, 16]> input_409_cast_fp16 = conv(bias = const_244_to_fp16, dilations = input_407_dilations_0, groups = input_407_groups_0, pad = input_407_pad_0, pad_type = input_407_pad_type_0, strides = input_407_strides_0, weight = const_243_to_fp16, x = input_405_cast_fp16)[name = string("input_409_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_411_cast_fp16 = relu(x = input_409_cast_fp16)[name = string("input_411_cast_fp16")];
            string input_413_pad_type_0 = const()[name = string("input_413_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_413_strides_0 = const()[name = string("input_413_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_413_pad_0 = const()[name = string("input_413_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(995776)))];
            tensor<int32, [2]> input_413_dilations_0 = const()[name = string("input_413_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_413_groups_0 = const()[name = string("input_413_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_245_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(995904))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1258112))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1259200)))];
            tensor<fp16, [512]> const_246_to_fp16 = const()[name = string("const_246_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1259776)))];
            tensor<fp16, [1, 512, 16, 16]> x_13_cast_fp16 = conv(bias = const_246_to_fp16, dilations = input_413_dilations_0, groups = input_413_groups_0, pad = input_413_pad_0, pad_type = input_413_pad_type_0, strides = input_413_strides_0, weight = const_245_to_fp16, x = input_411_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<int32, [4]> var_3599_begin_0 = const()[name = string("op_3599_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1260864)))];
            tensor<int32, [4]> var_3599_end_0 = const()[name = string("op_3599_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1260992)))];
            tensor<bool, [4]> var_3599_end_mask_0 = const()[name = string("op_3599_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3599_cast_fp16 = slice_by_index(begin = var_3599_begin_0, end = var_3599_end_0, end_mask = var_3599_end_mask_0, x = x_13_cast_fp16)[name = string("op_3599_cast_fp16")];
            tensor<int32, [4]> var_3603_begin_0 = const()[name = string("op_3603_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261120)))];
            tensor<int32, [4]> var_3603_end_0 = const()[name = string("op_3603_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261248)))];
            tensor<bool, [4]> var_3603_end_mask_0 = const()[name = string("op_3603_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3603_cast_fp16 = slice_by_index(begin = var_3603_begin_0, end = var_3603_end_0, end_mask = var_3603_end_mask_0, x = x_13_cast_fp16)[name = string("op_3603_cast_fp16")];
            tensor<int32, [4]> var_3607_begin_0 = const()[name = string("op_3607_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261376)))];
            tensor<int32, [4]> var_3607_end_0 = const()[name = string("op_3607_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261504)))];
            tensor<bool, [4]> var_3607_end_mask_0 = const()[name = string("op_3607_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3607_cast_fp16 = slice_by_index(begin = var_3607_begin_0, end = var_3607_end_0, end_mask = var_3607_end_mask_0, x = x_13_cast_fp16)[name = string("op_3607_cast_fp16")];
            tensor<int32, [4]> var_3611_begin_0 = const()[name = string("op_3611_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261632)))];
            tensor<int32, [4]> var_3611_end_0 = const()[name = string("op_3611_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261760)))];
            tensor<bool, [4]> var_3611_end_mask_0 = const()[name = string("op_3611_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3611_cast_fp16 = slice_by_index(begin = var_3611_begin_0, end = var_3611_end_0, end_mask = var_3611_end_mask_0, x = x_13_cast_fp16)[name = string("op_3611_cast_fp16")];
            string input_417_pad_type_0 = const()[name = string("input_417_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_417_strides_0 = const()[name = string("input_417_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_417_pad_0 = const()[name = string("input_417_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261888)))];
            tensor<int32, [2]> input_417_dilations_0 = const()[name = string("input_417_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_417_groups_0 = const()[name = string("input_417_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_247_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1262016))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278464))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278784)))];
            tensor<fp16, [128]> const_248_to_fp16 = const()[name = string("const_248_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278976)))];
            tensor<fp16, [1, 128, 16, 16]> input_419_cast_fp16 = conv(bias = const_248_to_fp16, dilations = input_417_dilations_0, groups = input_417_groups_0, pad = input_417_pad_0, pad_type = input_417_pad_type_0, strides = input_417_strides_0, weight = const_247_to_fp16, x = var_3603_cast_fp16)[name = string("input_419_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_421_cast_fp16 = relu(x = input_419_cast_fp16)[name = string("input_421_cast_fp16")];
            string input_423_pad_type_0 = const()[name = string("input_423_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_423_pad_0 = const()[name = string("input_423_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1279296)))];
            int32 input_423_groups_0 = const()[name = string("input_423_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_423_strides_0 = const()[name = string("input_423_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_423_dilations_0 = const()[name = string("input_423_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_249_to_fp16 = const()[name = string("const_249_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1279424)))];
            tensor<fp16, [128]> const_250_to_fp16 = const()[name = string("const_250_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1285888)))];
            tensor<fp16, [1, 128, 16, 16]> input_425_cast_fp16 = conv(bias = const_250_to_fp16, dilations = input_423_dilations_0, groups = input_423_groups_0, pad = input_423_pad_0, pad_type = input_423_pad_type_0, strides = input_423_strides_0, weight = const_249_to_fp16, x = input_421_cast_fp16)[name = string("input_425_cast_fp16")];
            string input_427_pad_type_0 = const()[name = string("input_427_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_427_strides_0 = const()[name = string("input_427_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_427_pad_0 = const()[name = string("input_427_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1286208)))];
            tensor<int32, [2]> input_427_dilations_0 = const()[name = string("input_427_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_427_groups_0 = const()[name = string("input_427_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_251_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1286336))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1302784))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303104)))];
            tensor<fp16, [128]> const_252_to_fp16 = const()[name = string("const_252_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303296)))];
            tensor<fp16, [1, 128, 16, 16]> input_429_cast_fp16 = conv(bias = const_252_to_fp16, dilations = input_427_dilations_0, groups = input_427_groups_0, pad = input_427_pad_0, pad_type = input_427_pad_type_0, strides = input_427_strides_0, weight = const_251_to_fp16, x = input_425_cast_fp16)[name = string("input_429_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_13_cast_fp16 = relu(x = input_429_cast_fp16)[name = string("out1_13_cast_fp16")];
            string input_433_pad_type_0 = const()[name = string("input_433_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_433_strides_0 = const()[name = string("input_433_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_433_pad_0 = const()[name = string("input_433_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303616)))];
            tensor<int32, [2]> input_433_dilations_0 = const()[name = string("input_433_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_433_groups_0 = const()[name = string("input_433_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_253_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303744))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320192))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320512)))];
            tensor<fp16, [128]> const_254_to_fp16 = const()[name = string("const_254_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320704)))];
            tensor<fp16, [1, 128, 16, 16]> input_435_cast_fp16 = conv(bias = const_254_to_fp16, dilations = input_433_dilations_0, groups = input_433_groups_0, pad = input_433_pad_0, pad_type = input_433_pad_type_0, strides = input_433_strides_0, weight = const_253_to_fp16, x = var_3607_cast_fp16)[name = string("input_435_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_437_cast_fp16 = relu(x = input_435_cast_fp16)[name = string("input_437_cast_fp16")];
            string input_439_pad_type_0 = const()[name = string("input_439_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_439_pad_0 = const()[name = string("input_439_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1321024)))];
            int32 input_439_groups_0 = const()[name = string("input_439_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_439_strides_0 = const()[name = string("input_439_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_439_dilations_0 = const()[name = string("input_439_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_255_to_fp16 = const()[name = string("const_255_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1321152)))];
            tensor<fp16, [128]> const_256_to_fp16 = const()[name = string("const_256_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1327616)))];
            tensor<fp16, [1, 128, 16, 16]> input_441_cast_fp16 = conv(bias = const_256_to_fp16, dilations = input_439_dilations_0, groups = input_439_groups_0, pad = input_439_pad_0, pad_type = input_439_pad_type_0, strides = input_439_strides_0, weight = const_255_to_fp16, x = input_437_cast_fp16)[name = string("input_441_cast_fp16")];
            string input_443_pad_type_0 = const()[name = string("input_443_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_443_strides_0 = const()[name = string("input_443_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_443_pad_0 = const()[name = string("input_443_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1327936)))];
            tensor<int32, [2]> input_443_dilations_0 = const()[name = string("input_443_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_443_groups_0 = const()[name = string("input_443_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_257_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1328064))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1344512))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1344832)))];
            tensor<fp16, [128]> const_258_to_fp16 = const()[name = string("const_258_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345024)))];
            tensor<fp16, [1, 128, 16, 16]> input_445_cast_fp16 = conv(bias = const_258_to_fp16, dilations = input_443_dilations_0, groups = input_443_groups_0, pad = input_443_pad_0, pad_type = input_443_pad_type_0, strides = input_443_strides_0, weight = const_257_to_fp16, x = input_441_cast_fp16)[name = string("input_445_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_13_cast_fp16 = relu(x = input_445_cast_fp16)[name = string("out2_13_cast_fp16")];
            string input_449_pad_type_0 = const()[name = string("input_449_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_449_strides_0 = const()[name = string("input_449_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_449_pad_0 = const()[name = string("input_449_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345344)))];
            tensor<int32, [2]> input_449_dilations_0 = const()[name = string("input_449_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_449_groups_0 = const()[name = string("input_449_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_259_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345472))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1361920))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362240)))];
            tensor<fp16, [128]> const_260_to_fp16 = const()[name = string("const_260_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362432)))];
            tensor<fp16, [1, 128, 16, 16]> input_451_cast_fp16 = conv(bias = const_260_to_fp16, dilations = input_449_dilations_0, groups = input_449_groups_0, pad = input_449_pad_0, pad_type = input_449_pad_type_0, strides = input_449_strides_0, weight = const_259_to_fp16, x = var_3611_cast_fp16)[name = string("input_451_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_453_cast_fp16 = relu(x = input_451_cast_fp16)[name = string("input_453_cast_fp16")];
            string input_455_pad_type_0 = const()[name = string("input_455_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_455_pad_0 = const()[name = string("input_455_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362752)))];
            int32 input_455_groups_0 = const()[name = string("input_455_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_455_strides_0 = const()[name = string("input_455_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_455_dilations_0 = const()[name = string("input_455_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_261_to_fp16 = const()[name = string("const_261_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362880)))];
            tensor<fp16, [128]> const_262_to_fp16 = const()[name = string("const_262_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369344)))];
            tensor<fp16, [1, 128, 16, 16]> input_457_cast_fp16 = conv(bias = const_262_to_fp16, dilations = input_455_dilations_0, groups = input_455_groups_0, pad = input_455_pad_0, pad_type = input_455_pad_type_0, strides = input_455_strides_0, weight = const_261_to_fp16, x = input_453_cast_fp16)[name = string("input_457_cast_fp16")];
            string input_459_pad_type_0 = const()[name = string("input_459_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_459_strides_0 = const()[name = string("input_459_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_459_pad_0 = const()[name = string("input_459_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369664)))];
            tensor<int32, [2]> input_459_dilations_0 = const()[name = string("input_459_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_459_groups_0 = const()[name = string("input_459_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_263_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369792))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386240))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386560)))];
            tensor<fp16, [128]> const_264_to_fp16 = const()[name = string("const_264_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386752)))];
            tensor<fp16, [1, 128, 16, 16]> input_461_cast_fp16 = conv(bias = const_264_to_fp16, dilations = input_459_dilations_0, groups = input_459_groups_0, pad = input_459_pad_0, pad_type = input_459_pad_type_0, strides = input_459_strides_0, weight = const_263_to_fp16, x = input_457_cast_fp16)[name = string("input_461_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_13_cast_fp16 = relu(x = input_461_cast_fp16)[name = string("out3_13_cast_fp16")];
            bool input_463_interleave_0 = const()[name = string("input_463_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_463_cast_fp16 = concat(axis = var_86, interleave = input_463_interleave_0, values = (var_3599_cast_fp16, out1_13_cast_fp16, out2_13_cast_fp16, out3_13_cast_fp16))[name = string("input_463_cast_fp16")];
            string input_465_pad_type_0 = const()[name = string("input_465_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_465_strides_0 = const()[name = string("input_465_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_465_pad_0 = const()[name = string("input_465_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1387072)))];
            tensor<int32, [2]> input_465_dilations_0 = const()[name = string("input_465_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_465_groups_0 = const()[name = string("input_465_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_265_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1387200))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1649408))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1650496)))];
            tensor<fp16, [512]> const_266_to_fp16 = const()[name = string("const_266_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1651072)))];
            tensor<fp16, [1, 512, 16, 16]> input_467_cast_fp16 = conv(bias = const_266_to_fp16, dilations = input_465_dilations_0, groups = input_465_groups_0, pad = input_465_pad_0, pad_type = input_465_pad_type_0, strides = input_465_strides_0, weight = const_265_to_fp16, x = input_463_cast_fp16)[name = string("input_467_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_469_cast_fp16 = relu(x = input_467_cast_fp16)[name = string("input_469_cast_fp16")];
            string input_471_pad_type_0 = const()[name = string("input_471_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_471_pad_0 = const()[name = string("input_471_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1652160)))];
            int32 input_471_groups_0 = const()[name = string("input_471_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_471_strides_0 = const()[name = string("input_471_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_471_dilations_0 = const()[name = string("input_471_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [512, 1, 5, 5]> const_267_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1652288))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1665152))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1666240)))];
            tensor<fp16, [512]> const_268_to_fp16 = const()[name = string("const_268_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1666816)))];
            tensor<fp16, [1, 512, 16, 16]> input_473_cast_fp16 = conv(bias = const_268_to_fp16, dilations = input_471_dilations_0, groups = input_471_groups_0, pad = input_471_pad_0, pad_type = input_471_pad_type_0, strides = input_471_strides_0, weight = const_267_to_fp16, x = input_469_cast_fp16)[name = string("input_473_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_475_cast_fp16 = relu(x = input_473_cast_fp16)[name = string("input_475_cast_fp16")];
            string input_477_pad_type_0 = const()[name = string("input_477_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_477_strides_0 = const()[name = string("input_477_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_477_pad_0 = const()[name = string("input_477_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1667904)))];
            tensor<int32, [2]> input_477_dilations_0 = const()[name = string("input_477_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_477_groups_0 = const()[name = string("input_477_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_269_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1668032))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1930240))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1931328)))];
            tensor<fp16, [512]> const_270_to_fp16 = const()[name = string("const_270_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1931904)))];
            tensor<fp16, [1, 512, 16, 16]> y_9_cast_fp16 = conv(bias = const_270_to_fp16, dilations = input_477_dilations_0, groups = input_477_groups_0, pad = input_477_pad_0, pad_type = input_477_pad_type_0, strides = input_477_strides_0, weight = const_269_to_fp16, x = input_475_cast_fp16)[name = string("y_9_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> x_15_cast_fp16 = add(x = input_463_cast_fp16, y = y_9_cast_fp16)[name = string("x_15_cast_fp16")];
            tensor<int32, [4]> var_3711_begin_0 = const()[name = string("op_3711_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1932992)))];
            tensor<int32, [4]> var_3711_end_0 = const()[name = string("op_3711_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933120)))];
            tensor<bool, [4]> var_3711_end_mask_0 = const()[name = string("op_3711_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3711_cast_fp16 = slice_by_index(begin = var_3711_begin_0, end = var_3711_end_0, end_mask = var_3711_end_mask_0, x = x_15_cast_fp16)[name = string("op_3711_cast_fp16")];
            tensor<int32, [4]> var_3715_begin_0 = const()[name = string("op_3715_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933248)))];
            tensor<int32, [4]> var_3715_end_0 = const()[name = string("op_3715_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933376)))];
            tensor<bool, [4]> var_3715_end_mask_0 = const()[name = string("op_3715_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3715_cast_fp16 = slice_by_index(begin = var_3715_begin_0, end = var_3715_end_0, end_mask = var_3715_end_mask_0, x = x_15_cast_fp16)[name = string("op_3715_cast_fp16")];
            tensor<int32, [4]> var_3719_begin_0 = const()[name = string("op_3719_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933504)))];
            tensor<int32, [4]> var_3719_end_0 = const()[name = string("op_3719_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933632)))];
            tensor<bool, [4]> var_3719_end_mask_0 = const()[name = string("op_3719_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3719_cast_fp16 = slice_by_index(begin = var_3719_begin_0, end = var_3719_end_0, end_mask = var_3719_end_mask_0, x = x_15_cast_fp16)[name = string("op_3719_cast_fp16")];
            tensor<int32, [4]> var_3723_begin_0 = const()[name = string("op_3723_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933760)))];
            tensor<int32, [4]> var_3723_end_0 = const()[name = string("op_3723_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933888)))];
            tensor<bool, [4]> var_3723_end_mask_0 = const()[name = string("op_3723_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3723_cast_fp16 = slice_by_index(begin = var_3723_begin_0, end = var_3723_end_0, end_mask = var_3723_end_mask_0, x = x_15_cast_fp16)[name = string("op_3723_cast_fp16")];
            string input_481_pad_type_0 = const()[name = string("input_481_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_481_strides_0 = const()[name = string("input_481_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_481_pad_0 = const()[name = string("input_481_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1934016)))];
            tensor<int32, [2]> input_481_dilations_0 = const()[name = string("input_481_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_481_groups_0 = const()[name = string("input_481_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_271_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1934144))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1950592))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1950912)))];
            tensor<fp16, [128]> const_272_to_fp16 = const()[name = string("const_272_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951104)))];
            tensor<fp16, [1, 128, 16, 16]> input_483_cast_fp16 = conv(bias = const_272_to_fp16, dilations = input_481_dilations_0, groups = input_481_groups_0, pad = input_481_pad_0, pad_type = input_481_pad_type_0, strides = input_481_strides_0, weight = const_271_to_fp16, x = var_3715_cast_fp16)[name = string("input_483_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_485_cast_fp16 = relu(x = input_483_cast_fp16)[name = string("input_485_cast_fp16")];
            string input_487_pad_type_0 = const()[name = string("input_487_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_487_pad_0 = const()[name = string("input_487_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951424)))];
            int32 input_487_groups_0 = const()[name = string("input_487_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_487_strides_0 = const()[name = string("input_487_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_487_dilations_0 = const()[name = string("input_487_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_273_to_fp16 = const()[name = string("const_273_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951552)))];
            tensor<fp16, [128]> const_274_to_fp16 = const()[name = string("const_274_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958016)))];
            tensor<fp16, [1, 128, 16, 16]> input_489_cast_fp16 = conv(bias = const_274_to_fp16, dilations = input_487_dilations_0, groups = input_487_groups_0, pad = input_487_pad_0, pad_type = input_487_pad_type_0, strides = input_487_strides_0, weight = const_273_to_fp16, x = input_485_cast_fp16)[name = string("input_489_cast_fp16")];
            string input_491_pad_type_0 = const()[name = string("input_491_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_491_strides_0 = const()[name = string("input_491_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_491_pad_0 = const()[name = string("input_491_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958336)))];
            tensor<int32, [2]> input_491_dilations_0 = const()[name = string("input_491_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_491_groups_0 = const()[name = string("input_491_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_275_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958464))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1974912))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975232)))];
            tensor<fp16, [128]> const_276_to_fp16 = const()[name = string("const_276_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975424)))];
            tensor<fp16, [1, 128, 16, 16]> input_493_cast_fp16 = conv(bias = const_276_to_fp16, dilations = input_491_dilations_0, groups = input_491_groups_0, pad = input_491_pad_0, pad_type = input_491_pad_type_0, strides = input_491_strides_0, weight = const_275_to_fp16, x = input_489_cast_fp16)[name = string("input_493_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_15_cast_fp16 = relu(x = input_493_cast_fp16)[name = string("out1_15_cast_fp16")];
            string input_497_pad_type_0 = const()[name = string("input_497_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_497_strides_0 = const()[name = string("input_497_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_497_pad_0 = const()[name = string("input_497_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975744)))];
            tensor<int32, [2]> input_497_dilations_0 = const()[name = string("input_497_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_497_groups_0 = const()[name = string("input_497_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_277_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975872))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992320))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992640)))];
            tensor<fp16, [128]> const_278_to_fp16 = const()[name = string("const_278_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992832)))];
            tensor<fp16, [1, 128, 16, 16]> input_499_cast_fp16 = conv(bias = const_278_to_fp16, dilations = input_497_dilations_0, groups = input_497_groups_0, pad = input_497_pad_0, pad_type = input_497_pad_type_0, strides = input_497_strides_0, weight = const_277_to_fp16, x = var_3719_cast_fp16)[name = string("input_499_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_501_cast_fp16 = relu(x = input_499_cast_fp16)[name = string("input_501_cast_fp16")];
            string input_503_pad_type_0 = const()[name = string("input_503_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_503_pad_0 = const()[name = string("input_503_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1993152)))];
            int32 input_503_groups_0 = const()[name = string("input_503_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_503_strides_0 = const()[name = string("input_503_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_503_dilations_0 = const()[name = string("input_503_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_279_to_fp16 = const()[name = string("const_279_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1993280)))];
            tensor<fp16, [128]> const_280_to_fp16 = const()[name = string("const_280_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1999744)))];
            tensor<fp16, [1, 128, 16, 16]> input_505_cast_fp16 = conv(bias = const_280_to_fp16, dilations = input_503_dilations_0, groups = input_503_groups_0, pad = input_503_pad_0, pad_type = input_503_pad_type_0, strides = input_503_strides_0, weight = const_279_to_fp16, x = input_501_cast_fp16)[name = string("input_505_cast_fp16")];
            string input_507_pad_type_0 = const()[name = string("input_507_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_507_strides_0 = const()[name = string("input_507_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_507_pad_0 = const()[name = string("input_507_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2000064)))];
            tensor<int32, [2]> input_507_dilations_0 = const()[name = string("input_507_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_507_groups_0 = const()[name = string("input_507_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_281_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2000192))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2016640))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2016960)))];
            tensor<fp16, [128]> const_282_to_fp16 = const()[name = string("const_282_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017152)))];
            tensor<fp16, [1, 128, 16, 16]> input_509_cast_fp16 = conv(bias = const_282_to_fp16, dilations = input_507_dilations_0, groups = input_507_groups_0, pad = input_507_pad_0, pad_type = input_507_pad_type_0, strides = input_507_strides_0, weight = const_281_to_fp16, x = input_505_cast_fp16)[name = string("input_509_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_15_cast_fp16 = relu(x = input_509_cast_fp16)[name = string("out2_15_cast_fp16")];
            string input_513_pad_type_0 = const()[name = string("input_513_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_513_strides_0 = const()[name = string("input_513_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_513_pad_0 = const()[name = string("input_513_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017472)))];
            tensor<int32, [2]> input_513_dilations_0 = const()[name = string("input_513_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_513_groups_0 = const()[name = string("input_513_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_283_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017600))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034048))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034368)))];
            tensor<fp16, [128]> const_284_to_fp16 = const()[name = string("const_284_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034560)))];
            tensor<fp16, [1, 128, 16, 16]> input_515_cast_fp16 = conv(bias = const_284_to_fp16, dilations = input_513_dilations_0, groups = input_513_groups_0, pad = input_513_pad_0, pad_type = input_513_pad_type_0, strides = input_513_strides_0, weight = const_283_to_fp16, x = var_3723_cast_fp16)[name = string("input_515_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_517_cast_fp16 = relu(x = input_515_cast_fp16)[name = string("input_517_cast_fp16")];
            string input_519_pad_type_0 = const()[name = string("input_519_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_519_pad_0 = const()[name = string("input_519_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034880)))];
            int32 input_519_groups_0 = const()[name = string("input_519_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_519_strides_0 = const()[name = string("input_519_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_519_dilations_0 = const()[name = string("input_519_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_285_to_fp16 = const()[name = string("const_285_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2035008)))];
            tensor<fp16, [128]> const_286_to_fp16 = const()[name = string("const_286_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041472)))];
            tensor<fp16, [1, 128, 16, 16]> input_521_cast_fp16 = conv(bias = const_286_to_fp16, dilations = input_519_dilations_0, groups = input_519_groups_0, pad = input_519_pad_0, pad_type = input_519_pad_type_0, strides = input_519_strides_0, weight = const_285_to_fp16, x = input_517_cast_fp16)[name = string("input_521_cast_fp16")];
            string input_523_pad_type_0 = const()[name = string("input_523_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_523_strides_0 = const()[name = string("input_523_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_523_pad_0 = const()[name = string("input_523_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041792)))];
            tensor<int32, [2]> input_523_dilations_0 = const()[name = string("input_523_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_523_groups_0 = const()[name = string("input_523_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_287_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041920))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058368))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058688)))];
            tensor<fp16, [128]> const_288_to_fp16 = const()[name = string("const_288_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058880)))];
            tensor<fp16, [1, 128, 16, 16]> input_525_cast_fp16 = conv(bias = const_288_to_fp16, dilations = input_523_dilations_0, groups = input_523_groups_0, pad = input_523_pad_0, pad_type = input_523_pad_type_0, strides = input_523_strides_0, weight = const_287_to_fp16, x = input_521_cast_fp16)[name = string("input_525_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_15_cast_fp16 = relu(x = input_525_cast_fp16)[name = string("out3_15_cast_fp16")];
            bool input_527_interleave_0 = const()[name = string("input_527_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_527_cast_fp16 = concat(axis = var_86, interleave = input_527_interleave_0, values = (var_3711_cast_fp16, out1_15_cast_fp16, out2_15_cast_fp16, out3_15_cast_fp16))[name = string("input_527_cast_fp16")];
            string input_529_pad_type_0 = const()[name = string("input_529_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_529_strides_0 = const()[name = string("input_529_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_529_pad_0 = const()[name = string("input_529_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2059200)))];
            tensor<int32, [2]> input_529_dilations_0 = const()[name = string("input_529_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_529_groups_0 = const()[name = string("input_529_groups_0"), val = int32(1)];
            tensor<fp16, [128, 512, 1, 1]> model_key_encoder_xfpn_p5_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2059328))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2124928))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125248)))];
            tensor<fp16, [1, 128, 16, 16]> input_529_cast_fp16 = conv(dilations = input_529_dilations_0, groups = input_529_groups_0, pad = input_529_pad_0, pad_type = input_529_pad_type_0, strides = input_529_strides_0, weight = model_key_encoder_xfpn_p5_1x1_weight_to_fp16, x = input_527_cast_fp16)[name = string("input_529_cast_fp16")];
            fp32 y_11_scale_factor_height_0 = const()[name = string("y_11_scale_factor_height_0"), val = fp32(2)];
            fp32 y_11_scale_factor_width_0 = const()[name = string("y_11_scale_factor_width_0"), val = fp32(2)];
            tensor<fp16, [1, 128, 32, 32]> y_11_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = y_11_scale_factor_height_0, scale_factor_width = y_11_scale_factor_width_0, x = input_529_cast_fp16)[name = string("y_11_cast_fp16")];
            string x_17_pad_type_0 = const()[name = string("x_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_17_strides_0 = const()[name = string("x_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_17_pad_0 = const()[name = string("x_17_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125440)))];
            tensor<int32, [2]> x_17_dilations_0 = const()[name = string("x_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_17_groups_0 = const()[name = string("x_17_groups_0"), val = int32(1)];
            tensor<fp16, [128, 256, 1, 1]> model_key_encoder_xfpn_p4_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125568))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158400))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158720)))];
            tensor<fp16, [1, 128, 32, 32]> x_17_cast_fp16 = conv(dilations = x_17_dilations_0, groups = x_17_groups_0, pad = x_17_pad_0, pad_type = x_17_pad_type_0, strides = x_17_strides_0, weight = model_key_encoder_xfpn_p4_1x1_weight_to_fp16, x = input_399_cast_fp16)[name = string("x_17_cast_fp16")];
            tensor<fp16, [1, 128, 32, 32]> input_531_cast_fp16 = add(x = x_17_cast_fp16, y = y_11_cast_fp16)[name = string("input_531_cast_fp16")];
            string input_631_pad_type_0 = const()[name = string("input_631_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_631_pad_0 = const()[name = string("input_631_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158912)))];
            int32 input_631_groups_0 = const()[name = string("input_631_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_631_strides_0 = const()[name = string("input_631_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_631_dilations_0 = const()[name = string("input_631_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> model_key_encoder_xfpn_fpn_output4_weight_to_fp16 = const()[name = string("model_key_encoder_xfpn_fpn_output4_weight_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2159040)))];
            tensor<fp16, [1, 128, 32, 32]> input_631_cast_fp16 = conv(dilations = input_631_dilations_0, groups = input_631_groups_0, pad = input_631_pad_0, pad_type = input_631_pad_type_0, strides = input_631_strides_0, weight = model_key_encoder_xfpn_fpn_output4_weight_to_fp16, x = input_531_cast_fp16)[name = string("input_631_cast_fp16")];
            string key_k_pad_type_0 = const()[name = string("key_k_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> key_k_pad_0 = const()[name = string("key_k_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2161408)))];
            tensor<int32, [2]> key_k_strides_0 = const()[name = string("key_k_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> key_k_dilations_0 = const()[name = string("key_k_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 key_k_groups_0 = const()[name = string("key_k_groups_0"), val = int32(1)];
            tensor<fp16, [64, 128, 3, 3]> model_key_proj_key_proj_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2161536))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235328))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235520)))];
            tensor<fp16, [64]> model_key_proj_key_proj_bias_to_fp16 = const()[name = string("model_key_proj_key_proj_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235648)))];
            tensor<fp16, [1, 64, 32, 32]> key_k_cast_fp16 = conv(bias = model_key_proj_key_proj_bias_to_fp16, dilations = key_k_dilations_0, groups = key_k_groups_0, pad = key_k_pad_0, pad_type = key_k_pad_type_0, strides = key_k_strides_0, weight = model_key_proj_key_proj_weight_to_fp16, x = input_631_cast_fp16)[name = string("key_k_cast_fp16")];
            int32 var_7769 = const()[name = string("op_7769"), val = int32(1)];
            string input_1279_pad_type_0 = const()[name = string("input_1279_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1279_strides_0 = const()[name = string("input_1279_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1279_pad_0 = const()[name = string("input_1279_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5013056)))];
            tensor<int32, [2]> input_1279_dilations_0 = const()[name = string("input_1279_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1279_groups_0 = const()[name = string("input_1279_groups_0"), val = int32(1)];
            tensor<fp16, [24, 24, 1, 1]> const_485_to_fp16 = const()[name = string("const_485_to_fp16"), val = tensor<fp16, [24, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5013184)))];
            tensor<fp16, [24]> const_486_to_fp16 = const()[name = string("const_486_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5014400)))];
            tensor<fp16, [1, 24, 128, 128]> input_1281_cast_fp16 = conv(bias = const_486_to_fp16, dilations = input_1279_dilations_0, groups = input_1279_groups_0, pad = input_1279_pad_0, pad_type = input_1279_pad_type_0, strides = input_1279_strides_0, weight = const_485_to_fp16, x = input_11_cast_fp16)[name = string("input_1281_cast_fp16")];
            tensor<fp16, [1, 24, 128, 128]> input_1945_cast_fp16 = relu(x = input_1281_cast_fp16)[name = string("input_1945_cast_fp16")];
            fp32 y_41_scale_factor_height_0 = const()[name = string("y_41_scale_factor_height_0"), val = fp32(2)];
            fp32 y_41_scale_factor_width_0 = const()[name = string("y_41_scale_factor_width_0"), val = fp32(2)];
            tensor<fp16, [1, 128, 64, 64]> y_41_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = y_41_scale_factor_height_0, scale_factor_width = y_41_scale_factor_width_0, x = input_531_cast_fp16)[name = string("y_41_cast_fp16")];
            string x_85_pad_type_0 = const()[name = string("x_85_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_85_strides_0 = const()[name = string("x_85_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_85_pad_0 = const()[name = string("x_85_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5014528)))];
            tensor<int32, [2]> x_85_dilations_0 = const()[name = string("x_85_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_85_groups_0 = const()[name = string("x_85_groups_0"), val = int32(1)];
            tensor<fp16, [128, 144, 1, 1]> model_key_encoder_xfpn_p3_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5014656))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5033152))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5033472)))];
            tensor<fp16, [1, 128, 64, 64]> x_85_cast_fp16 = conv(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 = model_key_encoder_xfpn_p3_1x1_weight_to_fp16, x = input_143_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1799_cast_fp16 = add(x = x_85_cast_fp16, y = y_41_cast_fp16)[name = string("input_1799_cast_fp16")];
            string input_1801_pad_type_0 = const()[name = string("input_1801_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1801_pad_0 = const()[name = string("input_1801_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5033664)))];
            int32 input_1801_groups_0 = const()[name = string("input_1801_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1801_strides_0 = const()[name = string("input_1801_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1801_dilations_0 = const()[name = string("input_1801_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> model_key_encoder_xfpn_fpn_output3_weight_to_fp16 = const()[name = string("model_key_encoder_xfpn_fpn_output3_weight_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5033792)))];
            tensor<fp16, [1, 128, 64, 64]> input_1801_cast_fp16 = conv(dilations = input_1801_dilations_0, groups = input_1801_groups_0, pad = input_1801_pad_0, pad_type = input_1801_pad_type_0, strides = input_1801_strides_0, weight = model_key_encoder_xfpn_fpn_output3_weight_to_fp16, x = input_1799_cast_fp16)[name = string("input_1801_cast_fp16")];
            string input_1803_pad_type_0 = const()[name = string("input_1803_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1803_strides_0 = const()[name = string("input_1803_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1803_pad_0 = const()[name = string("input_1803_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5036160)))];
            tensor<int32, [2]> input_1803_dilations_0 = const()[name = string("input_1803_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1803_groups_0 = const()[name = string("input_1803_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_679_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5036288))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5052736))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053056)))];
            tensor<fp16, [128]> const_680_to_fp16 = const()[name = string("const_680_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053248)))];
            tensor<fp16, [1, 128, 64, 64]> input_1805_cast_fp16 = conv(bias = const_680_to_fp16, dilations = input_1803_dilations_0, groups = input_1803_groups_0, pad = input_1803_pad_0, pad_type = input_1803_pad_type_0, strides = input_1803_strides_0, weight = const_679_to_fp16, x = input_1801_cast_fp16)[name = string("input_1805_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_87_cast_fp16 = relu(x = input_1805_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> var_11571_begin_0 = const()[name = string("op_11571_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053568)))];
            tensor<int32, [4]> var_11571_end_0 = const()[name = string("op_11571_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053696)))];
            tensor<bool, [4]> var_11571_end_mask_0 = const()[name = string("op_11571_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11571_cast_fp16 = slice_by_index(begin = var_11571_begin_0, end = var_11571_end_0, end_mask = var_11571_end_mask_0, x = x_87_cast_fp16)[name = string("op_11571_cast_fp16")];
            tensor<int32, [4]> var_11575_begin_0 = const()[name = string("op_11575_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053824)))];
            tensor<int32, [4]> var_11575_end_0 = const()[name = string("op_11575_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053952)))];
            tensor<bool, [4]> var_11575_end_mask_0 = const()[name = string("op_11575_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11575_cast_fp16 = slice_by_index(begin = var_11575_begin_0, end = var_11575_end_0, end_mask = var_11575_end_mask_0, x = x_87_cast_fp16)[name = string("op_11575_cast_fp16")];
            tensor<int32, [4]> var_11579_begin_0 = const()[name = string("op_11579_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054080)))];
            tensor<int32, [4]> var_11579_end_0 = const()[name = string("op_11579_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054208)))];
            tensor<bool, [4]> var_11579_end_mask_0 = const()[name = string("op_11579_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11579_cast_fp16 = slice_by_index(begin = var_11579_begin_0, end = var_11579_end_0, end_mask = var_11579_end_mask_0, x = x_87_cast_fp16)[name = string("op_11579_cast_fp16")];
            tensor<int32, [4]> var_11583_begin_0 = const()[name = string("op_11583_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054336)))];
            tensor<int32, [4]> var_11583_end_0 = const()[name = string("op_11583_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054464)))];
            tensor<bool, [4]> var_11583_end_mask_0 = const()[name = string("op_11583_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11583_cast_fp16 = slice_by_index(begin = var_11583_begin_0, end = var_11583_end_0, end_mask = var_11583_end_mask_0, x = x_87_cast_fp16)[name = string("op_11583_cast_fp16")];
            string input_1809_pad_type_0 = const()[name = string("input_1809_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1809_pad_0 = const()[name = string("input_1809_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054592)))];
            tensor<int32, [2]> input_1809_dilations_0 = const()[name = string("input_1809_dilations_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_1809_groups_0 = const()[name = string("input_1809_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1809_strides_0 = const()[name = string("input_1809_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_681_to_fp16 = const()[name = string("const_681_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054720)))];
            tensor<fp16, [32]> const_682_to_fp16 = const()[name = string("const_682_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5055360)))];
            tensor<fp16, [1, 32, 64, 64]> input_1811_cast_fp16 = conv(bias = const_682_to_fp16, dilations = input_1809_dilations_0, groups = input_1809_groups_0, pad = input_1809_pad_0, pad_type = input_1809_pad_type_0, strides = input_1809_strides_0, weight = const_681_to_fp16, x = var_11575_cast_fp16)[name = string("input_1811_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out1_57_cast_fp16 = relu(x = input_1811_cast_fp16)[name = string("out1_57_cast_fp16")];
            string input_1815_pad_type_0 = const()[name = string("input_1815_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1815_pad_0 = const()[name = string("input_1815_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5055488)))];
            tensor<int32, [2]> input_1815_dilations_0 = const()[name = string("input_1815_dilations_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_1815_groups_0 = const()[name = string("input_1815_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1815_strides_0 = const()[name = string("input_1815_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_683_to_fp16 = const()[name = string("const_683_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5055616)))];
            tensor<fp16, [32]> const_684_to_fp16 = const()[name = string("const_684_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5056256)))];
            tensor<fp16, [1, 32, 64, 64]> input_1817_cast_fp16 = conv(bias = const_684_to_fp16, dilations = input_1815_dilations_0, groups = input_1815_groups_0, pad = input_1815_pad_0, pad_type = input_1815_pad_type_0, strides = input_1815_strides_0, weight = const_683_to_fp16, x = var_11579_cast_fp16)[name = string("input_1817_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out2_57_cast_fp16 = relu(x = input_1817_cast_fp16)[name = string("out2_57_cast_fp16")];
            string input_1821_pad_type_0 = const()[name = string("input_1821_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1821_pad_0 = const()[name = string("input_1821_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5056384)))];
            tensor<int32, [2]> input_1821_dilations_0 = const()[name = string("input_1821_dilations_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_1821_groups_0 = const()[name = string("input_1821_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1821_strides_0 = const()[name = string("input_1821_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_685_to_fp16 = const()[name = string("const_685_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5056512)))];
            tensor<fp16, [32]> const_686_to_fp16 = const()[name = string("const_686_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5057152)))];
            tensor<fp16, [1, 32, 64, 64]> input_1823_cast_fp16 = conv(bias = const_686_to_fp16, dilations = input_1821_dilations_0, groups = input_1821_groups_0, pad = input_1821_pad_0, pad_type = input_1821_pad_type_0, strides = input_1821_strides_0, weight = const_685_to_fp16, x = var_11583_cast_fp16)[name = string("input_1823_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out3_57_cast_fp16 = relu(x = input_1823_cast_fp16)[name = string("out3_57_cast_fp16")];
            bool input_1825_interleave_0 = const()[name = string("input_1825_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 64, 64]> input_1825_cast_fp16 = concat(axis = var_7769, interleave = input_1825_interleave_0, values = (var_11571_cast_fp16, out1_57_cast_fp16, out2_57_cast_fp16, out3_57_cast_fp16))[name = string("input_1825_cast_fp16")];
            string input_1827_pad_type_0 = const()[name = string("input_1827_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1827_strides_0 = const()[name = string("input_1827_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1827_pad_0 = const()[name = string("input_1827_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5057280)))];
            tensor<int32, [2]> input_1827_dilations_0 = const()[name = string("input_1827_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1827_groups_0 = const()[name = string("input_1827_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_687_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5057408))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5073856))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5074176)))];
            tensor<fp16, [128]> const_688_to_fp16 = const()[name = string("const_688_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5074368)))];
            tensor<fp16, [1, 128, 64, 64]> input_1829_cast_fp16 = conv(bias = const_688_to_fp16, dilations = input_1827_dilations_0, groups = input_1827_groups_0, pad = input_1827_pad_0, pad_type = input_1827_pad_type_0, strides = input_1827_strides_0, weight = const_687_to_fp16, x = input_1825_cast_fp16)[name = string("input_1829_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_89_cast_fp16 = relu(x = input_1829_cast_fp16)[name = string("x_89_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1831_cast_fp16 = add(x = x_89_cast_fp16, y = input_1801_cast_fp16)[name = string("input_1831_cast_fp16")];
            string input_1833_pad_type_0 = const()[name = string("input_1833_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1833_strides_0 = const()[name = string("input_1833_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1833_pad_0 = const()[name = string("input_1833_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5074688)))];
            tensor<int32, [2]> input_1833_dilations_0 = const()[name = string("input_1833_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1833_groups_0 = const()[name = string("input_1833_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_689_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5074816))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5091264))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5091584)))];
            tensor<fp16, [128]> const_690_to_fp16 = const()[name = string("const_690_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5091776)))];
            tensor<fp16, [1, 128, 64, 64]> input_1835_cast_fp16 = conv(bias = const_690_to_fp16, dilations = input_1833_dilations_0, groups = input_1833_groups_0, pad = input_1833_pad_0, pad_type = input_1833_pad_type_0, strides = input_1833_strides_0, weight = const_689_to_fp16, x = input_1831_cast_fp16)[name = string("input_1835_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1837_cast_fp16 = relu(x = input_1835_cast_fp16)[name = string("input_1837_cast_fp16")];
            string input_1839_pad_type_0 = const()[name = string("input_1839_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1839_pad_0 = const()[name = string("input_1839_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5092096)))];
            tensor<int32, [2]> input_1839_dilations_0 = const()[name = string("input_1839_dilations_0"), val = tensor<int32, [2]>([4, 4])];
            int32 input_1839_groups_0 = const()[name = string("input_1839_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1839_strides_0 = const()[name = string("input_1839_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> const_691_to_fp16 = const()[name = string("const_691_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5092224)))];
            tensor<fp16, [128]> const_692_to_fp16 = const()[name = string("const_692_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5094592)))];
            tensor<fp16, [1, 128, 64, 64]> input_1841_cast_fp16 = conv(bias = const_692_to_fp16, dilations = input_1839_dilations_0, groups = input_1839_groups_0, pad = input_1839_pad_0, pad_type = input_1839_pad_type_0, strides = input_1839_strides_0, weight = const_691_to_fp16, x = input_1837_cast_fp16)[name = string("input_1841_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1843_cast_fp16 = relu(x = input_1841_cast_fp16)[name = string("input_1843_cast_fp16")];
            string input_1845_pad_type_0 = const()[name = string("input_1845_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1845_strides_0 = const()[name = string("input_1845_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1845_pad_0 = const()[name = string("input_1845_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5094912)))];
            tensor<int32, [2]> input_1845_dilations_0 = const()[name = string("input_1845_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1845_groups_0 = const()[name = string("input_1845_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_693_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5095040))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5111488))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5111808)))];
            tensor<fp16, [128]> const_694_to_fp16 = const()[name = string("const_694_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5112000)))];
            tensor<fp16, [1, 128, 64, 64]> input_1847_cast_fp16 = conv(bias = const_694_to_fp16, dilations = input_1845_dilations_0, groups = input_1845_groups_0, pad = input_1845_pad_0, pad_type = input_1845_pad_type_0, strides = input_1845_strides_0, weight = const_693_to_fp16, x = input_1843_cast_fp16)[name = string("input_1847_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_91_cast_fp16 = relu(x = input_1847_cast_fp16)[name = string("x_91_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1849_cast_fp16 = add(x = x_91_cast_fp16, y = input_1831_cast_fp16)[name = string("input_1849_cast_fp16")];
            string input_1851_pad_type_0 = const()[name = string("input_1851_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1851_strides_0 = const()[name = string("input_1851_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1851_pad_0 = const()[name = string("input_1851_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5112320)))];
            tensor<int32, [2]> input_1851_dilations_0 = const()[name = string("input_1851_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1851_groups_0 = const()[name = string("input_1851_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_695_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5112448))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5128896))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129216)))];
            tensor<fp16, [128]> const_696_to_fp16 = const()[name = string("const_696_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129408)))];
            tensor<fp16, [1, 128, 64, 64]> input_1853_cast_fp16 = conv(bias = const_696_to_fp16, dilations = input_1851_dilations_0, groups = input_1851_groups_0, pad = input_1851_pad_0, pad_type = input_1851_pad_type_0, strides = input_1851_strides_0, weight = const_695_to_fp16, x = input_1849_cast_fp16)[name = string("input_1853_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_93_cast_fp16 = relu(x = input_1853_cast_fp16)[name = string("x_93_cast_fp16")];
            tensor<int32, [4]> var_11730_begin_0 = const()[name = string("op_11730_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129728)))];
            tensor<int32, [4]> var_11730_end_0 = const()[name = string("op_11730_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129856)))];
            tensor<bool, [4]> var_11730_end_mask_0 = const()[name = string("op_11730_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11730_cast_fp16 = slice_by_index(begin = var_11730_begin_0, end = var_11730_end_0, end_mask = var_11730_end_mask_0, x = x_93_cast_fp16)[name = string("op_11730_cast_fp16")];
            tensor<int32, [4]> var_11734_begin_0 = const()[name = string("op_11734_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129984)))];
            tensor<int32, [4]> var_11734_end_0 = const()[name = string("op_11734_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130112)))];
            tensor<bool, [4]> var_11734_end_mask_0 = const()[name = string("op_11734_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11734_cast_fp16 = slice_by_index(begin = var_11734_begin_0, end = var_11734_end_0, end_mask = var_11734_end_mask_0, x = x_93_cast_fp16)[name = string("op_11734_cast_fp16")];
            tensor<int32, [4]> var_11738_begin_0 = const()[name = string("op_11738_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130240)))];
            tensor<int32, [4]> var_11738_end_0 = const()[name = string("op_11738_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130368)))];
            tensor<bool, [4]> var_11738_end_mask_0 = const()[name = string("op_11738_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11738_cast_fp16 = slice_by_index(begin = var_11738_begin_0, end = var_11738_end_0, end_mask = var_11738_end_mask_0, x = x_93_cast_fp16)[name = string("op_11738_cast_fp16")];
            tensor<int32, [4]> var_11742_begin_0 = const()[name = string("op_11742_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130496)))];
            tensor<int32, [4]> var_11742_end_0 = const()[name = string("op_11742_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130624)))];
            tensor<bool, [4]> var_11742_end_mask_0 = const()[name = string("op_11742_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11742_cast_fp16 = slice_by_index(begin = var_11742_begin_0, end = var_11742_end_0, end_mask = var_11742_end_mask_0, x = x_93_cast_fp16)[name = string("op_11742_cast_fp16")];
            string input_1857_pad_type_0 = const()[name = string("input_1857_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1857_pad_0 = const()[name = string("input_1857_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130752)))];
            tensor<int32, [2]> input_1857_dilations_0 = const()[name = string("input_1857_dilations_0"), val = tensor<int32, [2]>([6, 6])];
            int32 input_1857_groups_0 = const()[name = string("input_1857_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1857_strides_0 = const()[name = string("input_1857_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_697_to_fp16 = const()[name = string("const_697_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130880)))];
            tensor<fp16, [32]> const_698_to_fp16 = const()[name = string("const_698_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5131520)))];
            tensor<fp16, [1, 32, 64, 64]> input_1859_cast_fp16 = conv(bias = const_698_to_fp16, dilations = input_1857_dilations_0, groups = input_1857_groups_0, pad = input_1857_pad_0, pad_type = input_1857_pad_type_0, strides = input_1857_strides_0, weight = const_697_to_fp16, x = var_11734_cast_fp16)[name = string("input_1859_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out1_59_cast_fp16 = relu(x = input_1859_cast_fp16)[name = string("out1_59_cast_fp16")];
            string input_1863_pad_type_0 = const()[name = string("input_1863_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1863_pad_0 = const()[name = string("input_1863_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5131648)))];
            tensor<int32, [2]> input_1863_dilations_0 = const()[name = string("input_1863_dilations_0"), val = tensor<int32, [2]>([6, 6])];
            int32 input_1863_groups_0 = const()[name = string("input_1863_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1863_strides_0 = const()[name = string("input_1863_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_699_to_fp16 = const()[name = string("const_699_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5131776)))];
            tensor<fp16, [32]> const_700_to_fp16 = const()[name = string("const_700_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132416)))];
            tensor<fp16, [1, 32, 64, 64]> input_1865_cast_fp16 = conv(bias = const_700_to_fp16, dilations = input_1863_dilations_0, groups = input_1863_groups_0, pad = input_1863_pad_0, pad_type = input_1863_pad_type_0, strides = input_1863_strides_0, weight = const_699_to_fp16, x = var_11738_cast_fp16)[name = string("input_1865_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out2_59_cast_fp16 = relu(x = input_1865_cast_fp16)[name = string("out2_59_cast_fp16")];
            string input_1869_pad_type_0 = const()[name = string("input_1869_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1869_pad_0 = const()[name = string("input_1869_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132544)))];
            tensor<int32, [2]> input_1869_dilations_0 = const()[name = string("input_1869_dilations_0"), val = tensor<int32, [2]>([6, 6])];
            int32 input_1869_groups_0 = const()[name = string("input_1869_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1869_strides_0 = const()[name = string("input_1869_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_701_to_fp16 = const()[name = string("const_701_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132672)))];
            tensor<fp16, [32]> const_702_to_fp16 = const()[name = string("const_702_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133312)))];
            tensor<fp16, [1, 32, 64, 64]> input_1871_cast_fp16 = conv(bias = const_702_to_fp16, dilations = input_1869_dilations_0, groups = input_1869_groups_0, pad = input_1869_pad_0, pad_type = input_1869_pad_type_0, strides = input_1869_strides_0, weight = const_701_to_fp16, x = var_11742_cast_fp16)[name = string("input_1871_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out3_59_cast_fp16 = relu(x = input_1871_cast_fp16)[name = string("out3_59_cast_fp16")];
            bool input_1873_interleave_0 = const()[name = string("input_1873_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 64, 64]> input_1873_cast_fp16 = concat(axis = var_7769, interleave = input_1873_interleave_0, values = (var_11730_cast_fp16, out1_59_cast_fp16, out2_59_cast_fp16, out3_59_cast_fp16))[name = string("input_1873_cast_fp16")];
            string input_1875_pad_type_0 = const()[name = string("input_1875_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1875_strides_0 = const()[name = string("input_1875_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1875_pad_0 = const()[name = string("input_1875_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133440)))];
            tensor<int32, [2]> input_1875_dilations_0 = const()[name = string("input_1875_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1875_groups_0 = const()[name = string("input_1875_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_703_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133568))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150016))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150336)))];
            tensor<fp16, [128]> const_704_to_fp16 = const()[name = string("const_704_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150528)))];
            tensor<fp16, [1, 128, 64, 64]> input_1877_cast_fp16 = conv(bias = const_704_to_fp16, dilations = input_1875_dilations_0, groups = input_1875_groups_0, pad = input_1875_pad_0, pad_type = input_1875_pad_type_0, strides = input_1875_strides_0, weight = const_703_to_fp16, x = input_1873_cast_fp16)[name = string("input_1877_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_95_cast_fp16 = relu(x = input_1877_cast_fp16)[name = string("x_95_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1879_cast_fp16 = add(x = x_95_cast_fp16, y = input_1849_cast_fp16)[name = string("input_1879_cast_fp16")];
            string input_1881_pad_type_0 = const()[name = string("input_1881_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1881_strides_0 = const()[name = string("input_1881_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1881_pad_0 = const()[name = string("input_1881_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150848)))];
            tensor<int32, [2]> input_1881_dilations_0 = const()[name = string("input_1881_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1881_groups_0 = const()[name = string("input_1881_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_705_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150976))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5167424))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5167744)))];
            tensor<fp16, [128]> const_706_to_fp16 = const()[name = string("const_706_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5167936)))];
            tensor<fp16, [1, 128, 64, 64]> input_1883_cast_fp16 = conv(bias = const_706_to_fp16, dilations = input_1881_dilations_0, groups = input_1881_groups_0, pad = input_1881_pad_0, pad_type = input_1881_pad_type_0, strides = input_1881_strides_0, weight = const_705_to_fp16, x = input_1879_cast_fp16)[name = string("input_1883_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1885_cast_fp16 = relu(x = input_1883_cast_fp16)[name = string("input_1885_cast_fp16")];
            string input_1887_pad_type_0 = const()[name = string("input_1887_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1887_pad_0 = const()[name = string("input_1887_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5168256)))];
            tensor<int32, [2]> input_1887_dilations_0 = const()[name = string("input_1887_dilations_0"), val = tensor<int32, [2]>([6, 6])];
            int32 input_1887_groups_0 = const()[name = string("input_1887_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1887_strides_0 = const()[name = string("input_1887_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> const_707_to_fp16 = const()[name = string("const_707_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5168384)))];
            tensor<fp16, [128]> const_708_to_fp16 = const()[name = string("const_708_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5170752)))];
            tensor<fp16, [1, 128, 64, 64]> input_1889_cast_fp16 = conv(bias = const_708_to_fp16, dilations = input_1887_dilations_0, groups = input_1887_groups_0, pad = input_1887_pad_0, pad_type = input_1887_pad_type_0, strides = input_1887_strides_0, weight = const_707_to_fp16, x = input_1885_cast_fp16)[name = string("input_1889_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1891_cast_fp16 = relu(x = input_1889_cast_fp16)[name = string("input_1891_cast_fp16")];
            string input_1893_pad_type_0 = const()[name = string("input_1893_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1893_strides_0 = const()[name = string("input_1893_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1893_pad_0 = const()[name = string("input_1893_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5171072)))];
            tensor<int32, [2]> input_1893_dilations_0 = const()[name = string("input_1893_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1893_groups_0 = const()[name = string("input_1893_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_709_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5171200))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5187648))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5187968)))];
            tensor<fp16, [128]> const_710_to_fp16 = const()[name = string("const_710_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5188160)))];
            tensor<fp16, [1, 128, 64, 64]> input_1895_cast_fp16 = conv(bias = const_710_to_fp16, dilations = input_1893_dilations_0, groups = input_1893_groups_0, pad = input_1893_pad_0, pad_type = input_1893_pad_type_0, strides = input_1893_strides_0, weight = const_709_to_fp16, x = input_1891_cast_fp16)[name = string("input_1895_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_97_cast_fp16 = relu(x = input_1895_cast_fp16)[name = string("x_97_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1933_cast_fp16 = add(x = x_97_cast_fp16, y = input_1879_cast_fp16)[name = string("input_1933_cast_fp16")];
            tensor<int32, [4]> a_sq_1_perm_0 = const()[name = string("a_sq_1_perm_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5188480)))];
            tensor<fp16, [1, 64, 1, 2048]> a_sq_1_cast_fp16 = transpose(perm = a_sq_1_perm_0, x = prev_key)[name = string("transpose_2")];
            tensor<fp16, [1, 64, 1, 2048]> input_1899_cast_fp16 = mul(x = a_sq_1_cast_fp16, y = a_sq_1_cast_fp16)[name = string("input_1899_cast_fp16")];
            string a_sq_3_pad_type_0 = const()[name = string("a_sq_3_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> a_sq_3_strides_0 = const()[name = string("a_sq_3_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> a_sq_3_pad_0 = const()[name = string("a_sq_3_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5188608)))];
            tensor<int32, [2]> a_sq_3_dilations_0 = const()[name = string("a_sq_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 a_sq_3_groups_0 = const()[name = string("a_sq_3_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 64, 1, 1]> model_memory_op_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [1024, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5188736))), scale = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5254336))), zero_point = tensor<int8, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5256448)))];
            tensor<fp16, [1, 1024, 1, 2048]> a_sq_3_cast_fp16 = conv(dilations = a_sq_3_dilations_0, groups = a_sq_3_groups_0, pad = a_sq_3_pad_0, pad_type = a_sq_3_pad_type_0, strides = a_sq_3_strides_0, weight = model_memory_op_conv_weight_to_fp16, x = input_1899_cast_fp16)[name = string("a_sq_3_cast_fp16")];
            tensor<int32, [4]> a_sq_5_perm_0 = const()[name = string("a_sq_5_perm_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5257536)))];
            tensor<int32, [4]> var_11916 = const()[name = string("op_11916"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5257664)))];
            tensor<fp16, [1, 64, 1, 1024]> var_11917_cast_fp16 = reshape(shape = var_11916, x = key_k_cast_fp16)[name = string("op_11917_cast_fp16")];
            string p_1_equation_0 = const()[name = string("p_1_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 2048, 1, 1024]> p_1_cast_fp16 = einsum(equation = p_1_equation_0, values = (prev_key, var_11917_cast_fp16))[name = string("p_1_cast_fp16")];
            fp16 var_11922_promoted_to_fp16 = const()[name = string("op_11922_promoted_to_fp16"), val = fp16(2)];
            tensor<fp16, [1, 2048, 1, 1024]> var_11923_cast_fp16 = mul(x = p_1_cast_fp16, y = var_11922_promoted_to_fp16)[name = string("op_11923_cast_fp16")];
            tensor<fp16, [1, 2048, 1, 1024]> a_sq_5_cast_fp16 = transpose(perm = a_sq_5_perm_0, x = a_sq_3_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 1, 1024]> var_11925_cast_fp16 = sub(x = var_11923_cast_fp16, y = a_sq_5_cast_fp16)[name = string("op_11925_cast_fp16")];
            fp16 _inversed_affinity_1_y_0_to_fp16 = const()[name = string("_inversed_affinity_1_y_0_to_fp16"), val = fp16(0.125)];
            tensor<fp16, [1, 2048, 1, 1024]> _inversed_affinity_1_cast_fp16 = mul(x = var_11925_cast_fp16, y = _inversed_affinity_1_y_0_to_fp16)[name = string("_inversed_affinity_1_cast_fp16")];
            tensor<int32, [4]> affinity0_1_begin_0 = const()[name = string("affinity0_1_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5257792)))];
            tensor<int32, [4]> affinity0_1_end_0 = const()[name = string("affinity0_1_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5257920)))];
            tensor<bool, [4]> affinity0_1_end_mask_0 = const()[name = string("affinity0_1_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 1024, 1, 1024]> affinity0_1_cast_fp16 = slice_by_index(begin = affinity0_1_begin_0, end = affinity0_1_end_0, end_mask = affinity0_1_end_mask_0, x = _inversed_affinity_1_cast_fp16)[name = string("affinity0_1_cast_fp16")];
            tensor<int32, [4]> affinity1_1_begin_0 = const()[name = string("affinity1_1_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258048)))];
            tensor<int32, [4]> affinity1_1_end_0 = const()[name = string("affinity1_1_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258176)))];
            tensor<bool, [4]> affinity1_1_end_mask_0 = const()[name = string("affinity1_1_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 1024, 1, 1024]> affinity1_1_cast_fp16 = slice_by_index(begin = affinity1_1_begin_0, end = affinity1_1_end_0, end_mask = affinity1_1_end_mask_0, x = _inversed_affinity_1_cast_fp16)[name = string("affinity1_1_cast_fp16")];
            fp16 var_11953_to_fp16 = const()[name = string("op_11953_to_fp16"), val = fp16(0.5)];
            tensor<fp16, [1, 1024, 1, 1024]> var_11954_cast_fp16 = sub(x = affinity1_1_cast_fp16, y = var_11953_to_fp16)[name = string("op_11954_cast_fp16")];
            int32 var_11956 = const()[name = string("op_11956"), val = int32(1)];
            bool input_1901_interleave_0 = const()[name = string("input_1901_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 2048, 1, 1024]> input_1901_cast_fp16 = concat(axis = var_11956, interleave = input_1901_interleave_0, values = (affinity0_1_cast_fp16, var_11954_cast_fp16))[name = string("input_1901_cast_fp16")];
            int32 var_11958 = const()[name = string("op_11958"), val = int32(1)];
            tensor<fp16, [1, 2048, 1, 1024]> var_11960_cast_fp16 = softmax(axis = var_11958, x = input_1901_cast_fp16)[name = string("op_11960_cast_fp16")];
            string mem_1_equation_0 = const()[name = string("mem_1_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 128, 1, 1024]> mem_1_cast_fp16 = einsum(equation = mem_1_equation_0, values = (prev_value, var_11960_cast_fp16))[name = string("mem_1_cast_fp16")];
            tensor<int32, [4]> var_11965 = const()[name = string("op_11965"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258304)))];
            tensor<fp16, [1, 128, 32, 32]> mem_3_cast_fp16 = reshape(shape = var_11965, x = mem_1_cast_fp16)[name = string("mem_3_cast_fp16")];
            int32 var_11968 = const()[name = string("op_11968"), val = int32(1)];
            bool x_99_interleave_0 = const()[name = string("x_99_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> x_99_cast_fp16 = concat(axis = var_11968, interleave = x_99_interleave_0, values = (input_631_cast_fp16, mem_3_cast_fp16))[name = string("x_99_cast_fp16")];
            int32 var_11976 = const()[name = string("op_11976"), val = int32(1)];
            bool var_11980 = const()[name = string("op_11980"), val = bool(true)];
            bool input_1903_interleave_0 = const()[name = string("input_1903_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 32, 32]> input_1903_cast_fp16 = concat(axis = var_11976, interleave = input_1903_interleave_0, values = (x_99_cast_fp16, hidden_state))[name = string("input_1903_cast_fp16")];
            tensor<fp16, [1, 320, 32, 32]> input_1905_cast_fp16 = relu(x = input_1903_cast_fp16)[name = string("input_1905_cast_fp16")];
            string input_1907_pad_type_0 = const()[name = string("input_1907_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1907_pad_0 = const()[name = string("input_1907_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258432)))];
            tensor<int32, [2]> input_1907_strides_0 = const()[name = string("input_1907_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1907_dilations_0 = const()[name = string("input_1907_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1907_groups_0 = const()[name = string("input_1907_groups_0"), val = int32(1)];
            tensor<fp16, [64, 320, 3, 3]> model_decoder_fuser_block1_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 320, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258560))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5442944))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5443136)))];
            tensor<fp16, [64]> model_decoder_fuser_block1_conv1_bias_to_fp16 = const()[name = string("model_decoder_fuser_block1_conv1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5443264)))];
            tensor<fp16, [1, 64, 32, 32]> input_1907_cast_fp16 = conv(bias = model_decoder_fuser_block1_conv1_bias_to_fp16, dilations = input_1907_dilations_0, groups = input_1907_groups_0, pad = input_1907_pad_0, pad_type = input_1907_pad_type_0, strides = input_1907_strides_0, weight = model_decoder_fuser_block1_conv1_weight_to_fp16, x = input_1905_cast_fp16)[name = string("input_1907_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1909_cast_fp16 = relu(x = input_1907_cast_fp16)[name = string("input_1909_cast_fp16")];
            string y_43_pad_type_0 = const()[name = string("y_43_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_43_pad_0 = const()[name = string("y_43_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5443456)))];
            tensor<int32, [2]> y_43_strides_0 = const()[name = string("y_43_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_43_dilations_0 = const()[name = string("y_43_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_43_groups_0 = const()[name = string("y_43_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_fuser_block1_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5443584))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480512))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480704)))];
            tensor<fp16, [64]> model_decoder_fuser_block1_conv2_bias_to_fp16 = const()[name = string("model_decoder_fuser_block1_conv2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480832)))];
            tensor<fp16, [1, 64, 32, 32]> y_43_cast_fp16 = conv(bias = model_decoder_fuser_block1_conv2_bias_to_fp16, dilations = y_43_dilations_0, groups = y_43_groups_0, pad = y_43_pad_0, pad_type = y_43_pad_type_0, strides = y_43_strides_0, weight = model_decoder_fuser_block1_conv2_weight_to_fp16, x = input_1909_cast_fp16)[name = string("y_43_cast_fp16")];
            string x_101_pad_type_0 = const()[name = string("x_101_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_101_pad_0 = const()[name = string("x_101_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5481024)))];
            tensor<int32, [2]> x_101_strides_0 = const()[name = string("x_101_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_101_dilations_0 = const()[name = string("x_101_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_101_groups_0 = const()[name = string("x_101_groups_0"), val = int32(1)];
            tensor<fp16, [64, 320, 3, 3]> model_decoder_fuser_block1_downsample_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 320, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5481152))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5665536))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5665728)))];
            tensor<fp16, [64]> model_decoder_fuser_block1_downsample_bias_to_fp16 = const()[name = string("model_decoder_fuser_block1_downsample_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5665856)))];
            tensor<fp16, [1, 64, 32, 32]> x_101_cast_fp16 = conv(bias = model_decoder_fuser_block1_downsample_bias_to_fp16, dilations = x_101_dilations_0, groups = x_101_groups_0, pad = x_101_pad_0, pad_type = x_101_pad_type_0, strides = x_101_strides_0, weight = model_decoder_fuser_block1_downsample_weight_to_fp16, x = input_1903_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> x_103_cast_fp16 = add(x = x_101_cast_fp16, y = y_43_cast_fp16)[name = string("x_103_cast_fp16")];
            tensor<int32, [2]> var_12029 = const()[name = string("op_12029"), val = tensor<int32, [2]>([32, 32])];
            tensor<int32, [2]> var_12030 = const()[name = string("op_12030"), val = tensor<int32, [2]>([32, 32])];
            string input_1911_pad_type_0 = const()[name = string("input_1911_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1911_pad_0 = const()[name = string("input_1911_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5666048)))];
            bool input_1911_exclude_padding_from_average_0 = const()[name = string("input_1911_exclude_padding_from_average_0"), val = bool(false)];
            bool input_1911_ceil_mode_0 = const()[name = string("input_1911_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 64, 1, 1]> input_1911_cast_fp16 = avg_pool(ceil_mode = input_1911_ceil_mode_0, exclude_padding_from_average = input_1911_exclude_padding_from_average_0, kernel_sizes = var_12029, pad = input_1911_pad_0, pad_type = input_1911_pad_type_0, strides = var_12030, x = x_103_cast_fp16)[name = string("input_1911_cast_fp16")];
            string input_1913_pad_type_0 = const()[name = string("input_1913_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1913_strides_0 = const()[name = string("input_1913_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1913_pad_0 = const()[name = string("input_1913_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5666176)))];
            tensor<int32, [2]> input_1913_dilations_0 = const()[name = string("input_1913_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1913_groups_0 = const()[name = string("input_1913_groups_0"), val = int32(1)];
            tensor<fp16, [4, 64, 1, 1]> model_decoder_fuser_attention_ChannelGate_mlp_1_weight_to_fp16 = const()[name = string("model_decoder_fuser_attention_ChannelGate_mlp_1_weight_to_fp16"), val = tensor<fp16, [4, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5666304)))];
            tensor<fp16, [4]> model_decoder_fuser_attention_ChannelGate_mlp_1_bias_to_fp16 = const()[name = string("model_decoder_fuser_attention_ChannelGate_mlp_1_bias_to_fp16"), val = tensor<fp16, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5666880)))];
            tensor<fp16, [1, 4, 1, 1]> input_1913_cast_fp16 = conv(bias = model_decoder_fuser_attention_ChannelGate_mlp_1_bias_to_fp16, dilations = input_1913_dilations_0, groups = input_1913_groups_0, pad = input_1913_pad_0, pad_type = input_1913_pad_type_0, strides = input_1913_strides_0, weight = model_decoder_fuser_attention_ChannelGate_mlp_1_weight_to_fp16, x = input_1911_cast_fp16)[name = string("input_1913_cast_fp16")];
            tensor<fp16, [1, 4, 1, 1]> input_1915_cast_fp16 = relu(x = input_1913_cast_fp16)[name = string("input_1915_cast_fp16")];
            string x_105_pad_type_0 = const()[name = string("x_105_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_105_strides_0 = const()[name = string("x_105_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_105_pad_0 = const()[name = string("x_105_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5667008)))];
            tensor<int32, [2]> x_105_dilations_0 = const()[name = string("x_105_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_105_groups_0 = const()[name = string("x_105_groups_0"), val = int32(1)];
            tensor<fp16, [64, 4, 1, 1]> model_decoder_fuser_attention_ChannelGate_mlp_3_weight_to_fp16 = const()[name = string("model_decoder_fuser_attention_ChannelGate_mlp_3_weight_to_fp16"), val = tensor<fp16, [64, 4, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5667136)))];
            tensor<fp16, [64]> model_decoder_fuser_attention_ChannelGate_mlp_3_bias_to_fp16 = const()[name = string("model_decoder_fuser_attention_ChannelGate_mlp_3_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5667712)))];
            tensor<fp16, [1, 64, 1, 1]> x_105_cast_fp16 = conv(bias = model_decoder_fuser_attention_ChannelGate_mlp_3_bias_to_fp16, dilations = x_105_dilations_0, groups = x_105_groups_0, pad = x_105_pad_0, pad_type = x_105_pad_type_0, strides = x_105_strides_0, weight = model_decoder_fuser_attention_ChannelGate_mlp_3_weight_to_fp16, x = input_1915_cast_fp16)[name = string("x_105_cast_fp16")];
            tensor<int32, [2]> var_12054 = const()[name = string("op_12054"), val = tensor<int32, [2]>([32, 32])];
            tensor<int32, [2]> var_12055 = const()[name = string("op_12055"), val = tensor<int32, [2]>([32, 32])];
            string input_1917_pad_type_0 = const()[name = string("input_1917_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1917_pad_0 = const()[name = string("input_1917_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5667904)))];
            bool input_1917_ceil_mode_0 = const()[name = string("input_1917_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 64, 1, 1]> input_1917_cast_fp16 = max_pool(ceil_mode = input_1917_ceil_mode_0, kernel_sizes = var_12054, pad = input_1917_pad_0, pad_type = input_1917_pad_type_0, strides = var_12055, x = x_103_cast_fp16)[name = string("input_1917_cast_fp16")];
            string input_1919_pad_type_0 = const()[name = string("input_1919_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1919_strides_0 = const()[name = string("input_1919_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1919_pad_0 = const()[name = string("input_1919_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668032)))];
            tensor<int32, [2]> input_1919_dilations_0 = const()[name = string("input_1919_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1919_groups_0 = const()[name = string("input_1919_groups_0"), val = int32(1)];
            tensor<fp16, [1, 4, 1, 1]> input_1919_cast_fp16 = conv(bias = model_decoder_fuser_attention_ChannelGate_mlp_1_bias_to_fp16, dilations = input_1919_dilations_0, groups = input_1919_groups_0, pad = input_1919_pad_0, pad_type = input_1919_pad_type_0, strides = input_1919_strides_0, weight = model_decoder_fuser_attention_ChannelGate_mlp_1_weight_to_fp16, x = input_1917_cast_fp16)[name = string("input_1919_cast_fp16")];
            tensor<fp16, [1, 4, 1, 1]> input_1921_cast_fp16 = relu(x = input_1919_cast_fp16)[name = string("input_1921_cast_fp16")];
            string y_45_pad_type_0 = const()[name = string("y_45_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> y_45_strides_0 = const()[name = string("y_45_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> y_45_pad_0 = const()[name = string("y_45_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668160)))];
            tensor<int32, [2]> y_45_dilations_0 = const()[name = string("y_45_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_45_groups_0 = const()[name = string("y_45_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1, 1]> y_45_cast_fp16 = conv(bias = model_decoder_fuser_attention_ChannelGate_mlp_3_bias_to_fp16, dilations = y_45_dilations_0, groups = y_45_groups_0, pad = y_45_pad_0, pad_type = y_45_pad_type_0, strides = y_45_strides_0, weight = model_decoder_fuser_attention_ChannelGate_mlp_3_weight_to_fp16, x = input_1921_cast_fp16)[name = string("y_45_cast_fp16")];
            tensor<fp16, [1, 64, 1, 1]> channel_att_sum_1_cast_fp16 = add(x = x_105_cast_fp16, y = y_45_cast_fp16)[name = string("channel_att_sum_1_cast_fp16")];
            tensor<fp16, [1, 64, 1, 1]> y_47_cast_fp16 = sigmoid(x = channel_att_sum_1_cast_fp16)[name = string("y_47_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> x_107_cast_fp16 = mul(x = x_103_cast_fp16, y = y_47_cast_fp16)[name = string("x_107_cast_fp16")];
            tensor<int32, [1]> reduce_max_0_axes_0 = const()[name = string("reduce_max_0_axes_0"), val = tensor<int32, [1]>([1])];
            bool reduce_max_0_keep_dims_0 = const()[name = string("reduce_max_0_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 1, 32, 32]> reduce_max_0_cast_fp16 = reduce_max(axes = reduce_max_0_axes_0, keep_dims = reduce_max_0_keep_dims_0, x = x_107_cast_fp16)[name = string("reduce_max_0_cast_fp16")];
            tensor<int32, [1]> var_12083_axes_0 = const()[name = string("op_12083_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1, 32, 32]> var_12083_cast_fp16 = reduce_mean(axes = var_12083_axes_0, keep_dims = var_11980, x = x_107_cast_fp16)[name = string("op_12083_cast_fp16")];
            bool input_1923_interleave_0 = const()[name = string("input_1923_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 2, 32, 32]> input_1923_cast_fp16 = concat(axis = var_11976, interleave = input_1923_interleave_0, values = (reduce_max_0_cast_fp16, var_12083_cast_fp16))[name = string("input_1923_cast_fp16")];
            string x_out_1_pad_type_0 = const()[name = string("x_out_1_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_out_1_pad_0 = const()[name = string("x_out_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668288)))];
            tensor<int32, [2]> x_out_1_strides_0 = const()[name = string("x_out_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_out_1_dilations_0 = const()[name = string("x_out_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_out_1_groups_0 = const()[name = string("x_out_1_groups_0"), val = int32(1)];
            tensor<fp16, [1, 2, 7, 7]> model_decoder_fuser_attention_SpatialGate_spatial_conv_weight_to_fp16 = const()[name = string("model_decoder_fuser_attention_SpatialGate_spatial_conv_weight_to_fp16"), val = tensor<fp16, [1, 2, 7, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668416)))];
            tensor<fp16, [1]> model_decoder_fuser_attention_SpatialGate_spatial_conv_bias_to_fp16 = const()[name = string("model_decoder_fuser_attention_SpatialGate_spatial_conv_bias_to_fp16"), val = tensor<fp16, [1]>([0.212158203])];
            tensor<fp16, [1, 1, 32, 32]> x_out_1_cast_fp16 = conv(bias = model_decoder_fuser_attention_SpatialGate_spatial_conv_bias_to_fp16, dilations = x_out_1_dilations_0, groups = x_out_1_groups_0, pad = x_out_1_pad_0, pad_type = x_out_1_pad_type_0, strides = x_out_1_strides_0, weight = model_decoder_fuser_attention_SpatialGate_spatial_conv_weight_to_fp16, x = input_1923_cast_fp16)[name = string("x_out_1_cast_fp16")];
            tensor<fp16, [1, 1, 32, 32]> y_49_cast_fp16 = sigmoid(x = x_out_1_cast_fp16)[name = string("y_49_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> y_51_cast_fp16 = mul(x = x_107_cast_fp16, y = y_49_cast_fp16)[name = string("y_51_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1925_cast_fp16 = add(x = x_103_cast_fp16, y = y_51_cast_fp16)[name = string("input_1925_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1927_cast_fp16 = relu(x = input_1925_cast_fp16)[name = string("input_1927_cast_fp16")];
            string input_1929_pad_type_0 = const()[name = string("input_1929_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1929_pad_0 = const()[name = string("input_1929_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668736)))];
            tensor<int32, [2]> input_1929_strides_0 = const()[name = string("input_1929_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1929_dilations_0 = const()[name = string("input_1929_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1929_groups_0 = const()[name = string("input_1929_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_fuser_block2_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668864))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5705792))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5705984)))];
            tensor<fp16, [64]> model_decoder_fuser_block2_conv1_bias_to_fp16 = const()[name = string("model_decoder_fuser_block2_conv1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5706112)))];
            tensor<fp16, [1, 64, 32, 32]> input_1929_cast_fp16 = conv(bias = model_decoder_fuser_block2_conv1_bias_to_fp16, dilations = input_1929_dilations_0, groups = input_1929_groups_0, pad = input_1929_pad_0, pad_type = input_1929_pad_type_0, strides = input_1929_strides_0, weight = model_decoder_fuser_block2_conv1_weight_to_fp16, x = input_1927_cast_fp16)[name = string("input_1929_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1931_cast_fp16 = relu(x = input_1929_cast_fp16)[name = string("input_1931_cast_fp16")];
            string y_53_pad_type_0 = const()[name = string("y_53_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_53_pad_0 = const()[name = string("y_53_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5706304)))];
            tensor<int32, [2]> y_53_strides_0 = const()[name = string("y_53_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_53_dilations_0 = const()[name = string("y_53_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_53_groups_0 = const()[name = string("y_53_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_fuser_block2_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5706432))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5743360))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5743552)))];
            tensor<fp16, [64]> model_decoder_fuser_block2_conv2_bias_to_fp16 = const()[name = string("model_decoder_fuser_block2_conv2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5743680)))];
            tensor<fp16, [1, 64, 32, 32]> y_53_cast_fp16 = conv(bias = model_decoder_fuser_block2_conv2_bias_to_fp16, dilations = y_53_dilations_0, groups = y_53_groups_0, pad = y_53_pad_0, pad_type = y_53_pad_type_0, strides = y_53_strides_0, weight = model_decoder_fuser_block2_conv2_weight_to_fp16, x = input_1931_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1935_cast_fp16 = add(x = input_1925_cast_fp16, y = y_53_cast_fp16)[name = string("input_1935_cast_fp16")];
            string x_109_pad_type_0 = const()[name = string("x_109_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_109_pad_0 = const()[name = string("x_109_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5743872)))];
            tensor<int32, [2]> x_109_strides_0 = const()[name = string("x_109_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_109_dilations_0 = const()[name = string("x_109_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_109_groups_0 = const()[name = string("x_109_groups_0"), val = int32(1)];
            tensor<fp16, [64, 128, 3, 3]> model_decoder_up_16_8_skip_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5744000))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817792))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817984)))];
            tensor<fp16, [64]> model_decoder_up_16_8_skip_conv_bias_to_fp16 = const()[name = string("model_decoder_up_16_8_skip_conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5818112)))];
            tensor<fp16, [1, 64, 64, 64]> x_109_cast_fp16 = conv(bias = model_decoder_up_16_8_skip_conv_bias_to_fp16, dilations = x_109_dilations_0, groups = x_109_groups_0, pad = x_109_pad_0, pad_type = x_109_pad_type_0, strides = x_109_strides_0, weight = model_decoder_up_16_8_skip_conv_weight_to_fp16, x = input_1933_cast_fp16)[name = string("x_109_cast_fp16")];
            fp32 y_55_scale_factor_height_0 = const()[name = string("y_55_scale_factor_height_0"), val = fp32(2)];
            fp32 y_55_scale_factor_width_0 = const()[name = string("y_55_scale_factor_width_0"), val = fp32(2)];
            bool y_55_align_corners_0 = const()[name = string("y_55_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 64, 64]> y_55_cast_fp16 = upsample_bilinear(align_corners = y_55_align_corners_0, scale_factor_height = y_55_scale_factor_height_0, scale_factor_width = y_55_scale_factor_width_0, x = input_1935_cast_fp16)[name = string("y_55_cast_fp16")];
            tensor<fp16, [1, 64, 64, 64]> input_1937_cast_fp16 = add(x = x_109_cast_fp16, y = y_55_cast_fp16)[name = string("input_1937_cast_fp16")];
            tensor<fp16, [1, 64, 64, 64]> input_1939_cast_fp16 = relu(x = input_1937_cast_fp16)[name = string("input_1939_cast_fp16")];
            string input_1941_pad_type_0 = const()[name = string("input_1941_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1941_pad_0 = const()[name = string("input_1941_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5818304)))];
            tensor<int32, [2]> input_1941_strides_0 = const()[name = string("input_1941_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1941_dilations_0 = const()[name = string("input_1941_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1941_groups_0 = const()[name = string("input_1941_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_up_16_8_out_conv_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5818432))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5855360))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5855552)))];
            tensor<fp16, [64]> model_decoder_up_16_8_out_conv_conv1_bias_to_fp16 = const()[name = string("model_decoder_up_16_8_out_conv_conv1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5855680)))];
            tensor<fp16, [1, 64, 64, 64]> input_1941_cast_fp16 = conv(bias = model_decoder_up_16_8_out_conv_conv1_bias_to_fp16, dilations = input_1941_dilations_0, groups = input_1941_groups_0, pad = input_1941_pad_0, pad_type = input_1941_pad_type_0, strides = input_1941_strides_0, weight = model_decoder_up_16_8_out_conv_conv1_weight_to_fp16, x = input_1939_cast_fp16)[name = string("input_1941_cast_fp16")];
            tensor<fp16, [1, 64, 64, 64]> input_1943_cast_fp16 = relu(x = input_1941_cast_fp16)[name = string("input_1943_cast_fp16")];
            string y_57_pad_type_0 = const()[name = string("y_57_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_57_pad_0 = const()[name = string("y_57_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5855872)))];
            tensor<int32, [2]> y_57_strides_0 = const()[name = string("y_57_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_57_dilations_0 = const()[name = string("y_57_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_57_groups_0 = const()[name = string("y_57_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_up_16_8_out_conv_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5856000))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5892928))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5893120)))];
            tensor<fp16, [64]> model_decoder_up_16_8_out_conv_conv2_bias_to_fp16 = const()[name = string("model_decoder_up_16_8_out_conv_conv2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5893248)))];
            tensor<fp16, [1, 64, 64, 64]> y_57_cast_fp16 = conv(bias = model_decoder_up_16_8_out_conv_conv2_bias_to_fp16, dilations = y_57_dilations_0, groups = y_57_groups_0, pad = y_57_pad_0, pad_type = y_57_pad_type_0, strides = y_57_strides_0, weight = model_decoder_up_16_8_out_conv_conv2_weight_to_fp16, x = input_1943_cast_fp16)[name = string("y_57_cast_fp16")];
            tensor<fp16, [1, 64, 64, 64]> x_111_cast_fp16 = add(x = input_1937_cast_fp16, y = y_57_cast_fp16)[name = string("x_111_cast_fp16")];
            fp16 var_11974_to_fp16 = const()[name = string("op_11974_to_fp16"), val = fp16(-2000)];
            fp16 var_11975_to_fp16 = const()[name = string("op_11975_to_fp16"), val = fp16(2000)];
            tensor<fp16, [1, 64, 64, 64]> input_1947_cast_fp16 = clip(alpha = var_11974_to_fp16, beta = var_11975_to_fp16, x = x_111_cast_fp16)[name = string("input_1947_cast_fp16")];
            string x_113_pad_type_0 = const()[name = string("x_113_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_113_pad_0 = const()[name = string("x_113_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5893440)))];
            tensor<int32, [2]> x_113_strides_0 = const()[name = string("x_113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_113_dilations_0 = const()[name = string("x_113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_113_groups_0 = const()[name = string("x_113_groups_0"), val = int32(1)];
            tensor<fp16, [64, 24, 3, 3]> model_decoder_up_8_4_skip_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5893568))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5907456))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5907648)))];
            tensor<fp16, [64]> model_decoder_up_8_4_skip_conv_bias_to_fp16 = const()[name = string("model_decoder_up_8_4_skip_conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5907776)))];
            tensor<fp16, [1, 64, 128, 128]> x_113_cast_fp16 = conv(bias = model_decoder_up_8_4_skip_conv_bias_to_fp16, dilations = x_113_dilations_0, groups = x_113_groups_0, pad = x_113_pad_0, pad_type = x_113_pad_type_0, strides = x_113_strides_0, weight = model_decoder_up_8_4_skip_conv_weight_to_fp16, x = input_1945_cast_fp16)[name = string("x_113_cast_fp16")];
            fp32 y_59_scale_factor_height_0 = const()[name = string("y_59_scale_factor_height_0"), val = fp32(2)];
            fp32 y_59_scale_factor_width_0 = const()[name = string("y_59_scale_factor_width_0"), val = fp32(2)];
            bool y_59_align_corners_0 = const()[name = string("y_59_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 128, 128]> y_59_cast_fp16 = upsample_bilinear(align_corners = y_59_align_corners_0, scale_factor_height = y_59_scale_factor_height_0, scale_factor_width = y_59_scale_factor_width_0, x = input_1947_cast_fp16)[name = string("y_59_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> input_1949_cast_fp16 = add(x = x_113_cast_fp16, y = y_59_cast_fp16)[name = string("input_1949_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> input_1951_cast_fp16 = relu(x = input_1949_cast_fp16)[name = string("input_1951_cast_fp16")];
            string input_1953_pad_type_0 = const()[name = string("input_1953_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1953_pad_0 = const()[name = string("input_1953_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5907968)))];
            tensor<int32, [2]> input_1953_strides_0 = const()[name = string("input_1953_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1953_dilations_0 = const()[name = string("input_1953_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1953_groups_0 = const()[name = string("input_1953_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_up_8_4_out_conv_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5908096))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945024))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945216)))];
            tensor<fp16, [64]> model_decoder_up_8_4_out_conv_conv1_bias_to_fp16 = const()[name = string("model_decoder_up_8_4_out_conv_conv1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945344)))];
            tensor<fp16, [1, 64, 128, 128]> input_1953_cast_fp16 = conv(bias = model_decoder_up_8_4_out_conv_conv1_bias_to_fp16, dilations = input_1953_dilations_0, groups = input_1953_groups_0, pad = input_1953_pad_0, pad_type = input_1953_pad_type_0, strides = input_1953_strides_0, weight = model_decoder_up_8_4_out_conv_conv1_weight_to_fp16, x = input_1951_cast_fp16)[name = string("input_1953_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> input_1955_cast_fp16 = relu(x = input_1953_cast_fp16)[name = string("input_1955_cast_fp16")];
            string y_61_pad_type_0 = const()[name = string("y_61_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_61_pad_0 = const()[name = string("y_61_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945536)))];
            tensor<int32, [2]> y_61_strides_0 = const()[name = string("y_61_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_61_dilations_0 = const()[name = string("y_61_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_61_groups_0 = const()[name = string("y_61_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_up_8_4_out_conv_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945664))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5982592))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5982784)))];
            tensor<fp16, [64]> model_decoder_up_8_4_out_conv_conv2_bias_to_fp16 = const()[name = string("model_decoder_up_8_4_out_conv_conv2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5982912)))];
            tensor<fp16, [1, 64, 128, 128]> y_61_cast_fp16 = conv(bias = model_decoder_up_8_4_out_conv_conv2_bias_to_fp16, dilations = y_61_dilations_0, groups = y_61_groups_0, pad = y_61_pad_0, pad_type = y_61_pad_type_0, strides = y_61_strides_0, weight = model_decoder_up_8_4_out_conv_conv2_weight_to_fp16, x = input_1955_cast_fp16)[name = string("y_61_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> x_115_cast_fp16 = add(x = input_1949_cast_fp16, y = y_61_cast_fp16)[name = string("x_115_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> input_1957_cast_fp16 = clip(alpha = var_11974_to_fp16, beta = var_11975_to_fp16, x = x_115_cast_fp16)[name = string("input_1957_cast_fp16")];
            string x_117_pad_type_0 = const()[name = string("x_117_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_117_pad_0 = const()[name = string("x_117_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5983104)))];
            tensor<int32, [2]> x_117_strides_0 = const()[name = string("x_117_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_117_dilations_0 = const()[name = string("x_117_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_117_groups_0 = const()[name = string("x_117_groups_0"), val = int32(1)];
            tensor<fp16, [16, 24, 3, 3]> model_decoder_up_4_2_skip_conv_weight_to_fp16 = const()[name = string("model_decoder_up_4_2_skip_conv_weight_to_fp16"), val = tensor<fp16, [16, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5983232)))];
            tensor<fp16, [16]> model_decoder_up_4_2_skip_conv_bias_to_fp16 = const()[name = string("model_decoder_up_4_2_skip_conv_bias_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5990208)))];
            tensor<fp16, [1, 16, 256, 256]> x_117_cast_fp16 = conv(bias = model_decoder_up_4_2_skip_conv_bias_to_fp16, dilations = x_117_dilations_0, groups = x_117_groups_0, pad = x_117_pad_0, pad_type = x_117_pad_type_0, strides = x_117_strides_0, weight = model_decoder_up_4_2_skip_conv_weight_to_fp16, x = input_9_cast_fp16)[name = string("x_117_cast_fp16")];
            string input_1959_pad_type_0 = const()[name = string("input_1959_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1959_strides_0 = const()[name = string("input_1959_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1959_pad_0 = const()[name = string("input_1959_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5990336)))];
            tensor<int32, [2]> input_1959_dilations_0 = const()[name = string("input_1959_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1959_groups_0 = const()[name = string("input_1959_groups_0"), val = int32(1)];
            tensor<fp16, [16, 64, 1, 1]> model_decoder_up_4_2_reduce_channel_weight_to_fp16 = const()[name = string("model_decoder_up_4_2_reduce_channel_weight_to_fp16"), val = tensor<fp16, [16, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5990464)))];
            tensor<fp16, [16]> model_decoder_up_4_2_reduce_channel_bias_to_fp16 = const()[name = string("model_decoder_up_4_2_reduce_channel_bias_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5992576)))];
            tensor<fp16, [1, 16, 128, 128]> input_1959_cast_fp16 = conv(bias = model_decoder_up_4_2_reduce_channel_bias_to_fp16, dilations = input_1959_dilations_0, groups = input_1959_groups_0, pad = input_1959_pad_0, pad_type = input_1959_pad_type_0, strides = input_1959_strides_0, weight = model_decoder_up_4_2_reduce_channel_weight_to_fp16, x = input_1957_cast_fp16)[name = string("input_1959_cast_fp16")];
            fp32 var_12198_scale_factor_height_0 = const()[name = string("op_12198_scale_factor_height_0"), val = fp32(2)];
            fp32 var_12198_scale_factor_width_0 = const()[name = string("op_12198_scale_factor_width_0"), val = fp32(2)];
            bool var_12198_align_corners_0 = const()[name = string("op_12198_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 16, 256, 256]> var_12198_cast_fp16 = upsample_bilinear(align_corners = var_12198_align_corners_0, scale_factor_height = var_12198_scale_factor_height_0, scale_factor_width = var_12198_scale_factor_width_0, x = input_1959_cast_fp16)[name = string("op_12198_cast_fp16")];
            bool input_1961_interleave_0 = const()[name = string("input_1961_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 32, 256, 256]> input_1961_cast_fp16 = concat(axis = var_11976, interleave = input_1961_interleave_0, values = (x_117_cast_fp16, var_12198_cast_fp16))[name = string("input_1961_cast_fp16")];
            tensor<fp16, [1, 32, 256, 256]> input_1963_cast_fp16 = relu(x = input_1961_cast_fp16)[name = string("input_1963_cast_fp16")];
            string input_1965_pad_type_0 = const()[name = string("input_1965_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1965_pad_0 = const()[name = string("input_1965_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5992704)))];
            tensor<int32, [2]> input_1965_strides_0 = const()[name = string("input_1965_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1965_dilations_0 = const()[name = string("input_1965_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1965_groups_0 = const()[name = string("input_1965_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3, 3]> model_decoder_up_4_2_out_conv_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [32, 32, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5992832))), scale = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002112))), zero_point = tensor<int8, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002240)))];
            tensor<fp16, [32]> model_decoder_up_4_2_out_conv_conv1_bias_to_fp16 = const()[name = string("model_decoder_up_4_2_out_conv_conv1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002368)))];
            tensor<fp16, [1, 32, 256, 256]> input_1965_cast_fp16 = conv(bias = model_decoder_up_4_2_out_conv_conv1_bias_to_fp16, dilations = input_1965_dilations_0, groups = input_1965_groups_0, pad = input_1965_pad_0, pad_type = input_1965_pad_type_0, strides = input_1965_strides_0, weight = model_decoder_up_4_2_out_conv_conv1_weight_to_fp16, x = input_1963_cast_fp16)[name = string("input_1965_cast_fp16")];
            tensor<fp16, [1, 32, 256, 256]> input_1967_cast_fp16 = relu(x = input_1965_cast_fp16)[name = string("input_1967_cast_fp16")];
            string y_63_pad_type_0 = const()[name = string("y_63_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_63_pad_0 = const()[name = string("y_63_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002496)))];
            tensor<int32, [2]> y_63_strides_0 = const()[name = string("y_63_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_63_dilations_0 = const()[name = string("y_63_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_63_groups_0 = const()[name = string("y_63_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3, 3]> model_decoder_up_4_2_out_conv_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [32, 32, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002624))), scale = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6011904))), zero_point = tensor<int8, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6012032)))];
            tensor<fp16, [32]> model_decoder_up_4_2_out_conv_conv2_bias_to_fp16 = const()[name = string("model_decoder_up_4_2_out_conv_conv2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6012160)))];
            tensor<fp16, [1, 32, 256, 256]> y_63_cast_fp16 = conv(bias = model_decoder_up_4_2_out_conv_conv2_bias_to_fp16, dilations = y_63_dilations_0, groups = y_63_groups_0, pad = y_63_pad_0, pad_type = y_63_pad_type_0, strides = y_63_strides_0, weight = model_decoder_up_4_2_out_conv_conv2_weight_to_fp16, x = input_1967_cast_fp16)[name = string("y_63_cast_fp16")];
            tensor<fp16, [1, 32, 256, 256]> input_1969_cast_fp16 = add(x = input_1961_cast_fp16, y = y_63_cast_fp16)[name = string("input_1969_cast_fp16")];
            tensor<fp16, [1, 32, 256, 256]> input_1971_cast_fp16 = relu(x = input_1969_cast_fp16)[name = string("input_1971_cast_fp16")];
            string logits_1_pad_type_0 = const()[name = string("logits_1_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> logits_1_pad_0 = const()[name = string("logits_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6012288)))];
            tensor<int32, [2]> logits_1_strides_0 = const()[name = string("logits_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> logits_1_dilations_0 = const()[name = string("logits_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 logits_1_groups_0 = const()[name = string("logits_1_groups_0"), val = int32(1)];
            tensor<fp16, [1, 32, 3, 3]> model_decoder_pred_weight_to_fp16 = const()[name = string("model_decoder_pred_weight_to_fp16"), val = tensor<fp16, [1, 32, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6012416)))];
            tensor<fp16, [1]> model_decoder_pred_bias_to_fp16 = const()[name = string("model_decoder_pred_bias_to_fp16"), val = tensor<fp16, [1]>([-0.10168457])];
            tensor<fp16, [1, 1, 256, 256]> logits_1_cast_fp16 = conv(bias = model_decoder_pred_bias_to_fp16, dilations = logits_1_dilations_0, groups = logits_1_groups_0, pad = logits_1_pad_0, pad_type = logits_1_pad_type_0, strides = logits_1_strides_0, weight = model_decoder_pred_weight_to_fp16, x = input_1971_cast_fp16)[name = string("logits_1_cast_fp16")];
            string g_1_pad_type_0 = const()[name = string("g_1_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> g_1_strides_0 = const()[name = string("g_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> g_1_pad_0 = const()[name = string("g_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6013056)))];
            tensor<int32, [2]> g_1_dilations_0 = const()[name = string("g_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 g_1_groups_0 = const()[name = string("g_1_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> model_decoder_quality_pred_g16_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6013184))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017344))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017536)))];
            tensor<fp16, [64]> model_decoder_quality_pred_g16_conv_bias_to_fp16 = const()[name = string("model_decoder_quality_pred_g16_conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017664)))];
            tensor<fp16, [1, 64, 32, 32]> g_1_cast_fp16 = conv(bias = model_decoder_quality_pred_g16_conv_bias_to_fp16, dilations = g_1_dilations_0, groups = g_1_groups_0, pad = g_1_pad_0, pad_type = g_1_pad_type_0, strides = g_1_strides_0, weight = model_decoder_quality_pred_g16_conv_weight_to_fp16, x = input_1935_cast_fp16)[name = string("g_1_cast_fp16")];
            tensor<int32, [2]> var_12239 = const()[name = string("op_12239"), val = tensor<int32, [2]>([32, 32])];
            tensor<int32, [2]> var_12240 = const()[name = string("op_12240"), val = tensor<int32, [2]>([32, 32])];
            string input_1973_pad_type_0 = const()[name = string("input_1973_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1973_pad_0 = const()[name = string("input_1973_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017856)))];
            bool input_1973_ceil_mode_0 = const()[name = string("input_1973_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 64, 1, 1]> input_1973_cast_fp16 = max_pool(ceil_mode = input_1973_ceil_mode_0, kernel_sizes = var_12239, pad = input_1973_pad_0, pad_type = input_1973_pad_type_0, strides = var_12240, x = g_1_cast_fp16)[name = string("input_1973_cast_fp16")];
            string qualitys_1_pad_type_0 = const()[name = string("qualitys_1_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> qualitys_1_strides_0 = const()[name = string("qualitys_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> qualitys_1_pad_0 = const()[name = string("qualitys_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017984)))];
            tensor<int32, [2]> qualitys_1_dilations_0 = const()[name = string("qualitys_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 qualitys_1_groups_0 = const()[name = string("qualitys_1_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1, 1]> model_decoder_quality_pred_transform_weight_to_fp16 = const()[name = string("model_decoder_quality_pred_transform_weight_to_fp16"), val = tensor<fp16, [1, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6018112)))];
            tensor<fp16, [1]> model_decoder_quality_pred_transform_bias_to_fp16 = const()[name = string("model_decoder_quality_pred_transform_bias_to_fp16"), val = tensor<fp16, [1]>([0.0545654297])];
            tensor<fp16, [1, 1, 1, 1]> qualitys_1_cast_fp16 = conv(bias = model_decoder_quality_pred_transform_bias_to_fp16, dilations = qualitys_1_dilations_0, groups = qualitys_1_groups_0, pad = qualitys_1_pad_0, pad_type = qualitys_1_pad_type_0, strides = qualitys_1_strides_0, weight = model_decoder_quality_pred_transform_weight_to_fp16, x = input_1973_cast_fp16)[name = string("qualitys_1_cast_fp16")];
            string x_119_pad_type_0 = const()[name = string("x_119_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_119_strides_0 = const()[name = string("x_119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_119_pad_0 = const()[name = string("x_119_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6018304)))];
            tensor<int32, [2]> x_119_dilations_0 = const()[name = string("x_119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_119_groups_0 = const()[name = string("x_119_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> model_decoder_hidden_update_g16_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6018432))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6022592))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6022784)))];
            tensor<fp16, [64]> model_decoder_hidden_update_g16_conv_bias_to_fp16 = const()[name = string("model_decoder_hidden_update_g16_conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6022912)))];
            tensor<fp16, [1, 64, 32, 32]> x_119_cast_fp16 = conv(bias = model_decoder_hidden_update_g16_conv_bias_to_fp16, dilations = x_119_dilations_0, groups = x_119_groups_0, pad = x_119_pad_0, pad_type = x_119_pad_type_0, strides = x_119_strides_0, weight = model_decoder_hidden_update_g16_conv_weight_to_fp16, x = input_1935_cast_fp16)[name = string("x_119_cast_fp16")];
            tensor<int32, [2]> var_12261 = const()[name = string("op_12261"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_12262 = const()[name = string("op_12262"), val = tensor<int32, [2]>([2, 2])];
            string input_1975_pad_type_0 = const()[name = string("input_1975_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1975_pad_0 = const()[name = string("input_1975_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6023104)))];
            bool input_1975_exclude_padding_from_average_0 = const()[name = string("input_1975_exclude_padding_from_average_0"), val = bool(false)];
            bool input_1975_ceil_mode_0 = const()[name = string("input_1975_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 64, 32, 32]> input_1975_cast_fp16 = avg_pool(ceil_mode = input_1975_ceil_mode_0, exclude_padding_from_average = input_1975_exclude_padding_from_average_0, kernel_sizes = var_12261, pad = input_1975_pad_0, pad_type = input_1975_pad_type_0, strides = var_12262, x = input_1947_cast_fp16)[name = string("input_1975_cast_fp16")];
            string y_65_pad_type_0 = const()[name = string("y_65_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> y_65_strides_0 = const()[name = string("y_65_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> y_65_pad_0 = const()[name = string("y_65_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6023232)))];
            tensor<int32, [2]> y_65_dilations_0 = const()[name = string("y_65_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_65_groups_0 = const()[name = string("y_65_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> model_decoder_hidden_update_g8_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6023360))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6027520))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6027712)))];
            tensor<fp16, [64]> model_decoder_hidden_update_g8_conv_bias_to_fp16 = const()[name = string("model_decoder_hidden_update_g8_conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6027840)))];
            tensor<fp16, [1, 64, 32, 32]> y_65_cast_fp16 = conv(bias = model_decoder_hidden_update_g8_conv_bias_to_fp16, dilations = y_65_dilations_0, groups = y_65_groups_0, pad = y_65_pad_0, pad_type = y_65_pad_type_0, strides = y_65_strides_0, weight = model_decoder_hidden_update_g8_conv_weight_to_fp16, x = input_1975_cast_fp16)[name = string("y_65_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> g_3_cast_fp16 = add(x = x_119_cast_fp16, y = y_65_cast_fp16)[name = string("g_3_cast_fp16")];
            bool input_1977_interleave_0 = const()[name = string("input_1977_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 32, 32]> input_1977_cast_fp16 = concat(axis = var_11976, interleave = input_1977_interleave_0, values = (g_3_cast_fp16, hidden_state))[name = string("input_1977_cast_fp16")];
            string values_3_pad_type_0 = const()[name = string("values_3_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> values_3_pad_0 = const()[name = string("values_3_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6028032)))];
            tensor<int32, [2]> values_3_strides_0 = const()[name = string("values_3_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> values_3_dilations_0 = const()[name = string("values_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 values_3_groups_0 = const()[name = string("values_3_groups_0"), val = int32(1)];
            tensor<fp16, [192, 128, 3, 3]> model_decoder_hidden_update_transform_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [192, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6028160))), scale = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6249408))), zero_point = tensor<int8, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6249856)))];
            tensor<fp16, [192]> model_decoder_hidden_update_transform_bias_to_fp16 = const()[name = string("model_decoder_hidden_update_transform_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6250112)))];
            tensor<fp16, [1, 192, 32, 32]> values_3_cast_fp16 = conv(bias = model_decoder_hidden_update_transform_bias_to_fp16, dilations = values_3_dilations_0, groups = values_3_groups_0, pad = values_3_pad_0, pad_type = values_3_pad_type_0, strides = values_3_strides_0, weight = model_decoder_hidden_update_transform_weight_to_fp16, x = input_1977_cast_fp16)[name = string("values_3_cast_fp16")];
            tensor<int32, [4]> var_12283_begin_0 = const()[name = string("op_12283_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6250560)))];
            tensor<int32, [4]> var_12283_end_0 = const()[name = string("op_12283_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6250688)))];
            tensor<bool, [4]> var_12283_end_mask_0 = const()[name = string("op_12283_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_12283_cast_fp16 = slice_by_index(begin = var_12283_begin_0, end = var_12283_end_0, end_mask = var_12283_end_mask_0, x = values_3_cast_fp16)[name = string("op_12283_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> x_125_cast_fp16 = sigmoid(x = var_12283_cast_fp16)[name = string("x_125_cast_fp16")];
            tensor<int32, [4]> var_12286_begin_0 = const()[name = string("op_12286_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6250816)))];
            tensor<int32, [4]> var_12286_end_0 = const()[name = string("op_12286_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6250944)))];
            tensor<bool, [4]> var_12286_end_mask_0 = const()[name = string("op_12286_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_12286_cast_fp16 = slice_by_index(begin = var_12286_begin_0, end = var_12286_end_0, end_mask = var_12286_end_mask_0, x = values_3_cast_fp16)[name = string("op_12286_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> x_121_cast_fp16 = sigmoid(x = var_12286_cast_fp16)[name = string("x_121_cast_fp16")];
            tensor<int32, [4]> var_12289_begin_0 = const()[name = string("op_12289_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6251072)))];
            tensor<int32, [4]> var_12289_end_0 = const()[name = string("op_12289_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6251200)))];
            tensor<bool, [4]> var_12289_end_mask_0 = const()[name = string("op_12289_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_12289_cast_fp16 = slice_by_index(begin = var_12289_begin_0, end = var_12289_end_0, end_mask = var_12289_end_mask_0, x = values_3_cast_fp16)[name = string("op_12289_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> y_71_cast_fp16 = tanh(x = var_12289_cast_fp16)[name = string("y_71_cast_fp16")];
            fp16 var_12291_promoted_to_fp16 = const()[name = string("op_12291_promoted_to_fp16"), val = fp16(-1)];
            tensor<fp16, [1, 64, 32, 32]> x_123_cast_fp16 = mul(x = x_121_cast_fp16, y = var_12291_promoted_to_fp16)[name = string("x_123_cast_fp16")];
            fp16 var_12293_promoted_to_fp16 = const()[name = string("op_12293_promoted_to_fp16"), val = fp16(1)];
            tensor<fp16, [1, 64, 32, 32]> y_67_cast_fp16 = add(x = x_123_cast_fp16, y = var_12293_promoted_to_fp16)[name = string("y_67_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> y_69_cast_fp16 = mul(x = hidden_state, y = y_67_cast_fp16)[name = string("y_69_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> x_127_cast_fp16 = mul(x = x_125_cast_fp16, y = y_69_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> y_73_cast_fp16 = mul(x = x_121_cast_fp16, y = y_71_cast_fp16)[name = string("y_73_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> regular_h = add(x = x_127_cast_fp16, y = y_73_cast_fp16)[name = string("op_12298_cast_fp16")];
            fp32 logits_3_scale_factor_height_0 = const()[name = string("logits_3_scale_factor_height_0"), val = fp32(2)];
            fp32 logits_3_scale_factor_width_0 = const()[name = string("logits_3_scale_factor_width_0"), val = fp32(2)];
            bool logits_3_align_corners_0 = const()[name = string("logits_3_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 1, 512, 512]> logits_3_cast_fp16 = upsample_bilinear(align_corners = logits_3_align_corners_0, scale_factor_height = logits_3_scale_factor_height_0, scale_factor_width = logits_3_scale_factor_width_0, x = logits_1_cast_fp16)[name = string("logits_3_cast_fp16")];
            tensor<fp16, [1, 1, 1, 1]> regular_q = sigmoid(x = qualitys_1_cast_fp16)[name = string("op_12305_cast_fp16")];
            fp16 var_12306_to_fp16 = const()[name = string("op_12306_to_fp16"), val = fp16(2)];
            tensor<fp16, [1, 1, 512, 512]> var_12307_cast_fp16 = mul(x = logits_3_cast_fp16, y = var_12306_to_fp16)[name = string("op_12307_cast_fp16")];
            tensor<fp16, [1, 1, 512, 512]> regular_prob = sigmoid(x = var_12307_cast_fp16)[name = string("op_12308_cast_fp16")];
        } -> (regular_h, regular_prob, regular_q);
    func updateFrame<ios18>(tensor<fp16, [1, 64, 32, 32]> hidden_state, pixel_buffer<FMT_32BGRA, shape=[512, 512]> input_image, tensor<fp16, [1, 1, 512, 512]> mask, tensor<fp16, [1, 2048, 1, 64]> prev_key, tensor<fp16, [1, 128, 1, 2048]> prev_value) [E5_FlagsEir = dict<string, string>({{"allowSoftmaxApproximation", "1"}, {"early_arch_extended_reshape", "1"}, {"experimental.ane.early_arch_transposes", "1"}, {"experimental.ane.enable_rsqrt", "1"}, {"experimental.ane.reduce_mean_spatial", "1"}, {"experimental.aot.enable_surface_desc", "1"}})] {
            tensor<fp16, [1, 3, 1, 1]> var_47_to_fp16 = const()[name = string("op_47_to_fp16"), val = tensor<fp16, [1, 3, 1, 1]>([[[[123.6875]], [[116.25]], [[103.5]]]])];
            tensor<uint8, [4, 512, 512]> images_tensor_bgra_uint8 = pixel_buffer_to_tensor(input = input_image);
            tensor<fp16, [4, 512, 512]> images_tensor_bgra_fp16 = cast(dtype = string("fp16"), x = images_tensor_bgra_uint8);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_b = slice_by_index(begin = tensor<int32, [3]>([0, 0, 0]), end = tensor<int32, [3]>([1, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_g = slice_by_index(begin = tensor<int32, [3]>([1, 0, 0]), end = tensor<int32, [3]>([2, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [1, 512, 512]> images_tensor_slice_r = slice_by_index(begin = tensor<int32, [3]>([2, 0, 0]), end = tensor<int32, [3]>([3, 0, 0]), end_mask = tensor<bool, [3]>([false, true, true]), x = images_tensor_bgra_fp16);
            tensor<fp16, [3, 512, 512]> images_tensor_rgb_fp16 = concat(axis = int32(0), interleave = bool(false), values = (images_tensor_slice_r, images_tensor_slice_g, images_tensor_slice_b));
            tensor<fp16, [1, 3, 512, 512]> images_tensor_tensor = expand_dims(axes = tensor<int32, [1]>([0]), x = images_tensor_rgb_fp16);
            tensor<fp16, [1, 3, 512, 512]> tensor_5_cast_fp16 = sub(x = images_tensor_tensor, y = var_47_to_fp16)[name = string("tensor_5_cast_fp16")];
            tensor<fp16, [1, 3, 1, 1]> _inversed_input_1_y_0_to_fp16 = const()[name = string("_inversed_input_1_y_0_to_fp16"), val = tensor<fp16, [1, 3, 1, 1]>([[[[0.0171203613]], [[0.0175018311]], [[0.0174255371]]]])];
            tensor<fp16, [1, 3, 512, 512]> _inversed_input_1_cast_fp16 = mul(x = tensor_5_cast_fp16, y = _inversed_input_1_y_0_to_fp16)[name = string("_inversed_input_1_cast_fp16")];
            int32 var_86 = const()[name = string("op_86"), val = int32(1)];
            tensor<int32, [8]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [8]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("constant")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0)];
            tensor<fp16, [1, 3, 513, 513]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = _inversed_input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<int32, [2]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [24, 3, 3, 3]> const_95_to_fp16 = const()[name = string("const_95_to_fp16"), val = tensor<fp16, [24, 3, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [24]> const_96_to_fp16 = const()[name = string("const_96_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1728)))];
            tensor<fp16, [1, 24, 256, 256]> input_7_cast_fp16 = conv(bias = const_96_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = const_95_to_fp16, x = input_3_cast_fp16)[name = string("input_7_cast_fp16")];
            tensor<fp16, [1, 24, 256, 256]> input_9_cast_fp16 = relu(x = input_7_cast_fp16)[name = string("input_9_cast_fp16")];
            tensor<int32, [2]> var_2890 = const()[name = string("op_2890"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_2891 = const()[name = string("op_2891"), val = tensor<int32, [2]>([2, 2])];
            string input_11_pad_type_0 = const()[name = string("input_11_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_11_pad_0 = const()[name = string("input_11_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1856)))];
            bool input_11_ceil_mode_0 = const()[name = string("input_11_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 24, 128, 128]> input_11_cast_fp16 = max_pool(ceil_mode = input_11_ceil_mode_0, kernel_sizes = var_2890, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = var_2891, x = input_9_cast_fp16)[name = string("input_11_cast_fp16")];
            string input_17_pad_type_0 = const()[name = string("input_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_17_strides_0 = const()[name = string("input_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1984)))];
            tensor<int32, [2]> input_17_dilations_0 = const()[name = string("input_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_17_groups_0 = const()[name = string("input_17_groups_0"), val = int32(1)];
            tensor<fp16, [144, 24, 1, 1]> const_97_to_fp16 = const()[name = string("const_97_to_fp16"), val = tensor<fp16, [144, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2112)))];
            tensor<fp16, [144]> const_98_to_fp16 = const()[name = string("const_98_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9088)))];
            tensor<fp16, [1, 144, 128, 128]> input_19_cast_fp16 = conv(bias = const_98_to_fp16, dilations = input_17_dilations_0, groups = input_17_groups_0, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = input_17_strides_0, weight = const_97_to_fp16, x = input_11_cast_fp16)[name = string("input_19_cast_fp16")];
            tensor<fp16, [1, 144, 128, 128]> input_21_cast_fp16 = relu(x = input_19_cast_fp16)[name = string("input_21_cast_fp16")];
            string input_23_pad_type_0 = const()[name = string("input_23_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9472)))];
            tensor<int32, [2]> input_23_strides_0 = const()[name = string("input_23_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_23_groups_0 = const()[name = string("input_23_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_23_dilations_0 = const()[name = string("input_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [144, 1, 5, 5]> const_99_to_fp16 = const()[name = string("const_99_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9600)))];
            tensor<fp16, [144]> const_100_to_fp16 = const()[name = string("const_100_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16896)))];
            tensor<fp16, [1, 144, 64, 64]> input_25_cast_fp16 = conv(bias = const_100_to_fp16, dilations = input_23_dilations_0, groups = input_23_groups_0, pad = input_23_pad_0, pad_type = input_23_pad_type_0, strides = input_23_strides_0, weight = const_99_to_fp16, x = input_21_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_27_cast_fp16 = relu(x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_29_pad_type_0 = const()[name = string("input_29_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_29_strides_0 = const()[name = string("input_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_29_pad_0 = const()[name = string("input_29_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17280)))];
            tensor<int32, [2]> input_29_dilations_0 = const()[name = string("input_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_29_groups_0 = const()[name = string("input_29_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_101_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17408))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38208))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38592)))];
            tensor<fp16, [144]> const_102_to_fp16 = const()[name = string("const_102_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38848)))];
            tensor<fp16, [1, 144, 64, 64]> x_1_cast_fp16 = conv(bias = const_102_to_fp16, dilations = input_29_dilations_0, groups = input_29_groups_0, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = input_29_strides_0, weight = const_101_to_fp16, x = input_27_cast_fp16)[name = string("x_1_cast_fp16")];
            tensor<int32, [4]> var_2929_begin_0 = const()[name = string("op_2929_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39232)))];
            tensor<int32, [4]> var_2929_end_0 = const()[name = string("op_2929_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39360)))];
            tensor<bool, [4]> var_2929_end_mask_0 = const()[name = string("op_2929_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2929_cast_fp16 = slice_by_index(begin = var_2929_begin_0, end = var_2929_end_0, end_mask = var_2929_end_mask_0, x = x_1_cast_fp16)[name = string("op_2929_cast_fp16")];
            tensor<int32, [4]> var_2933_begin_0 = const()[name = string("op_2933_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39488)))];
            tensor<int32, [4]> var_2933_end_0 = const()[name = string("op_2933_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39616)))];
            tensor<bool, [4]> var_2933_end_mask_0 = const()[name = string("op_2933_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2933_cast_fp16 = slice_by_index(begin = var_2933_begin_0, end = var_2933_end_0, end_mask = var_2933_end_mask_0, x = x_1_cast_fp16)[name = string("op_2933_cast_fp16")];
            tensor<int32, [4]> var_2937_begin_0 = const()[name = string("op_2937_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39744)))];
            tensor<int32, [4]> var_2937_end_0 = const()[name = string("op_2937_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39872)))];
            tensor<bool, [4]> var_2937_end_mask_0 = const()[name = string("op_2937_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2937_cast_fp16 = slice_by_index(begin = var_2937_begin_0, end = var_2937_end_0, end_mask = var_2937_end_mask_0, x = x_1_cast_fp16)[name = string("op_2937_cast_fp16")];
            tensor<int32, [4]> var_2941_begin_0 = const()[name = string("op_2941_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40000)))];
            tensor<int32, [4]> var_2941_end_0 = const()[name = string("op_2941_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40128)))];
            tensor<bool, [4]> var_2941_end_mask_0 = const()[name = string("op_2941_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_2941_cast_fp16 = slice_by_index(begin = var_2941_begin_0, end = var_2941_end_0, end_mask = var_2941_end_mask_0, x = x_1_cast_fp16)[name = string("op_2941_cast_fp16")];
            string input_33_pad_type_0 = const()[name = string("input_33_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_33_strides_0 = const()[name = string("input_33_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40256)))];
            tensor<int32, [2]> input_33_dilations_0 = const()[name = string("input_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_33_groups_0 = const()[name = string("input_33_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_103_to_fp16 = const()[name = string("const_103_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40384)))];
            tensor<fp16, [36]> const_104_to_fp16 = const()[name = string("const_104_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43072)))];
            tensor<fp16, [1, 36, 64, 64]> input_35_cast_fp16 = conv(bias = const_104_to_fp16, dilations = input_33_dilations_0, groups = input_33_groups_0, pad = input_33_pad_0, pad_type = input_33_pad_type_0, strides = input_33_strides_0, weight = const_103_to_fp16, x = var_2933_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_37_cast_fp16 = relu(x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_39_pad_type_0 = const()[name = string("input_39_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_39_pad_0 = const()[name = string("input_39_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43264)))];
            int32 input_39_groups_0 = const()[name = string("input_39_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_39_strides_0 = const()[name = string("input_39_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_39_dilations_0 = const()[name = string("input_39_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_105_to_fp16 = const()[name = string("const_105_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43392)))];
            tensor<fp16, [36]> const_106_to_fp16 = const()[name = string("const_106_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45312)))];
            tensor<fp16, [1, 36, 64, 64]> input_41_cast_fp16 = conv(bias = const_106_to_fp16, dilations = input_39_dilations_0, groups = input_39_groups_0, pad = input_39_pad_0, pad_type = input_39_pad_type_0, strides = input_39_strides_0, weight = const_105_to_fp16, x = input_37_cast_fp16)[name = string("input_41_cast_fp16")];
            string input_43_pad_type_0 = const()[name = string("input_43_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_43_strides_0 = const()[name = string("input_43_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45504)))];
            tensor<int32, [2]> input_43_dilations_0 = const()[name = string("input_43_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_43_groups_0 = const()[name = string("input_43_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45632)))];
            tensor<fp16, [36]> const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48320)))];
            tensor<fp16, [1, 36, 64, 64]> input_45_cast_fp16 = conv(bias = const_108_to_fp16, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_107_to_fp16, x = input_41_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_1_cast_fp16 = relu(x = input_45_cast_fp16)[name = string("out1_1_cast_fp16")];
            string input_49_pad_type_0 = const()[name = string("input_49_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_49_strides_0 = const()[name = string("input_49_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_49_pad_0 = const()[name = string("input_49_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48512)))];
            tensor<int32, [2]> input_49_dilations_0 = const()[name = string("input_49_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_49_groups_0 = const()[name = string("input_49_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_109_to_fp16 = const()[name = string("const_109_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48640)))];
            tensor<fp16, [36]> const_110_to_fp16 = const()[name = string("const_110_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51328)))];
            tensor<fp16, [1, 36, 64, 64]> input_51_cast_fp16 = conv(bias = const_110_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_109_to_fp16, x = var_2937_cast_fp16)[name = string("input_51_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_53_cast_fp16 = relu(x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string input_55_pad_type_0 = const()[name = string("input_55_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_55_pad_0 = const()[name = string("input_55_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51520)))];
            int32 input_55_groups_0 = const()[name = string("input_55_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_55_strides_0 = const()[name = string("input_55_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_55_dilations_0 = const()[name = string("input_55_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_111_to_fp16 = const()[name = string("const_111_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51648)))];
            tensor<fp16, [36]> const_112_to_fp16 = const()[name = string("const_112_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53568)))];
            tensor<fp16, [1, 36, 64, 64]> input_57_cast_fp16 = conv(bias = const_112_to_fp16, dilations = input_55_dilations_0, groups = input_55_groups_0, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = input_55_strides_0, weight = const_111_to_fp16, x = input_53_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_59_pad_type_0 = const()[name = string("input_59_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_59_strides_0 = const()[name = string("input_59_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_59_pad_0 = const()[name = string("input_59_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53760)))];
            tensor<int32, [2]> input_59_dilations_0 = const()[name = string("input_59_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_59_groups_0 = const()[name = string("input_59_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_113_to_fp16 = const()[name = string("const_113_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53888)))];
            tensor<fp16, [36]> const_114_to_fp16 = const()[name = string("const_114_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56576)))];
            tensor<fp16, [1, 36, 64, 64]> input_61_cast_fp16 = conv(bias = const_114_to_fp16, dilations = input_59_dilations_0, groups = input_59_groups_0, pad = input_59_pad_0, pad_type = input_59_pad_type_0, strides = input_59_strides_0, weight = const_113_to_fp16, x = input_57_cast_fp16)[name = string("input_61_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_1_cast_fp16 = relu(x = input_61_cast_fp16)[name = string("out2_1_cast_fp16")];
            string input_65_pad_type_0 = const()[name = string("input_65_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_65_strides_0 = const()[name = string("input_65_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_65_pad_0 = const()[name = string("input_65_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56768)))];
            tensor<int32, [2]> input_65_dilations_0 = const()[name = string("input_65_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_65_groups_0 = const()[name = string("input_65_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56896)))];
            tensor<fp16, [36]> const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59584)))];
            tensor<fp16, [1, 36, 64, 64]> input_67_cast_fp16 = conv(bias = const_116_to_fp16, dilations = input_65_dilations_0, groups = input_65_groups_0, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = input_65_strides_0, weight = const_115_to_fp16, x = var_2941_cast_fp16)[name = string("input_67_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_69_cast_fp16 = relu(x = input_67_cast_fp16)[name = string("input_69_cast_fp16")];
            string input_71_pad_type_0 = const()[name = string("input_71_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_71_pad_0 = const()[name = string("input_71_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59776)))];
            int32 input_71_groups_0 = const()[name = string("input_71_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_71_strides_0 = const()[name = string("input_71_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_71_dilations_0 = const()[name = string("input_71_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_117_to_fp16 = const()[name = string("const_117_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59904)))];
            tensor<fp16, [36]> const_118_to_fp16 = const()[name = string("const_118_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61824)))];
            tensor<fp16, [1, 36, 64, 64]> input_73_cast_fp16 = conv(bias = const_118_to_fp16, dilations = input_71_dilations_0, groups = input_71_groups_0, pad = input_71_pad_0, pad_type = input_71_pad_type_0, strides = input_71_strides_0, weight = const_117_to_fp16, x = input_69_cast_fp16)[name = string("input_73_cast_fp16")];
            string input_75_pad_type_0 = const()[name = string("input_75_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_75_strides_0 = const()[name = string("input_75_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_75_pad_0 = const()[name = string("input_75_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(62016)))];
            tensor<int32, [2]> input_75_dilations_0 = const()[name = string("input_75_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_75_groups_0 = const()[name = string("input_75_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_119_to_fp16 = const()[name = string("const_119_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(62144)))];
            tensor<fp16, [36]> const_120_to_fp16 = const()[name = string("const_120_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64832)))];
            tensor<fp16, [1, 36, 64, 64]> input_77_cast_fp16 = conv(bias = const_120_to_fp16, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = const_119_to_fp16, x = input_73_cast_fp16)[name = string("input_77_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_1_cast_fp16 = relu(x = input_77_cast_fp16)[name = string("out3_1_cast_fp16")];
            bool input_79_interleave_0 = const()[name = string("input_79_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_79_cast_fp16 = concat(axis = var_86, interleave = input_79_interleave_0, values = (var_2929_cast_fp16, out1_1_cast_fp16, out2_1_cast_fp16, out3_1_cast_fp16))[name = string("input_79_cast_fp16")];
            string input_81_pad_type_0 = const()[name = string("input_81_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_81_strides_0 = const()[name = string("input_81_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_81_pad_0 = const()[name = string("input_81_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(65024)))];
            tensor<int32, [2]> input_81_dilations_0 = const()[name = string("input_81_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_81_groups_0 = const()[name = string("input_81_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_121_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(65152))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85952))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86336)))];
            tensor<fp16, [144]> const_122_to_fp16 = const()[name = string("const_122_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86592)))];
            tensor<fp16, [1, 144, 64, 64]> input_83_cast_fp16 = conv(bias = const_122_to_fp16, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = const_121_to_fp16, x = input_79_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_85_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("input_85_cast_fp16")];
            string input_87_pad_type_0 = const()[name = string("input_87_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(86976)))];
            int32 input_87_groups_0 = const()[name = string("input_87_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_87_strides_0 = const()[name = string("input_87_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_87_dilations_0 = const()[name = string("input_87_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [144, 1, 5, 5]> const_123_to_fp16 = const()[name = string("const_123_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(87104)))];
            tensor<fp16, [144]> const_124_to_fp16 = const()[name = string("const_124_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94400)))];
            tensor<fp16, [1, 144, 64, 64]> input_89_cast_fp16 = conv(bias = const_124_to_fp16, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = const_123_to_fp16, x = input_85_cast_fp16)[name = string("input_89_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_91_cast_fp16 = relu(x = input_89_cast_fp16)[name = string("input_91_cast_fp16")];
            string input_93_pad_type_0 = const()[name = string("input_93_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_93_strides_0 = const()[name = string("input_93_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_93_pad_0 = const()[name = string("input_93_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94784)))];
            tensor<int32, [2]> input_93_dilations_0 = const()[name = string("input_93_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_93_groups_0 = const()[name = string("input_93_groups_0"), val = int32(1)];
            tensor<fp16, [144, 144, 1, 1]> const_125_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94912))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(115712))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116096)))];
            tensor<fp16, [144]> const_126_to_fp16 = const()[name = string("const_126_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116352)))];
            tensor<fp16, [1, 144, 64, 64]> y_1_cast_fp16 = conv(bias = const_126_to_fp16, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = const_125_to_fp16, x = input_91_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> x_3_cast_fp16 = add(x = input_79_cast_fp16, y = y_1_cast_fp16)[name = string("x_3_cast_fp16")];
            tensor<int32, [4]> var_3041_begin_0 = const()[name = string("op_3041_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116736)))];
            tensor<int32, [4]> var_3041_end_0 = const()[name = string("op_3041_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116864)))];
            tensor<bool, [4]> var_3041_end_mask_0 = const()[name = string("op_3041_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3041_cast_fp16 = slice_by_index(begin = var_3041_begin_0, end = var_3041_end_0, end_mask = var_3041_end_mask_0, x = x_3_cast_fp16)[name = string("op_3041_cast_fp16")];
            tensor<int32, [4]> var_3045_begin_0 = const()[name = string("op_3045_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(116992)))];
            tensor<int32, [4]> var_3045_end_0 = const()[name = string("op_3045_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117120)))];
            tensor<bool, [4]> var_3045_end_mask_0 = const()[name = string("op_3045_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3045_cast_fp16 = slice_by_index(begin = var_3045_begin_0, end = var_3045_end_0, end_mask = var_3045_end_mask_0, x = x_3_cast_fp16)[name = string("op_3045_cast_fp16")];
            tensor<int32, [4]> var_3049_begin_0 = const()[name = string("op_3049_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117248)))];
            tensor<int32, [4]> var_3049_end_0 = const()[name = string("op_3049_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117376)))];
            tensor<bool, [4]> var_3049_end_mask_0 = const()[name = string("op_3049_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3049_cast_fp16 = slice_by_index(begin = var_3049_begin_0, end = var_3049_end_0, end_mask = var_3049_end_mask_0, x = x_3_cast_fp16)[name = string("op_3049_cast_fp16")];
            tensor<int32, [4]> var_3053_begin_0 = const()[name = string("op_3053_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117504)))];
            tensor<int32, [4]> var_3053_end_0 = const()[name = string("op_3053_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117632)))];
            tensor<bool, [4]> var_3053_end_mask_0 = const()[name = string("op_3053_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_3053_cast_fp16 = slice_by_index(begin = var_3053_begin_0, end = var_3053_end_0, end_mask = var_3053_end_mask_0, x = x_3_cast_fp16)[name = string("op_3053_cast_fp16")];
            string input_97_pad_type_0 = const()[name = string("input_97_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_97_strides_0 = const()[name = string("input_97_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117760)))];
            tensor<int32, [2]> input_97_dilations_0 = const()[name = string("input_97_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_97_groups_0 = const()[name = string("input_97_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_127_to_fp16 = const()[name = string("const_127_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(117888)))];
            tensor<fp16, [36]> const_128_to_fp16 = const()[name = string("const_128_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120576)))];
            tensor<fp16, [1, 36, 64, 64]> input_99_cast_fp16 = conv(bias = const_128_to_fp16, dilations = input_97_dilations_0, groups = input_97_groups_0, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = input_97_strides_0, weight = const_127_to_fp16, x = var_3045_cast_fp16)[name = string("input_99_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_101_cast_fp16 = relu(x = input_99_cast_fp16)[name = string("input_101_cast_fp16")];
            string input_103_pad_type_0 = const()[name = string("input_103_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_103_pad_0 = const()[name = string("input_103_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120768)))];
            int32 input_103_groups_0 = const()[name = string("input_103_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_103_strides_0 = const()[name = string("input_103_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_103_dilations_0 = const()[name = string("input_103_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_129_to_fp16 = const()[name = string("const_129_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120896)))];
            tensor<fp16, [36]> const_130_to_fp16 = const()[name = string("const_130_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(122816)))];
            tensor<fp16, [1, 36, 64, 64]> input_105_cast_fp16 = conv(bias = const_130_to_fp16, dilations = input_103_dilations_0, groups = input_103_groups_0, pad = input_103_pad_0, pad_type = input_103_pad_type_0, strides = input_103_strides_0, weight = const_129_to_fp16, x = input_101_cast_fp16)[name = string("input_105_cast_fp16")];
            string input_107_pad_type_0 = const()[name = string("input_107_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_107_strides_0 = const()[name = string("input_107_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_107_pad_0 = const()[name = string("input_107_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123008)))];
            tensor<int32, [2]> input_107_dilations_0 = const()[name = string("input_107_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_107_groups_0 = const()[name = string("input_107_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_131_to_fp16 = const()[name = string("const_131_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123136)))];
            tensor<fp16, [36]> const_132_to_fp16 = const()[name = string("const_132_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(125824)))];
            tensor<fp16, [1, 36, 64, 64]> input_109_cast_fp16 = conv(bias = const_132_to_fp16, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = const_131_to_fp16, x = input_105_cast_fp16)[name = string("input_109_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_3_cast_fp16 = relu(x = input_109_cast_fp16)[name = string("out1_3_cast_fp16")];
            string input_113_pad_type_0 = const()[name = string("input_113_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_113_strides_0 = const()[name = string("input_113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_113_pad_0 = const()[name = string("input_113_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(126016)))];
            tensor<int32, [2]> input_113_dilations_0 = const()[name = string("input_113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_113_groups_0 = const()[name = string("input_113_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_133_to_fp16 = const()[name = string("const_133_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(126144)))];
            tensor<fp16, [36]> const_134_to_fp16 = const()[name = string("const_134_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(128832)))];
            tensor<fp16, [1, 36, 64, 64]> input_115_cast_fp16 = conv(bias = const_134_to_fp16, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = const_133_to_fp16, x = var_3049_cast_fp16)[name = string("input_115_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_117_cast_fp16 = relu(x = input_115_cast_fp16)[name = string("input_117_cast_fp16")];
            string input_119_pad_type_0 = const()[name = string("input_119_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_119_pad_0 = const()[name = string("input_119_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(129024)))];
            int32 input_119_groups_0 = const()[name = string("input_119_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_119_strides_0 = const()[name = string("input_119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_119_dilations_0 = const()[name = string("input_119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_135_to_fp16 = const()[name = string("const_135_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(129152)))];
            tensor<fp16, [36]> const_136_to_fp16 = const()[name = string("const_136_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131072)))];
            tensor<fp16, [1, 36, 64, 64]> input_121_cast_fp16 = conv(bias = const_136_to_fp16, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = const_135_to_fp16, x = input_117_cast_fp16)[name = string("input_121_cast_fp16")];
            string input_123_pad_type_0 = const()[name = string("input_123_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_123_strides_0 = const()[name = string("input_123_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_123_pad_0 = const()[name = string("input_123_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131264)))];
            tensor<int32, [2]> input_123_dilations_0 = const()[name = string("input_123_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_123_groups_0 = const()[name = string("input_123_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_137_to_fp16 = const()[name = string("const_137_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131392)))];
            tensor<fp16, [36]> const_138_to_fp16 = const()[name = string("const_138_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134080)))];
            tensor<fp16, [1, 36, 64, 64]> input_125_cast_fp16 = conv(bias = const_138_to_fp16, dilations = input_123_dilations_0, groups = input_123_groups_0, pad = input_123_pad_0, pad_type = input_123_pad_type_0, strides = input_123_strides_0, weight = const_137_to_fp16, x = input_121_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_3_cast_fp16 = relu(x = input_125_cast_fp16)[name = string("out2_3_cast_fp16")];
            string input_129_pad_type_0 = const()[name = string("input_129_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_129_strides_0 = const()[name = string("input_129_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_129_pad_0 = const()[name = string("input_129_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134272)))];
            tensor<int32, [2]> input_129_dilations_0 = const()[name = string("input_129_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_129_groups_0 = const()[name = string("input_129_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_139_to_fp16 = const()[name = string("const_139_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134400)))];
            tensor<fp16, [36]> const_140_to_fp16 = const()[name = string("const_140_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137088)))];
            tensor<fp16, [1, 36, 64, 64]> input_131_cast_fp16 = conv(bias = const_140_to_fp16, dilations = input_129_dilations_0, groups = input_129_groups_0, pad = input_129_pad_0, pad_type = input_129_pad_type_0, strides = input_129_strides_0, weight = const_139_to_fp16, x = var_3053_cast_fp16)[name = string("input_131_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_133_cast_fp16 = relu(x = input_131_cast_fp16)[name = string("input_133_cast_fp16")];
            string input_135_pad_type_0 = const()[name = string("input_135_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_135_pad_0 = const()[name = string("input_135_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137280)))];
            int32 input_135_groups_0 = const()[name = string("input_135_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_135_strides_0 = const()[name = string("input_135_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_135_dilations_0 = const()[name = string("input_135_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36, 1, 5, 5]> const_141_to_fp16 = const()[name = string("const_141_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137408)))];
            tensor<fp16, [36]> const_142_to_fp16 = const()[name = string("const_142_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139328)))];
            tensor<fp16, [1, 36, 64, 64]> input_137_cast_fp16 = conv(bias = const_142_to_fp16, dilations = input_135_dilations_0, groups = input_135_groups_0, pad = input_135_pad_0, pad_type = input_135_pad_type_0, strides = input_135_strides_0, weight = const_141_to_fp16, x = input_133_cast_fp16)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139520)))];
            tensor<int32, [2]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [36, 36, 1, 1]> const_143_to_fp16 = const()[name = string("const_143_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139648)))];
            tensor<fp16, [36]> const_144_to_fp16 = const()[name = string("const_144_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142336)))];
            tensor<fp16, [1, 36, 64, 64]> input_141_cast_fp16 = conv(bias = const_144_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = const_143_to_fp16, x = input_137_cast_fp16)[name = string("input_141_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_3_cast_fp16 = relu(x = input_141_cast_fp16)[name = string("out3_3_cast_fp16")];
            bool input_143_interleave_0 = const()[name = string("input_143_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_143_cast_fp16 = concat(axis = var_86, interleave = input_143_interleave_0, values = (var_3041_cast_fp16, out1_3_cast_fp16, out2_3_cast_fp16, out3_3_cast_fp16))[name = string("input_143_cast_fp16")];
            string input_145_pad_type_0 = const()[name = string("input_145_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_145_strides_0 = const()[name = string("input_145_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_145_pad_0 = const()[name = string("input_145_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142528)))];
            tensor<int32, [2]> input_145_dilations_0 = const()[name = string("input_145_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_145_groups_0 = const()[name = string("input_145_groups_0"), val = int32(1)];
            tensor<fp16, [256, 144, 1, 1]> const_145_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142656))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(179584))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180160)))];
            tensor<fp16, [256]> const_146_to_fp16 = const()[name = string("const_146_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180480)))];
            tensor<fp16, [1, 256, 64, 64]> input_147_cast_fp16 = conv(bias = const_146_to_fp16, dilations = input_145_dilations_0, groups = input_145_groups_0, pad = input_145_pad_0, pad_type = input_145_pad_type_0, strides = input_145_strides_0, weight = const_145_to_fp16, x = input_143_cast_fp16)[name = string("input_147_cast_fp16")];
            tensor<fp16, [1, 256, 64, 64]> input_149_cast_fp16 = relu(x = input_147_cast_fp16)[name = string("input_149_cast_fp16")];
            string input_151_pad_type_0 = const()[name = string("input_151_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_151_pad_0 = const()[name = string("input_151_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181056)))];
            tensor<int32, [2]> input_151_strides_0 = const()[name = string("input_151_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_151_groups_0 = const()[name = string("input_151_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_151_dilations_0 = const()[name = string("input_151_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_147_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181184))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(187648))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(188224)))];
            tensor<fp16, [256]> const_148_to_fp16 = const()[name = string("const_148_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(188544)))];
            tensor<fp16, [1, 256, 32, 32]> input_153_cast_fp16 = conv(bias = const_148_to_fp16, dilations = input_151_dilations_0, groups = input_151_groups_0, pad = input_151_pad_0, pad_type = input_151_pad_type_0, strides = input_151_strides_0, weight = const_147_to_fp16, x = input_149_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_155_cast_fp16 = relu(x = input_153_cast_fp16)[name = string("input_155_cast_fp16")];
            string input_157_pad_type_0 = const()[name = string("input_157_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_157_strides_0 = const()[name = string("input_157_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_157_pad_0 = const()[name = string("input_157_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189120)))];
            tensor<int32, [2]> input_157_dilations_0 = const()[name = string("input_157_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_157_groups_0 = const()[name = string("input_157_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_149_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189248))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(254848))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(255424)))];
            tensor<fp16, [256]> const_150_to_fp16 = const()[name = string("const_150_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(255744)))];
            tensor<fp16, [1, 256, 32, 32]> x_5_cast_fp16 = conv(bias = const_150_to_fp16, dilations = input_157_dilations_0, groups = input_157_groups_0, pad = input_157_pad_0, pad_type = input_157_pad_type_0, strides = input_157_strides_0, weight = const_149_to_fp16, x = input_155_cast_fp16)[name = string("x_5_cast_fp16")];
            tensor<int32, [4]> var_3152_begin_0 = const()[name = string("op_3152_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256320)))];
            tensor<int32, [4]> var_3152_end_0 = const()[name = string("op_3152_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256448)))];
            tensor<bool, [4]> var_3152_end_mask_0 = const()[name = string("op_3152_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3152_cast_fp16 = slice_by_index(begin = var_3152_begin_0, end = var_3152_end_0, end_mask = var_3152_end_mask_0, x = x_5_cast_fp16)[name = string("op_3152_cast_fp16")];
            tensor<int32, [4]> var_3156_begin_0 = const()[name = string("op_3156_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256576)))];
            tensor<int32, [4]> var_3156_end_0 = const()[name = string("op_3156_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256704)))];
            tensor<bool, [4]> var_3156_end_mask_0 = const()[name = string("op_3156_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3156_cast_fp16 = slice_by_index(begin = var_3156_begin_0, end = var_3156_end_0, end_mask = var_3156_end_mask_0, x = x_5_cast_fp16)[name = string("op_3156_cast_fp16")];
            tensor<int32, [4]> var_3160_begin_0 = const()[name = string("op_3160_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256832)))];
            tensor<int32, [4]> var_3160_end_0 = const()[name = string("op_3160_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(256960)))];
            tensor<bool, [4]> var_3160_end_mask_0 = const()[name = string("op_3160_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3160_cast_fp16 = slice_by_index(begin = var_3160_begin_0, end = var_3160_end_0, end_mask = var_3160_end_mask_0, x = x_5_cast_fp16)[name = string("op_3160_cast_fp16")];
            tensor<int32, [4]> var_3164_begin_0 = const()[name = string("op_3164_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257088)))];
            tensor<int32, [4]> var_3164_end_0 = const()[name = string("op_3164_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257216)))];
            tensor<bool, [4]> var_3164_end_mask_0 = const()[name = string("op_3164_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3164_cast_fp16 = slice_by_index(begin = var_3164_begin_0, end = var_3164_end_0, end_mask = var_3164_end_mask_0, x = x_5_cast_fp16)[name = string("op_3164_cast_fp16")];
            string input_161_pad_type_0 = const()[name = string("input_161_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_161_strides_0 = const()[name = string("input_161_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_161_pad_0 = const()[name = string("input_161_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257344)))];
            tensor<int32, [2]> input_161_dilations_0 = const()[name = string("input_161_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_161_groups_0 = const()[name = string("input_161_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_151_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(257472))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261632))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261824)))];
            tensor<fp16, [64]> const_152_to_fp16 = const()[name = string("const_152_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(261952)))];
            tensor<fp16, [1, 64, 32, 32]> input_163_cast_fp16 = conv(bias = const_152_to_fp16, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_151_to_fp16, x = var_3156_cast_fp16)[name = string("input_163_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_165_cast_fp16 = relu(x = input_163_cast_fp16)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262144)))];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_153_to_fp16 = const()[name = string("const_153_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262272)))];
            tensor<fp16, [64]> const_154_to_fp16 = const()[name = string("const_154_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265536)))];
            tensor<fp16, [1, 64, 32, 32]> input_169_cast_fp16 = conv(bias = const_154_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_153_to_fp16, x = input_165_cast_fp16)[name = string("input_169_cast_fp16")];
            string input_171_pad_type_0 = const()[name = string("input_171_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_171_strides_0 = const()[name = string("input_171_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_171_pad_0 = const()[name = string("input_171_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265728)))];
            tensor<int32, [2]> input_171_dilations_0 = const()[name = string("input_171_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_171_groups_0 = const()[name = string("input_171_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_155_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(265856))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270016))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270208)))];
            tensor<fp16, [64]> const_156_to_fp16 = const()[name = string("const_156_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270336)))];
            tensor<fp16, [1, 64, 32, 32]> input_173_cast_fp16 = conv(bias = const_156_to_fp16, dilations = input_171_dilations_0, groups = input_171_groups_0, pad = input_171_pad_0, pad_type = input_171_pad_type_0, strides = input_171_strides_0, weight = const_155_to_fp16, x = input_169_cast_fp16)[name = string("input_173_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_5_cast_fp16 = relu(x = input_173_cast_fp16)[name = string("out1_5_cast_fp16")];
            string input_177_pad_type_0 = const()[name = string("input_177_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_177_strides_0 = const()[name = string("input_177_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_177_pad_0 = const()[name = string("input_177_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270528)))];
            tensor<int32, [2]> input_177_dilations_0 = const()[name = string("input_177_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_177_groups_0 = const()[name = string("input_177_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_157_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270656))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274816))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275008)))];
            tensor<fp16, [64]> const_158_to_fp16 = const()[name = string("const_158_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275136)))];
            tensor<fp16, [1, 64, 32, 32]> input_179_cast_fp16 = conv(bias = const_158_to_fp16, dilations = input_177_dilations_0, groups = input_177_groups_0, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = input_177_strides_0, weight = const_157_to_fp16, x = var_3160_cast_fp16)[name = string("input_179_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_181_cast_fp16 = relu(x = input_179_cast_fp16)[name = string("input_181_cast_fp16")];
            string input_183_pad_type_0 = const()[name = string("input_183_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_183_pad_0 = const()[name = string("input_183_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275328)))];
            int32 input_183_groups_0 = const()[name = string("input_183_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_183_strides_0 = const()[name = string("input_183_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_183_dilations_0 = const()[name = string("input_183_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_159_to_fp16 = const()[name = string("const_159_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275456)))];
            tensor<fp16, [64]> const_160_to_fp16 = const()[name = string("const_160_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278720)))];
            tensor<fp16, [1, 64, 32, 32]> input_185_cast_fp16 = conv(bias = const_160_to_fp16, dilations = input_183_dilations_0, groups = input_183_groups_0, pad = input_183_pad_0, pad_type = input_183_pad_type_0, strides = input_183_strides_0, weight = const_159_to_fp16, x = input_181_cast_fp16)[name = string("input_185_cast_fp16")];
            string input_187_pad_type_0 = const()[name = string("input_187_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_187_strides_0 = const()[name = string("input_187_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_187_pad_0 = const()[name = string("input_187_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278912)))];
            tensor<int32, [2]> input_187_dilations_0 = const()[name = string("input_187_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_187_groups_0 = const()[name = string("input_187_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_161_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(279040))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283200))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283392)))];
            tensor<fp16, [64]> const_162_to_fp16 = const()[name = string("const_162_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283520)))];
            tensor<fp16, [1, 64, 32, 32]> input_189_cast_fp16 = conv(bias = const_162_to_fp16, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = const_161_to_fp16, x = input_185_cast_fp16)[name = string("input_189_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_5_cast_fp16 = relu(x = input_189_cast_fp16)[name = string("out2_5_cast_fp16")];
            string input_193_pad_type_0 = const()[name = string("input_193_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_193_strides_0 = const()[name = string("input_193_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_193_pad_0 = const()[name = string("input_193_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283712)))];
            tensor<int32, [2]> input_193_dilations_0 = const()[name = string("input_193_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_193_groups_0 = const()[name = string("input_193_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_163_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(283840))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288000))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288192)))];
            tensor<fp16, [64]> const_164_to_fp16 = const()[name = string("const_164_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288320)))];
            tensor<fp16, [1, 64, 32, 32]> input_195_cast_fp16 = conv(bias = const_164_to_fp16, dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = const_163_to_fp16, x = var_3164_cast_fp16)[name = string("input_195_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_197_cast_fp16 = relu(x = input_195_cast_fp16)[name = string("input_197_cast_fp16")];
            string input_199_pad_type_0 = const()[name = string("input_199_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_199_pad_0 = const()[name = string("input_199_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288512)))];
            int32 input_199_groups_0 = const()[name = string("input_199_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_199_strides_0 = const()[name = string("input_199_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_199_dilations_0 = const()[name = string("input_199_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_165_to_fp16 = const()[name = string("const_165_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288640)))];
            tensor<fp16, [64]> const_166_to_fp16 = const()[name = string("const_166_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(291904)))];
            tensor<fp16, [1, 64, 32, 32]> input_201_cast_fp16 = conv(bias = const_166_to_fp16, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_165_to_fp16, x = input_197_cast_fp16)[name = string("input_201_cast_fp16")];
            string input_203_pad_type_0 = const()[name = string("input_203_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_203_strides_0 = const()[name = string("input_203_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_203_pad_0 = const()[name = string("input_203_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(292096)))];
            tensor<int32, [2]> input_203_dilations_0 = const()[name = string("input_203_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_203_groups_0 = const()[name = string("input_203_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_167_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(292224))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296384))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296576)))];
            tensor<fp16, [64]> const_168_to_fp16 = const()[name = string("const_168_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296704)))];
            tensor<fp16, [1, 64, 32, 32]> input_205_cast_fp16 = conv(bias = const_168_to_fp16, dilations = input_203_dilations_0, groups = input_203_groups_0, pad = input_203_pad_0, pad_type = input_203_pad_type_0, strides = input_203_strides_0, weight = const_167_to_fp16, x = input_201_cast_fp16)[name = string("input_205_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_5_cast_fp16 = relu(x = input_205_cast_fp16)[name = string("out3_5_cast_fp16")];
            bool input_207_interleave_0 = const()[name = string("input_207_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_207_cast_fp16 = concat(axis = var_86, interleave = input_207_interleave_0, values = (var_3152_cast_fp16, out1_5_cast_fp16, out2_5_cast_fp16, out3_5_cast_fp16))[name = string("input_207_cast_fp16")];
            string input_209_pad_type_0 = const()[name = string("input_209_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_209_strides_0 = const()[name = string("input_209_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_209_pad_0 = const()[name = string("input_209_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296896)))];
            tensor<int32, [2]> input_209_dilations_0 = const()[name = string("input_209_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_209_groups_0 = const()[name = string("input_209_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_169_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(297024))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(362624))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(363200)))];
            tensor<fp16, [256]> const_170_to_fp16 = const()[name = string("const_170_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(363520)))];
            tensor<fp16, [1, 256, 32, 32]> input_211_cast_fp16 = conv(bias = const_170_to_fp16, dilations = input_209_dilations_0, groups = input_209_groups_0, pad = input_209_pad_0, pad_type = input_209_pad_type_0, strides = input_209_strides_0, weight = const_169_to_fp16, x = input_207_cast_fp16)[name = string("input_211_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_213_cast_fp16 = relu(x = input_211_cast_fp16)[name = string("input_213_cast_fp16")];
            string input_215_pad_type_0 = const()[name = string("input_215_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_215_pad_0 = const()[name = string("input_215_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(364096)))];
            int32 input_215_groups_0 = const()[name = string("input_215_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_215_strides_0 = const()[name = string("input_215_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_215_dilations_0 = const()[name = string("input_215_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_171_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(364224))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(370688))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(371264)))];
            tensor<fp16, [256]> const_172_to_fp16 = const()[name = string("const_172_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(371584)))];
            tensor<fp16, [1, 256, 32, 32]> input_217_cast_fp16 = conv(bias = const_172_to_fp16, dilations = input_215_dilations_0, groups = input_215_groups_0, pad = input_215_pad_0, pad_type = input_215_pad_type_0, strides = input_215_strides_0, weight = const_171_to_fp16, x = input_213_cast_fp16)[name = string("input_217_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_219_cast_fp16 = relu(x = input_217_cast_fp16)[name = string("input_219_cast_fp16")];
            string input_221_pad_type_0 = const()[name = string("input_221_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_221_strides_0 = const()[name = string("input_221_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_221_pad_0 = const()[name = string("input_221_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(372160)))];
            tensor<int32, [2]> input_221_dilations_0 = const()[name = string("input_221_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_221_groups_0 = const()[name = string("input_221_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_173_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(372288))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(437888))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(438464)))];
            tensor<fp16, [256]> const_174_to_fp16 = const()[name = string("const_174_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(438784)))];
            tensor<fp16, [1, 256, 32, 32]> y_3_cast_fp16 = conv(bias = const_174_to_fp16, dilations = input_221_dilations_0, groups = input_221_groups_0, pad = input_221_pad_0, pad_type = input_221_pad_type_0, strides = input_221_strides_0, weight = const_173_to_fp16, x = input_219_cast_fp16)[name = string("y_3_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_7_cast_fp16 = add(x = input_207_cast_fp16, y = y_3_cast_fp16)[name = string("x_7_cast_fp16")];
            tensor<int32, [4]> var_3264_begin_0 = const()[name = string("op_3264_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439360)))];
            tensor<int32, [4]> var_3264_end_0 = const()[name = string("op_3264_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439488)))];
            tensor<bool, [4]> var_3264_end_mask_0 = const()[name = string("op_3264_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3264_cast_fp16 = slice_by_index(begin = var_3264_begin_0, end = var_3264_end_0, end_mask = var_3264_end_mask_0, x = x_7_cast_fp16)[name = string("op_3264_cast_fp16")];
            tensor<int32, [4]> var_3268_begin_0 = const()[name = string("op_3268_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439616)))];
            tensor<int32, [4]> var_3268_end_0 = const()[name = string("op_3268_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439744)))];
            tensor<bool, [4]> var_3268_end_mask_0 = const()[name = string("op_3268_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3268_cast_fp16 = slice_by_index(begin = var_3268_begin_0, end = var_3268_end_0, end_mask = var_3268_end_mask_0, x = x_7_cast_fp16)[name = string("op_3268_cast_fp16")];
            tensor<int32, [4]> var_3272_begin_0 = const()[name = string("op_3272_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(439872)))];
            tensor<int32, [4]> var_3272_end_0 = const()[name = string("op_3272_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440000)))];
            tensor<bool, [4]> var_3272_end_mask_0 = const()[name = string("op_3272_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3272_cast_fp16 = slice_by_index(begin = var_3272_begin_0, end = var_3272_end_0, end_mask = var_3272_end_mask_0, x = x_7_cast_fp16)[name = string("op_3272_cast_fp16")];
            tensor<int32, [4]> var_3276_begin_0 = const()[name = string("op_3276_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440128)))];
            tensor<int32, [4]> var_3276_end_0 = const()[name = string("op_3276_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440256)))];
            tensor<bool, [4]> var_3276_end_mask_0 = const()[name = string("op_3276_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3276_cast_fp16 = slice_by_index(begin = var_3276_begin_0, end = var_3276_end_0, end_mask = var_3276_end_mask_0, x = x_7_cast_fp16)[name = string("op_3276_cast_fp16")];
            string input_225_pad_type_0 = const()[name = string("input_225_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_225_strides_0 = const()[name = string("input_225_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_225_pad_0 = const()[name = string("input_225_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440384)))];
            tensor<int32, [2]> input_225_dilations_0 = const()[name = string("input_225_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_225_groups_0 = const()[name = string("input_225_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_175_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440512))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444672))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444864)))];
            tensor<fp16, [64]> const_176_to_fp16 = const()[name = string("const_176_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(444992)))];
            tensor<fp16, [1, 64, 32, 32]> input_227_cast_fp16 = conv(bias = const_176_to_fp16, dilations = input_225_dilations_0, groups = input_225_groups_0, pad = input_225_pad_0, pad_type = input_225_pad_type_0, strides = input_225_strides_0, weight = const_175_to_fp16, x = var_3268_cast_fp16)[name = string("input_227_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_229_cast_fp16 = relu(x = input_227_cast_fp16)[name = string("input_229_cast_fp16")];
            string input_231_pad_type_0 = const()[name = string("input_231_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_231_pad_0 = const()[name = string("input_231_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(445184)))];
            int32 input_231_groups_0 = const()[name = string("input_231_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_231_strides_0 = const()[name = string("input_231_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_231_dilations_0 = const()[name = string("input_231_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_177_to_fp16 = const()[name = string("const_177_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(445312)))];
            tensor<fp16, [64]> const_178_to_fp16 = const()[name = string("const_178_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448576)))];
            tensor<fp16, [1, 64, 32, 32]> input_233_cast_fp16 = conv(bias = const_178_to_fp16, dilations = input_231_dilations_0, groups = input_231_groups_0, pad = input_231_pad_0, pad_type = input_231_pad_type_0, strides = input_231_strides_0, weight = const_177_to_fp16, x = input_229_cast_fp16)[name = string("input_233_cast_fp16")];
            string input_235_pad_type_0 = const()[name = string("input_235_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_235_strides_0 = const()[name = string("input_235_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_235_pad_0 = const()[name = string("input_235_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448768)))];
            tensor<int32, [2]> input_235_dilations_0 = const()[name = string("input_235_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_235_groups_0 = const()[name = string("input_235_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_179_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(448896))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453056))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453248)))];
            tensor<fp16, [64]> const_180_to_fp16 = const()[name = string("const_180_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453376)))];
            tensor<fp16, [1, 64, 32, 32]> input_237_cast_fp16 = conv(bias = const_180_to_fp16, dilations = input_235_dilations_0, groups = input_235_groups_0, pad = input_235_pad_0, pad_type = input_235_pad_type_0, strides = input_235_strides_0, weight = const_179_to_fp16, x = input_233_cast_fp16)[name = string("input_237_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_7_cast_fp16 = relu(x = input_237_cast_fp16)[name = string("out1_7_cast_fp16")];
            string input_241_pad_type_0 = const()[name = string("input_241_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_241_strides_0 = const()[name = string("input_241_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_241_pad_0 = const()[name = string("input_241_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453568)))];
            tensor<int32, [2]> input_241_dilations_0 = const()[name = string("input_241_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_241_groups_0 = const()[name = string("input_241_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_181_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(453696))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(457856))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458048)))];
            tensor<fp16, [64]> const_182_to_fp16 = const()[name = string("const_182_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458176)))];
            tensor<fp16, [1, 64, 32, 32]> input_243_cast_fp16 = conv(bias = const_182_to_fp16, dilations = input_241_dilations_0, groups = input_241_groups_0, pad = input_241_pad_0, pad_type = input_241_pad_type_0, strides = input_241_strides_0, weight = const_181_to_fp16, x = var_3272_cast_fp16)[name = string("input_243_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_245_cast_fp16 = relu(x = input_243_cast_fp16)[name = string("input_245_cast_fp16")];
            string input_247_pad_type_0 = const()[name = string("input_247_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_247_pad_0 = const()[name = string("input_247_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458368)))];
            int32 input_247_groups_0 = const()[name = string("input_247_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_247_strides_0 = const()[name = string("input_247_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_247_dilations_0 = const()[name = string("input_247_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_183_to_fp16 = const()[name = string("const_183_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(458496)))];
            tensor<fp16, [64]> const_184_to_fp16 = const()[name = string("const_184_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(461760)))];
            tensor<fp16, [1, 64, 32, 32]> input_249_cast_fp16 = conv(bias = const_184_to_fp16, dilations = input_247_dilations_0, groups = input_247_groups_0, pad = input_247_pad_0, pad_type = input_247_pad_type_0, strides = input_247_strides_0, weight = const_183_to_fp16, x = input_245_cast_fp16)[name = string("input_249_cast_fp16")];
            string input_251_pad_type_0 = const()[name = string("input_251_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_251_strides_0 = const()[name = string("input_251_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_251_pad_0 = const()[name = string("input_251_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(461952)))];
            tensor<int32, [2]> input_251_dilations_0 = const()[name = string("input_251_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_251_groups_0 = const()[name = string("input_251_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_185_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(462080))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466240))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466432)))];
            tensor<fp16, [64]> const_186_to_fp16 = const()[name = string("const_186_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466560)))];
            tensor<fp16, [1, 64, 32, 32]> input_253_cast_fp16 = conv(bias = const_186_to_fp16, dilations = input_251_dilations_0, groups = input_251_groups_0, pad = input_251_pad_0, pad_type = input_251_pad_type_0, strides = input_251_strides_0, weight = const_185_to_fp16, x = input_249_cast_fp16)[name = string("input_253_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_7_cast_fp16 = relu(x = input_253_cast_fp16)[name = string("out2_7_cast_fp16")];
            string input_257_pad_type_0 = const()[name = string("input_257_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_257_strides_0 = const()[name = string("input_257_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_257_pad_0 = const()[name = string("input_257_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466752)))];
            tensor<int32, [2]> input_257_dilations_0 = const()[name = string("input_257_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_257_groups_0 = const()[name = string("input_257_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_187_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(466880))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471040))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471232)))];
            tensor<fp16, [64]> const_188_to_fp16 = const()[name = string("const_188_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471360)))];
            tensor<fp16, [1, 64, 32, 32]> input_259_cast_fp16 = conv(bias = const_188_to_fp16, dilations = input_257_dilations_0, groups = input_257_groups_0, pad = input_257_pad_0, pad_type = input_257_pad_type_0, strides = input_257_strides_0, weight = const_187_to_fp16, x = var_3276_cast_fp16)[name = string("input_259_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_261_cast_fp16 = relu(x = input_259_cast_fp16)[name = string("input_261_cast_fp16")];
            string input_263_pad_type_0 = const()[name = string("input_263_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_263_pad_0 = const()[name = string("input_263_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471552)))];
            int32 input_263_groups_0 = const()[name = string("input_263_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_263_strides_0 = const()[name = string("input_263_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_263_dilations_0 = const()[name = string("input_263_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_189_to_fp16 = const()[name = string("const_189_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471680)))];
            tensor<fp16, [64]> const_190_to_fp16 = const()[name = string("const_190_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(474944)))];
            tensor<fp16, [1, 64, 32, 32]> input_265_cast_fp16 = conv(bias = const_190_to_fp16, dilations = input_263_dilations_0, groups = input_263_groups_0, pad = input_263_pad_0, pad_type = input_263_pad_type_0, strides = input_263_strides_0, weight = const_189_to_fp16, x = input_261_cast_fp16)[name = string("input_265_cast_fp16")];
            string input_267_pad_type_0 = const()[name = string("input_267_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_267_strides_0 = const()[name = string("input_267_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_267_pad_0 = const()[name = string("input_267_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(475136)))];
            tensor<int32, [2]> input_267_dilations_0 = const()[name = string("input_267_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_267_groups_0 = const()[name = string("input_267_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_191_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(475264))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479424))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479616)))];
            tensor<fp16, [64]> const_192_to_fp16 = const()[name = string("const_192_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479744)))];
            tensor<fp16, [1, 64, 32, 32]> input_269_cast_fp16 = conv(bias = const_192_to_fp16, dilations = input_267_dilations_0, groups = input_267_groups_0, pad = input_267_pad_0, pad_type = input_267_pad_type_0, strides = input_267_strides_0, weight = const_191_to_fp16, x = input_265_cast_fp16)[name = string("input_269_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_7_cast_fp16 = relu(x = input_269_cast_fp16)[name = string("out3_7_cast_fp16")];
            bool input_271_interleave_0 = const()[name = string("input_271_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_271_cast_fp16 = concat(axis = var_86, interleave = input_271_interleave_0, values = (var_3264_cast_fp16, out1_7_cast_fp16, out2_7_cast_fp16, out3_7_cast_fp16))[name = string("input_271_cast_fp16")];
            string input_273_pad_type_0 = const()[name = string("input_273_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_273_strides_0 = const()[name = string("input_273_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_273_pad_0 = const()[name = string("input_273_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(479936)))];
            tensor<int32, [2]> input_273_dilations_0 = const()[name = string("input_273_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_273_groups_0 = const()[name = string("input_273_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_193_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(480064))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(545664))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(546240)))];
            tensor<fp16, [256]> const_194_to_fp16 = const()[name = string("const_194_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(546560)))];
            tensor<fp16, [1, 256, 32, 32]> input_275_cast_fp16 = conv(bias = const_194_to_fp16, dilations = input_273_dilations_0, groups = input_273_groups_0, pad = input_273_pad_0, pad_type = input_273_pad_type_0, strides = input_273_strides_0, weight = const_193_to_fp16, x = input_271_cast_fp16)[name = string("input_275_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_277_cast_fp16 = relu(x = input_275_cast_fp16)[name = string("input_277_cast_fp16")];
            string input_279_pad_type_0 = const()[name = string("input_279_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_279_pad_0 = const()[name = string("input_279_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(547136)))];
            int32 input_279_groups_0 = const()[name = string("input_279_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_279_strides_0 = const()[name = string("input_279_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_279_dilations_0 = const()[name = string("input_279_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_195_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(547264))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(553728))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(554304)))];
            tensor<fp16, [256]> const_196_to_fp16 = const()[name = string("const_196_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(554624)))];
            tensor<fp16, [1, 256, 32, 32]> input_281_cast_fp16 = conv(bias = const_196_to_fp16, dilations = input_279_dilations_0, groups = input_279_groups_0, pad = input_279_pad_0, pad_type = input_279_pad_type_0, strides = input_279_strides_0, weight = const_195_to_fp16, x = input_277_cast_fp16)[name = string("input_281_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_283_cast_fp16 = relu(x = input_281_cast_fp16)[name = string("input_283_cast_fp16")];
            string input_285_pad_type_0 = const()[name = string("input_285_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_285_strides_0 = const()[name = string("input_285_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_285_pad_0 = const()[name = string("input_285_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(555200)))];
            tensor<int32, [2]> input_285_dilations_0 = const()[name = string("input_285_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_285_groups_0 = const()[name = string("input_285_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_197_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(555328))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(620928))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(621504)))];
            tensor<fp16, [256]> const_198_to_fp16 = const()[name = string("const_198_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(621824)))];
            tensor<fp16, [1, 256, 32, 32]> y_5_cast_fp16 = conv(bias = const_198_to_fp16, dilations = input_285_dilations_0, groups = input_285_groups_0, pad = input_285_pad_0, pad_type = input_285_pad_type_0, strides = input_285_strides_0, weight = const_197_to_fp16, x = input_283_cast_fp16)[name = string("y_5_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_9_cast_fp16 = add(x = input_271_cast_fp16, y = y_5_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<int32, [4]> var_3376_begin_0 = const()[name = string("op_3376_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622400)))];
            tensor<int32, [4]> var_3376_end_0 = const()[name = string("op_3376_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622528)))];
            tensor<bool, [4]> var_3376_end_mask_0 = const()[name = string("op_3376_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3376_cast_fp16 = slice_by_index(begin = var_3376_begin_0, end = var_3376_end_0, end_mask = var_3376_end_mask_0, x = x_9_cast_fp16)[name = string("op_3376_cast_fp16")];
            tensor<int32, [4]> var_3380_begin_0 = const()[name = string("op_3380_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622656)))];
            tensor<int32, [4]> var_3380_end_0 = const()[name = string("op_3380_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622784)))];
            tensor<bool, [4]> var_3380_end_mask_0 = const()[name = string("op_3380_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3380_cast_fp16 = slice_by_index(begin = var_3380_begin_0, end = var_3380_end_0, end_mask = var_3380_end_mask_0, x = x_9_cast_fp16)[name = string("op_3380_cast_fp16")];
            tensor<int32, [4]> var_3384_begin_0 = const()[name = string("op_3384_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622912)))];
            tensor<int32, [4]> var_3384_end_0 = const()[name = string("op_3384_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623040)))];
            tensor<bool, [4]> var_3384_end_mask_0 = const()[name = string("op_3384_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3384_cast_fp16 = slice_by_index(begin = var_3384_begin_0, end = var_3384_end_0, end_mask = var_3384_end_mask_0, x = x_9_cast_fp16)[name = string("op_3384_cast_fp16")];
            tensor<int32, [4]> var_3388_begin_0 = const()[name = string("op_3388_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623168)))];
            tensor<int32, [4]> var_3388_end_0 = const()[name = string("op_3388_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623296)))];
            tensor<bool, [4]> var_3388_end_mask_0 = const()[name = string("op_3388_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3388_cast_fp16 = slice_by_index(begin = var_3388_begin_0, end = var_3388_end_0, end_mask = var_3388_end_mask_0, x = x_9_cast_fp16)[name = string("op_3388_cast_fp16")];
            string input_289_pad_type_0 = const()[name = string("input_289_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_289_strides_0 = const()[name = string("input_289_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_289_pad_0 = const()[name = string("input_289_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623424)))];
            tensor<int32, [2]> input_289_dilations_0 = const()[name = string("input_289_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_289_groups_0 = const()[name = string("input_289_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_199_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(623552))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627712))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627904)))];
            tensor<fp16, [64]> const_200_to_fp16 = const()[name = string("const_200_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628032)))];
            tensor<fp16, [1, 64, 32, 32]> input_291_cast_fp16 = conv(bias = const_200_to_fp16, dilations = input_289_dilations_0, groups = input_289_groups_0, pad = input_289_pad_0, pad_type = input_289_pad_type_0, strides = input_289_strides_0, weight = const_199_to_fp16, x = var_3380_cast_fp16)[name = string("input_291_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_293_cast_fp16 = relu(x = input_291_cast_fp16)[name = string("input_293_cast_fp16")];
            string input_295_pad_type_0 = const()[name = string("input_295_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_295_pad_0 = const()[name = string("input_295_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628224)))];
            int32 input_295_groups_0 = const()[name = string("input_295_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_295_strides_0 = const()[name = string("input_295_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_295_dilations_0 = const()[name = string("input_295_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_201_to_fp16 = const()[name = string("const_201_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(628352)))];
            tensor<fp16, [64]> const_202_to_fp16 = const()[name = string("const_202_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631616)))];
            tensor<fp16, [1, 64, 32, 32]> input_297_cast_fp16 = conv(bias = const_202_to_fp16, dilations = input_295_dilations_0, groups = input_295_groups_0, pad = input_295_pad_0, pad_type = input_295_pad_type_0, strides = input_295_strides_0, weight = const_201_to_fp16, x = input_293_cast_fp16)[name = string("input_297_cast_fp16")];
            string input_299_pad_type_0 = const()[name = string("input_299_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_299_strides_0 = const()[name = string("input_299_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_299_pad_0 = const()[name = string("input_299_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631808)))];
            tensor<int32, [2]> input_299_dilations_0 = const()[name = string("input_299_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_299_groups_0 = const()[name = string("input_299_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_203_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631936))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636096))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636288)))];
            tensor<fp16, [64]> const_204_to_fp16 = const()[name = string("const_204_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636416)))];
            tensor<fp16, [1, 64, 32, 32]> input_301_cast_fp16 = conv(bias = const_204_to_fp16, dilations = input_299_dilations_0, groups = input_299_groups_0, pad = input_299_pad_0, pad_type = input_299_pad_type_0, strides = input_299_strides_0, weight = const_203_to_fp16, x = input_297_cast_fp16)[name = string("input_301_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_9_cast_fp16 = relu(x = input_301_cast_fp16)[name = string("out1_9_cast_fp16")];
            string input_305_pad_type_0 = const()[name = string("input_305_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_305_strides_0 = const()[name = string("input_305_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_305_pad_0 = const()[name = string("input_305_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636608)))];
            tensor<int32, [2]> input_305_dilations_0 = const()[name = string("input_305_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_305_groups_0 = const()[name = string("input_305_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_205_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(636736))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(640896))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641088)))];
            tensor<fp16, [64]> const_206_to_fp16 = const()[name = string("const_206_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641216)))];
            tensor<fp16, [1, 64, 32, 32]> input_307_cast_fp16 = conv(bias = const_206_to_fp16, dilations = input_305_dilations_0, groups = input_305_groups_0, pad = input_305_pad_0, pad_type = input_305_pad_type_0, strides = input_305_strides_0, weight = const_205_to_fp16, x = var_3384_cast_fp16)[name = string("input_307_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_309_cast_fp16 = relu(x = input_307_cast_fp16)[name = string("input_309_cast_fp16")];
            string input_311_pad_type_0 = const()[name = string("input_311_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_311_pad_0 = const()[name = string("input_311_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641408)))];
            int32 input_311_groups_0 = const()[name = string("input_311_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_311_strides_0 = const()[name = string("input_311_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_311_dilations_0 = const()[name = string("input_311_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_207_to_fp16 = const()[name = string("const_207_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(641536)))];
            tensor<fp16, [64]> const_208_to_fp16 = const()[name = string("const_208_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(644800)))];
            tensor<fp16, [1, 64, 32, 32]> input_313_cast_fp16 = conv(bias = const_208_to_fp16, dilations = input_311_dilations_0, groups = input_311_groups_0, pad = input_311_pad_0, pad_type = input_311_pad_type_0, strides = input_311_strides_0, weight = const_207_to_fp16, x = input_309_cast_fp16)[name = string("input_313_cast_fp16")];
            string input_315_pad_type_0 = const()[name = string("input_315_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_315_strides_0 = const()[name = string("input_315_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_315_pad_0 = const()[name = string("input_315_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(644992)))];
            tensor<int32, [2]> input_315_dilations_0 = const()[name = string("input_315_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_315_groups_0 = const()[name = string("input_315_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_209_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(645120))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649280))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649472)))];
            tensor<fp16, [64]> const_210_to_fp16 = const()[name = string("const_210_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649600)))];
            tensor<fp16, [1, 64, 32, 32]> input_317_cast_fp16 = conv(bias = const_210_to_fp16, dilations = input_315_dilations_0, groups = input_315_groups_0, pad = input_315_pad_0, pad_type = input_315_pad_type_0, strides = input_315_strides_0, weight = const_209_to_fp16, x = input_313_cast_fp16)[name = string("input_317_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_9_cast_fp16 = relu(x = input_317_cast_fp16)[name = string("out2_9_cast_fp16")];
            string input_321_pad_type_0 = const()[name = string("input_321_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_321_strides_0 = const()[name = string("input_321_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_321_pad_0 = const()[name = string("input_321_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649792)))];
            tensor<int32, [2]> input_321_dilations_0 = const()[name = string("input_321_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_321_groups_0 = const()[name = string("input_321_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_211_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(649920))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654080))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654272)))];
            tensor<fp16, [64]> const_212_to_fp16 = const()[name = string("const_212_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654400)))];
            tensor<fp16, [1, 64, 32, 32]> input_323_cast_fp16 = conv(bias = const_212_to_fp16, dilations = input_321_dilations_0, groups = input_321_groups_0, pad = input_321_pad_0, pad_type = input_321_pad_type_0, strides = input_321_strides_0, weight = const_211_to_fp16, x = var_3388_cast_fp16)[name = string("input_323_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_325_cast_fp16 = relu(x = input_323_cast_fp16)[name = string("input_325_cast_fp16")];
            string input_327_pad_type_0 = const()[name = string("input_327_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_327_pad_0 = const()[name = string("input_327_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654592)))];
            int32 input_327_groups_0 = const()[name = string("input_327_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_327_strides_0 = const()[name = string("input_327_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_327_dilations_0 = const()[name = string("input_327_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_213_to_fp16 = const()[name = string("const_213_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(654720)))];
            tensor<fp16, [64]> const_214_to_fp16 = const()[name = string("const_214_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(657984)))];
            tensor<fp16, [1, 64, 32, 32]> input_329_cast_fp16 = conv(bias = const_214_to_fp16, dilations = input_327_dilations_0, groups = input_327_groups_0, pad = input_327_pad_0, pad_type = input_327_pad_type_0, strides = input_327_strides_0, weight = const_213_to_fp16, x = input_325_cast_fp16)[name = string("input_329_cast_fp16")];
            string input_331_pad_type_0 = const()[name = string("input_331_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_331_strides_0 = const()[name = string("input_331_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_331_pad_0 = const()[name = string("input_331_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658176)))];
            tensor<int32, [2]> input_331_dilations_0 = const()[name = string("input_331_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_331_groups_0 = const()[name = string("input_331_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_215_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658304))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662464))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662656)))];
            tensor<fp16, [64]> const_216_to_fp16 = const()[name = string("const_216_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662784)))];
            tensor<fp16, [1, 64, 32, 32]> input_333_cast_fp16 = conv(bias = const_216_to_fp16, dilations = input_331_dilations_0, groups = input_331_groups_0, pad = input_331_pad_0, pad_type = input_331_pad_type_0, strides = input_331_strides_0, weight = const_215_to_fp16, x = input_329_cast_fp16)[name = string("input_333_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_9_cast_fp16 = relu(x = input_333_cast_fp16)[name = string("out3_9_cast_fp16")];
            bool input_335_interleave_0 = const()[name = string("input_335_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_335_cast_fp16 = concat(axis = var_86, interleave = input_335_interleave_0, values = (var_3376_cast_fp16, out1_9_cast_fp16, out2_9_cast_fp16, out3_9_cast_fp16))[name = string("input_335_cast_fp16")];
            string input_337_pad_type_0 = const()[name = string("input_337_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_337_strides_0 = const()[name = string("input_337_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_337_pad_0 = const()[name = string("input_337_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(662976)))];
            tensor<int32, [2]> input_337_dilations_0 = const()[name = string("input_337_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_337_groups_0 = const()[name = string("input_337_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_217_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(663104))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(728704))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729280)))];
            tensor<fp16, [256]> const_218_to_fp16 = const()[name = string("const_218_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729600)))];
            tensor<fp16, [1, 256, 32, 32]> input_339_cast_fp16 = conv(bias = const_218_to_fp16, dilations = input_337_dilations_0, groups = input_337_groups_0, pad = input_337_pad_0, pad_type = input_337_pad_type_0, strides = input_337_strides_0, weight = const_217_to_fp16, x = input_335_cast_fp16)[name = string("input_339_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_341_cast_fp16 = relu(x = input_339_cast_fp16)[name = string("input_341_cast_fp16")];
            string input_343_pad_type_0 = const()[name = string("input_343_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_343_pad_0 = const()[name = string("input_343_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(730176)))];
            int32 input_343_groups_0 = const()[name = string("input_343_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_343_strides_0 = const()[name = string("input_343_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_343_dilations_0 = const()[name = string("input_343_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 5, 5]> const_219_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(730304))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(736768))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(737344)))];
            tensor<fp16, [256]> const_220_to_fp16 = const()[name = string("const_220_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(737664)))];
            tensor<fp16, [1, 256, 32, 32]> input_345_cast_fp16 = conv(bias = const_220_to_fp16, dilations = input_343_dilations_0, groups = input_343_groups_0, pad = input_343_pad_0, pad_type = input_343_pad_type_0, strides = input_343_strides_0, weight = const_219_to_fp16, x = input_341_cast_fp16)[name = string("input_345_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_347_cast_fp16 = relu(x = input_345_cast_fp16)[name = string("input_347_cast_fp16")];
            string input_349_pad_type_0 = const()[name = string("input_349_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_349_strides_0 = const()[name = string("input_349_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_349_pad_0 = const()[name = string("input_349_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(738240)))];
            tensor<int32, [2]> input_349_dilations_0 = const()[name = string("input_349_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_349_groups_0 = const()[name = string("input_349_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> const_221_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(738368))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(803968))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(804544)))];
            tensor<fp16, [256]> const_222_to_fp16 = const()[name = string("const_222_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(804864)))];
            tensor<fp16, [1, 256, 32, 32]> y_7_cast_fp16 = conv(bias = const_222_to_fp16, dilations = input_349_dilations_0, groups = input_349_groups_0, pad = input_349_pad_0, pad_type = input_349_pad_type_0, strides = input_349_strides_0, weight = const_221_to_fp16, x = input_347_cast_fp16)[name = string("y_7_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_11_cast_fp16 = add(x = input_335_cast_fp16, y = y_7_cast_fp16)[name = string("x_11_cast_fp16")];
            tensor<int32, [4]> var_3488_begin_0 = const()[name = string("op_3488_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805440)))];
            tensor<int32, [4]> var_3488_end_0 = const()[name = string("op_3488_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805568)))];
            tensor<bool, [4]> var_3488_end_mask_0 = const()[name = string("op_3488_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3488_cast_fp16 = slice_by_index(begin = var_3488_begin_0, end = var_3488_end_0, end_mask = var_3488_end_mask_0, x = x_11_cast_fp16)[name = string("op_3488_cast_fp16")];
            tensor<int32, [4]> var_3492_begin_0 = const()[name = string("op_3492_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805696)))];
            tensor<int32, [4]> var_3492_end_0 = const()[name = string("op_3492_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805824)))];
            tensor<bool, [4]> var_3492_end_mask_0 = const()[name = string("op_3492_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3492_cast_fp16 = slice_by_index(begin = var_3492_begin_0, end = var_3492_end_0, end_mask = var_3492_end_mask_0, x = x_11_cast_fp16)[name = string("op_3492_cast_fp16")];
            tensor<int32, [4]> var_3496_begin_0 = const()[name = string("op_3496_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(805952)))];
            tensor<int32, [4]> var_3496_end_0 = const()[name = string("op_3496_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806080)))];
            tensor<bool, [4]> var_3496_end_mask_0 = const()[name = string("op_3496_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3496_cast_fp16 = slice_by_index(begin = var_3496_begin_0, end = var_3496_end_0, end_mask = var_3496_end_mask_0, x = x_11_cast_fp16)[name = string("op_3496_cast_fp16")];
            tensor<int32, [4]> var_3500_begin_0 = const()[name = string("op_3500_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806208)))];
            tensor<int32, [4]> var_3500_end_0 = const()[name = string("op_3500_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806336)))];
            tensor<bool, [4]> var_3500_end_mask_0 = const()[name = string("op_3500_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_3500_cast_fp16 = slice_by_index(begin = var_3500_begin_0, end = var_3500_end_0, end_mask = var_3500_end_mask_0, x = x_11_cast_fp16)[name = string("op_3500_cast_fp16")];
            string input_353_pad_type_0 = const()[name = string("input_353_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_353_strides_0 = const()[name = string("input_353_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_353_pad_0 = const()[name = string("input_353_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806464)))];
            tensor<int32, [2]> input_353_dilations_0 = const()[name = string("input_353_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_353_groups_0 = const()[name = string("input_353_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_223_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806592))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(810752))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(810944)))];
            tensor<fp16, [64]> const_224_to_fp16 = const()[name = string("const_224_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811072)))];
            tensor<fp16, [1, 64, 32, 32]> input_355_cast_fp16 = conv(bias = const_224_to_fp16, dilations = input_353_dilations_0, groups = input_353_groups_0, pad = input_353_pad_0, pad_type = input_353_pad_type_0, strides = input_353_strides_0, weight = const_223_to_fp16, x = var_3492_cast_fp16)[name = string("input_355_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_357_cast_fp16 = relu(x = input_355_cast_fp16)[name = string("input_357_cast_fp16")];
            string input_359_pad_type_0 = const()[name = string("input_359_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_359_pad_0 = const()[name = string("input_359_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811264)))];
            int32 input_359_groups_0 = const()[name = string("input_359_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_359_strides_0 = const()[name = string("input_359_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_359_dilations_0 = const()[name = string("input_359_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_225_to_fp16 = const()[name = string("const_225_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(811392)))];
            tensor<fp16, [64]> const_226_to_fp16 = const()[name = string("const_226_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814656)))];
            tensor<fp16, [1, 64, 32, 32]> input_361_cast_fp16 = conv(bias = const_226_to_fp16, dilations = input_359_dilations_0, groups = input_359_groups_0, pad = input_359_pad_0, pad_type = input_359_pad_type_0, strides = input_359_strides_0, weight = const_225_to_fp16, x = input_357_cast_fp16)[name = string("input_361_cast_fp16")];
            string input_363_pad_type_0 = const()[name = string("input_363_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_363_strides_0 = const()[name = string("input_363_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_363_pad_0 = const()[name = string("input_363_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814848)))];
            tensor<int32, [2]> input_363_dilations_0 = const()[name = string("input_363_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_363_groups_0 = const()[name = string("input_363_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_227_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814976))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819136))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819328)))];
            tensor<fp16, [64]> const_228_to_fp16 = const()[name = string("const_228_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819456)))];
            tensor<fp16, [1, 64, 32, 32]> input_365_cast_fp16 = conv(bias = const_228_to_fp16, dilations = input_363_dilations_0, groups = input_363_groups_0, pad = input_363_pad_0, pad_type = input_363_pad_type_0, strides = input_363_strides_0, weight = const_227_to_fp16, x = input_361_cast_fp16)[name = string("input_365_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_11_cast_fp16 = relu(x = input_365_cast_fp16)[name = string("out1_11_cast_fp16")];
            string input_369_pad_type_0 = const()[name = string("input_369_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_369_strides_0 = const()[name = string("input_369_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_369_pad_0 = const()[name = string("input_369_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819648)))];
            tensor<int32, [2]> input_369_dilations_0 = const()[name = string("input_369_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_369_groups_0 = const()[name = string("input_369_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_229_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(819776))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(823936))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824128)))];
            tensor<fp16, [64]> const_230_to_fp16 = const()[name = string("const_230_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824256)))];
            tensor<fp16, [1, 64, 32, 32]> input_371_cast_fp16 = conv(bias = const_230_to_fp16, dilations = input_369_dilations_0, groups = input_369_groups_0, pad = input_369_pad_0, pad_type = input_369_pad_type_0, strides = input_369_strides_0, weight = const_229_to_fp16, x = var_3496_cast_fp16)[name = string("input_371_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_373_cast_fp16 = relu(x = input_371_cast_fp16)[name = string("input_373_cast_fp16")];
            string input_375_pad_type_0 = const()[name = string("input_375_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_375_pad_0 = const()[name = string("input_375_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824448)))];
            int32 input_375_groups_0 = const()[name = string("input_375_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_375_strides_0 = const()[name = string("input_375_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_375_dilations_0 = const()[name = string("input_375_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_231_to_fp16 = const()[name = string("const_231_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(824576)))];
            tensor<fp16, [64]> const_232_to_fp16 = const()[name = string("const_232_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(827840)))];
            tensor<fp16, [1, 64, 32, 32]> input_377_cast_fp16 = conv(bias = const_232_to_fp16, dilations = input_375_dilations_0, groups = input_375_groups_0, pad = input_375_pad_0, pad_type = input_375_pad_type_0, strides = input_375_strides_0, weight = const_231_to_fp16, x = input_373_cast_fp16)[name = string("input_377_cast_fp16")];
            string input_379_pad_type_0 = const()[name = string("input_379_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_379_strides_0 = const()[name = string("input_379_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_379_pad_0 = const()[name = string("input_379_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(828032)))];
            tensor<int32, [2]> input_379_dilations_0 = const()[name = string("input_379_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_379_groups_0 = const()[name = string("input_379_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_233_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(828160))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832320))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832512)))];
            tensor<fp16, [64]> const_234_to_fp16 = const()[name = string("const_234_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832640)))];
            tensor<fp16, [1, 64, 32, 32]> input_381_cast_fp16 = conv(bias = const_234_to_fp16, dilations = input_379_dilations_0, groups = input_379_groups_0, pad = input_379_pad_0, pad_type = input_379_pad_type_0, strides = input_379_strides_0, weight = const_233_to_fp16, x = input_377_cast_fp16)[name = string("input_381_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_11_cast_fp16 = relu(x = input_381_cast_fp16)[name = string("out2_11_cast_fp16")];
            string input_385_pad_type_0 = const()[name = string("input_385_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_385_strides_0 = const()[name = string("input_385_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_385_pad_0 = const()[name = string("input_385_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832832)))];
            tensor<int32, [2]> input_385_dilations_0 = const()[name = string("input_385_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_385_groups_0 = const()[name = string("input_385_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_235_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832960))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837120))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837312)))];
            tensor<fp16, [64]> const_236_to_fp16 = const()[name = string("const_236_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837440)))];
            tensor<fp16, [1, 64, 32, 32]> input_387_cast_fp16 = conv(bias = const_236_to_fp16, dilations = input_385_dilations_0, groups = input_385_groups_0, pad = input_385_pad_0, pad_type = input_385_pad_type_0, strides = input_385_strides_0, weight = const_235_to_fp16, x = var_3500_cast_fp16)[name = string("input_387_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_389_cast_fp16 = relu(x = input_387_cast_fp16)[name = string("input_389_cast_fp16")];
            string input_391_pad_type_0 = const()[name = string("input_391_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_391_pad_0 = const()[name = string("input_391_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837632)))];
            int32 input_391_groups_0 = const()[name = string("input_391_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_391_strides_0 = const()[name = string("input_391_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_391_dilations_0 = const()[name = string("input_391_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64, 1, 5, 5]> const_237_to_fp16 = const()[name = string("const_237_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(837760)))];
            tensor<fp16, [64]> const_238_to_fp16 = const()[name = string("const_238_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841024)))];
            tensor<fp16, [1, 64, 32, 32]> input_393_cast_fp16 = conv(bias = const_238_to_fp16, dilations = input_391_dilations_0, groups = input_391_groups_0, pad = input_391_pad_0, pad_type = input_391_pad_type_0, strides = input_391_strides_0, weight = const_237_to_fp16, x = input_389_cast_fp16)[name = string("input_393_cast_fp16")];
            string input_395_pad_type_0 = const()[name = string("input_395_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_395_strides_0 = const()[name = string("input_395_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_395_pad_0 = const()[name = string("input_395_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841216)))];
            tensor<int32, [2]> input_395_dilations_0 = const()[name = string("input_395_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_395_groups_0 = const()[name = string("input_395_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> const_239_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(841344))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845504))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845696)))];
            tensor<fp16, [64]> const_240_to_fp16 = const()[name = string("const_240_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(845824)))];
            tensor<fp16, [1, 64, 32, 32]> input_397_cast_fp16 = conv(bias = const_240_to_fp16, dilations = input_395_dilations_0, groups = input_395_groups_0, pad = input_395_pad_0, pad_type = input_395_pad_type_0, strides = input_395_strides_0, weight = const_239_to_fp16, x = input_393_cast_fp16)[name = string("input_397_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_11_cast_fp16 = relu(x = input_397_cast_fp16)[name = string("out3_11_cast_fp16")];
            bool input_399_interleave_0 = const()[name = string("input_399_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_399_cast_fp16 = concat(axis = var_86, interleave = input_399_interleave_0, values = (var_3488_cast_fp16, out1_11_cast_fp16, out2_11_cast_fp16, out3_11_cast_fp16))[name = string("input_399_cast_fp16")];
            string input_401_pad_type_0 = const()[name = string("input_401_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_401_strides_0 = const()[name = string("input_401_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_401_pad_0 = const()[name = string("input_401_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846016)))];
            tensor<int32, [2]> input_401_dilations_0 = const()[name = string("input_401_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_401_groups_0 = const()[name = string("input_401_groups_0"), val = int32(1)];
            tensor<fp16, [512, 256, 1, 1]> const_241_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846144))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(977280))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(978368)))];
            tensor<fp16, [512]> const_242_to_fp16 = const()[name = string("const_242_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(978944)))];
            tensor<fp16, [1, 512, 32, 32]> input_403_cast_fp16 = conv(bias = const_242_to_fp16, dilations = input_401_dilations_0, groups = input_401_groups_0, pad = input_401_pad_0, pad_type = input_401_pad_type_0, strides = input_401_strides_0, weight = const_241_to_fp16, x = input_399_cast_fp16)[name = string("input_403_cast_fp16")];
            tensor<fp16, [1, 512, 32, 32]> input_405_cast_fp16 = relu(x = input_403_cast_fp16)[name = string("input_405_cast_fp16")];
            string input_407_pad_type_0 = const()[name = string("input_407_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_407_pad_0 = const()[name = string("input_407_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(980032)))];
            tensor<int32, [2]> input_407_strides_0 = const()[name = string("input_407_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_407_groups_0 = const()[name = string("input_407_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_407_dilations_0 = const()[name = string("input_407_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [512, 1, 5, 5]> const_243_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(980160))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(993024))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(994112)))];
            tensor<fp16, [512]> const_244_to_fp16 = const()[name = string("const_244_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(994688)))];
            tensor<fp16, [1, 512, 16, 16]> input_409_cast_fp16 = conv(bias = const_244_to_fp16, dilations = input_407_dilations_0, groups = input_407_groups_0, pad = input_407_pad_0, pad_type = input_407_pad_type_0, strides = input_407_strides_0, weight = const_243_to_fp16, x = input_405_cast_fp16)[name = string("input_409_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_411_cast_fp16 = relu(x = input_409_cast_fp16)[name = string("input_411_cast_fp16")];
            string input_413_pad_type_0 = const()[name = string("input_413_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_413_strides_0 = const()[name = string("input_413_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_413_pad_0 = const()[name = string("input_413_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(995776)))];
            tensor<int32, [2]> input_413_dilations_0 = const()[name = string("input_413_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_413_groups_0 = const()[name = string("input_413_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_245_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(995904))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1258112))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1259200)))];
            tensor<fp16, [512]> const_246_to_fp16 = const()[name = string("const_246_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1259776)))];
            tensor<fp16, [1, 512, 16, 16]> x_13_cast_fp16 = conv(bias = const_246_to_fp16, dilations = input_413_dilations_0, groups = input_413_groups_0, pad = input_413_pad_0, pad_type = input_413_pad_type_0, strides = input_413_strides_0, weight = const_245_to_fp16, x = input_411_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<int32, [4]> var_3599_begin_0 = const()[name = string("op_3599_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1260864)))];
            tensor<int32, [4]> var_3599_end_0 = const()[name = string("op_3599_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1260992)))];
            tensor<bool, [4]> var_3599_end_mask_0 = const()[name = string("op_3599_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3599_cast_fp16 = slice_by_index(begin = var_3599_begin_0, end = var_3599_end_0, end_mask = var_3599_end_mask_0, x = x_13_cast_fp16)[name = string("op_3599_cast_fp16")];
            tensor<int32, [4]> var_3603_begin_0 = const()[name = string("op_3603_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261120)))];
            tensor<int32, [4]> var_3603_end_0 = const()[name = string("op_3603_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261248)))];
            tensor<bool, [4]> var_3603_end_mask_0 = const()[name = string("op_3603_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3603_cast_fp16 = slice_by_index(begin = var_3603_begin_0, end = var_3603_end_0, end_mask = var_3603_end_mask_0, x = x_13_cast_fp16)[name = string("op_3603_cast_fp16")];
            tensor<int32, [4]> var_3607_begin_0 = const()[name = string("op_3607_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261376)))];
            tensor<int32, [4]> var_3607_end_0 = const()[name = string("op_3607_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261504)))];
            tensor<bool, [4]> var_3607_end_mask_0 = const()[name = string("op_3607_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3607_cast_fp16 = slice_by_index(begin = var_3607_begin_0, end = var_3607_end_0, end_mask = var_3607_end_mask_0, x = x_13_cast_fp16)[name = string("op_3607_cast_fp16")];
            tensor<int32, [4]> var_3611_begin_0 = const()[name = string("op_3611_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261632)))];
            tensor<int32, [4]> var_3611_end_0 = const()[name = string("op_3611_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261760)))];
            tensor<bool, [4]> var_3611_end_mask_0 = const()[name = string("op_3611_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3611_cast_fp16 = slice_by_index(begin = var_3611_begin_0, end = var_3611_end_0, end_mask = var_3611_end_mask_0, x = x_13_cast_fp16)[name = string("op_3611_cast_fp16")];
            string input_417_pad_type_0 = const()[name = string("input_417_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_417_strides_0 = const()[name = string("input_417_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_417_pad_0 = const()[name = string("input_417_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1261888)))];
            tensor<int32, [2]> input_417_dilations_0 = const()[name = string("input_417_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_417_groups_0 = const()[name = string("input_417_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_247_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1262016))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278464))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278784)))];
            tensor<fp16, [128]> const_248_to_fp16 = const()[name = string("const_248_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1278976)))];
            tensor<fp16, [1, 128, 16, 16]> input_419_cast_fp16 = conv(bias = const_248_to_fp16, dilations = input_417_dilations_0, groups = input_417_groups_0, pad = input_417_pad_0, pad_type = input_417_pad_type_0, strides = input_417_strides_0, weight = const_247_to_fp16, x = var_3603_cast_fp16)[name = string("input_419_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_421_cast_fp16 = relu(x = input_419_cast_fp16)[name = string("input_421_cast_fp16")];
            string input_423_pad_type_0 = const()[name = string("input_423_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_423_pad_0 = const()[name = string("input_423_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1279296)))];
            int32 input_423_groups_0 = const()[name = string("input_423_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_423_strides_0 = const()[name = string("input_423_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_423_dilations_0 = const()[name = string("input_423_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_249_to_fp16 = const()[name = string("const_249_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1279424)))];
            tensor<fp16, [128]> const_250_to_fp16 = const()[name = string("const_250_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1285888)))];
            tensor<fp16, [1, 128, 16, 16]> input_425_cast_fp16 = conv(bias = const_250_to_fp16, dilations = input_423_dilations_0, groups = input_423_groups_0, pad = input_423_pad_0, pad_type = input_423_pad_type_0, strides = input_423_strides_0, weight = const_249_to_fp16, x = input_421_cast_fp16)[name = string("input_425_cast_fp16")];
            string input_427_pad_type_0 = const()[name = string("input_427_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_427_strides_0 = const()[name = string("input_427_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_427_pad_0 = const()[name = string("input_427_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1286208)))];
            tensor<int32, [2]> input_427_dilations_0 = const()[name = string("input_427_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_427_groups_0 = const()[name = string("input_427_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_251_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1286336))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1302784))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303104)))];
            tensor<fp16, [128]> const_252_to_fp16 = const()[name = string("const_252_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303296)))];
            tensor<fp16, [1, 128, 16, 16]> input_429_cast_fp16 = conv(bias = const_252_to_fp16, dilations = input_427_dilations_0, groups = input_427_groups_0, pad = input_427_pad_0, pad_type = input_427_pad_type_0, strides = input_427_strides_0, weight = const_251_to_fp16, x = input_425_cast_fp16)[name = string("input_429_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_13_cast_fp16 = relu(x = input_429_cast_fp16)[name = string("out1_13_cast_fp16")];
            string input_433_pad_type_0 = const()[name = string("input_433_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_433_strides_0 = const()[name = string("input_433_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_433_pad_0 = const()[name = string("input_433_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303616)))];
            tensor<int32, [2]> input_433_dilations_0 = const()[name = string("input_433_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_433_groups_0 = const()[name = string("input_433_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_253_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303744))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320192))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320512)))];
            tensor<fp16, [128]> const_254_to_fp16 = const()[name = string("const_254_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1320704)))];
            tensor<fp16, [1, 128, 16, 16]> input_435_cast_fp16 = conv(bias = const_254_to_fp16, dilations = input_433_dilations_0, groups = input_433_groups_0, pad = input_433_pad_0, pad_type = input_433_pad_type_0, strides = input_433_strides_0, weight = const_253_to_fp16, x = var_3607_cast_fp16)[name = string("input_435_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_437_cast_fp16 = relu(x = input_435_cast_fp16)[name = string("input_437_cast_fp16")];
            string input_439_pad_type_0 = const()[name = string("input_439_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_439_pad_0 = const()[name = string("input_439_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1321024)))];
            int32 input_439_groups_0 = const()[name = string("input_439_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_439_strides_0 = const()[name = string("input_439_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_439_dilations_0 = const()[name = string("input_439_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_255_to_fp16 = const()[name = string("const_255_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1321152)))];
            tensor<fp16, [128]> const_256_to_fp16 = const()[name = string("const_256_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1327616)))];
            tensor<fp16, [1, 128, 16, 16]> input_441_cast_fp16 = conv(bias = const_256_to_fp16, dilations = input_439_dilations_0, groups = input_439_groups_0, pad = input_439_pad_0, pad_type = input_439_pad_type_0, strides = input_439_strides_0, weight = const_255_to_fp16, x = input_437_cast_fp16)[name = string("input_441_cast_fp16")];
            string input_443_pad_type_0 = const()[name = string("input_443_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_443_strides_0 = const()[name = string("input_443_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_443_pad_0 = const()[name = string("input_443_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1327936)))];
            tensor<int32, [2]> input_443_dilations_0 = const()[name = string("input_443_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_443_groups_0 = const()[name = string("input_443_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_257_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1328064))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1344512))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1344832)))];
            tensor<fp16, [128]> const_258_to_fp16 = const()[name = string("const_258_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345024)))];
            tensor<fp16, [1, 128, 16, 16]> input_445_cast_fp16 = conv(bias = const_258_to_fp16, dilations = input_443_dilations_0, groups = input_443_groups_0, pad = input_443_pad_0, pad_type = input_443_pad_type_0, strides = input_443_strides_0, weight = const_257_to_fp16, x = input_441_cast_fp16)[name = string("input_445_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_13_cast_fp16 = relu(x = input_445_cast_fp16)[name = string("out2_13_cast_fp16")];
            string input_449_pad_type_0 = const()[name = string("input_449_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_449_strides_0 = const()[name = string("input_449_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_449_pad_0 = const()[name = string("input_449_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345344)))];
            tensor<int32, [2]> input_449_dilations_0 = const()[name = string("input_449_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_449_groups_0 = const()[name = string("input_449_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_259_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1345472))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1361920))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362240)))];
            tensor<fp16, [128]> const_260_to_fp16 = const()[name = string("const_260_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362432)))];
            tensor<fp16, [1, 128, 16, 16]> input_451_cast_fp16 = conv(bias = const_260_to_fp16, dilations = input_449_dilations_0, groups = input_449_groups_0, pad = input_449_pad_0, pad_type = input_449_pad_type_0, strides = input_449_strides_0, weight = const_259_to_fp16, x = var_3611_cast_fp16)[name = string("input_451_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_453_cast_fp16 = relu(x = input_451_cast_fp16)[name = string("input_453_cast_fp16")];
            string input_455_pad_type_0 = const()[name = string("input_455_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_455_pad_0 = const()[name = string("input_455_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362752)))];
            int32 input_455_groups_0 = const()[name = string("input_455_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_455_strides_0 = const()[name = string("input_455_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_455_dilations_0 = const()[name = string("input_455_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_261_to_fp16 = const()[name = string("const_261_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1362880)))];
            tensor<fp16, [128]> const_262_to_fp16 = const()[name = string("const_262_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369344)))];
            tensor<fp16, [1, 128, 16, 16]> input_457_cast_fp16 = conv(bias = const_262_to_fp16, dilations = input_455_dilations_0, groups = input_455_groups_0, pad = input_455_pad_0, pad_type = input_455_pad_type_0, strides = input_455_strides_0, weight = const_261_to_fp16, x = input_453_cast_fp16)[name = string("input_457_cast_fp16")];
            string input_459_pad_type_0 = const()[name = string("input_459_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_459_strides_0 = const()[name = string("input_459_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_459_pad_0 = const()[name = string("input_459_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369664)))];
            tensor<int32, [2]> input_459_dilations_0 = const()[name = string("input_459_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_459_groups_0 = const()[name = string("input_459_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_263_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1369792))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386240))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386560)))];
            tensor<fp16, [128]> const_264_to_fp16 = const()[name = string("const_264_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1386752)))];
            tensor<fp16, [1, 128, 16, 16]> input_461_cast_fp16 = conv(bias = const_264_to_fp16, dilations = input_459_dilations_0, groups = input_459_groups_0, pad = input_459_pad_0, pad_type = input_459_pad_type_0, strides = input_459_strides_0, weight = const_263_to_fp16, x = input_457_cast_fp16)[name = string("input_461_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_13_cast_fp16 = relu(x = input_461_cast_fp16)[name = string("out3_13_cast_fp16")];
            bool input_463_interleave_0 = const()[name = string("input_463_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_463_cast_fp16 = concat(axis = var_86, interleave = input_463_interleave_0, values = (var_3599_cast_fp16, out1_13_cast_fp16, out2_13_cast_fp16, out3_13_cast_fp16))[name = string("input_463_cast_fp16")];
            string input_465_pad_type_0 = const()[name = string("input_465_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_465_strides_0 = const()[name = string("input_465_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_465_pad_0 = const()[name = string("input_465_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1387072)))];
            tensor<int32, [2]> input_465_dilations_0 = const()[name = string("input_465_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_465_groups_0 = const()[name = string("input_465_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_265_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1387200))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1649408))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1650496)))];
            tensor<fp16, [512]> const_266_to_fp16 = const()[name = string("const_266_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1651072)))];
            tensor<fp16, [1, 512, 16, 16]> input_467_cast_fp16 = conv(bias = const_266_to_fp16, dilations = input_465_dilations_0, groups = input_465_groups_0, pad = input_465_pad_0, pad_type = input_465_pad_type_0, strides = input_465_strides_0, weight = const_265_to_fp16, x = input_463_cast_fp16)[name = string("input_467_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_469_cast_fp16 = relu(x = input_467_cast_fp16)[name = string("input_469_cast_fp16")];
            string input_471_pad_type_0 = const()[name = string("input_471_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_471_pad_0 = const()[name = string("input_471_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1652160)))];
            int32 input_471_groups_0 = const()[name = string("input_471_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_471_strides_0 = const()[name = string("input_471_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_471_dilations_0 = const()[name = string("input_471_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [512, 1, 5, 5]> const_267_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1652288))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1665152))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1666240)))];
            tensor<fp16, [512]> const_268_to_fp16 = const()[name = string("const_268_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1666816)))];
            tensor<fp16, [1, 512, 16, 16]> input_473_cast_fp16 = conv(bias = const_268_to_fp16, dilations = input_471_dilations_0, groups = input_471_groups_0, pad = input_471_pad_0, pad_type = input_471_pad_type_0, strides = input_471_strides_0, weight = const_267_to_fp16, x = input_469_cast_fp16)[name = string("input_473_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_475_cast_fp16 = relu(x = input_473_cast_fp16)[name = string("input_475_cast_fp16")];
            string input_477_pad_type_0 = const()[name = string("input_477_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_477_strides_0 = const()[name = string("input_477_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_477_pad_0 = const()[name = string("input_477_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1667904)))];
            tensor<int32, [2]> input_477_dilations_0 = const()[name = string("input_477_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_477_groups_0 = const()[name = string("input_477_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1, 1]> const_269_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1668032))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1930240))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1931328)))];
            tensor<fp16, [512]> const_270_to_fp16 = const()[name = string("const_270_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1931904)))];
            tensor<fp16, [1, 512, 16, 16]> y_9_cast_fp16 = conv(bias = const_270_to_fp16, dilations = input_477_dilations_0, groups = input_477_groups_0, pad = input_477_pad_0, pad_type = input_477_pad_type_0, strides = input_477_strides_0, weight = const_269_to_fp16, x = input_475_cast_fp16)[name = string("y_9_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> x_15_cast_fp16 = add(x = input_463_cast_fp16, y = y_9_cast_fp16)[name = string("x_15_cast_fp16")];
            tensor<int32, [4]> var_3711_begin_0 = const()[name = string("op_3711_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1932992)))];
            tensor<int32, [4]> var_3711_end_0 = const()[name = string("op_3711_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933120)))];
            tensor<bool, [4]> var_3711_end_mask_0 = const()[name = string("op_3711_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3711_cast_fp16 = slice_by_index(begin = var_3711_begin_0, end = var_3711_end_0, end_mask = var_3711_end_mask_0, x = x_15_cast_fp16)[name = string("op_3711_cast_fp16")];
            tensor<int32, [4]> var_3715_begin_0 = const()[name = string("op_3715_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933248)))];
            tensor<int32, [4]> var_3715_end_0 = const()[name = string("op_3715_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933376)))];
            tensor<bool, [4]> var_3715_end_mask_0 = const()[name = string("op_3715_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3715_cast_fp16 = slice_by_index(begin = var_3715_begin_0, end = var_3715_end_0, end_mask = var_3715_end_mask_0, x = x_15_cast_fp16)[name = string("op_3715_cast_fp16")];
            tensor<int32, [4]> var_3719_begin_0 = const()[name = string("op_3719_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933504)))];
            tensor<int32, [4]> var_3719_end_0 = const()[name = string("op_3719_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933632)))];
            tensor<bool, [4]> var_3719_end_mask_0 = const()[name = string("op_3719_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3719_cast_fp16 = slice_by_index(begin = var_3719_begin_0, end = var_3719_end_0, end_mask = var_3719_end_mask_0, x = x_15_cast_fp16)[name = string("op_3719_cast_fp16")];
            tensor<int32, [4]> var_3723_begin_0 = const()[name = string("op_3723_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933760)))];
            tensor<int32, [4]> var_3723_end_0 = const()[name = string("op_3723_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1933888)))];
            tensor<bool, [4]> var_3723_end_mask_0 = const()[name = string("op_3723_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_3723_cast_fp16 = slice_by_index(begin = var_3723_begin_0, end = var_3723_end_0, end_mask = var_3723_end_mask_0, x = x_15_cast_fp16)[name = string("op_3723_cast_fp16")];
            string input_481_pad_type_0 = const()[name = string("input_481_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_481_strides_0 = const()[name = string("input_481_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_481_pad_0 = const()[name = string("input_481_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1934016)))];
            tensor<int32, [2]> input_481_dilations_0 = const()[name = string("input_481_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_481_groups_0 = const()[name = string("input_481_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_271_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1934144))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1950592))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1950912)))];
            tensor<fp16, [128]> const_272_to_fp16 = const()[name = string("const_272_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951104)))];
            tensor<fp16, [1, 128, 16, 16]> input_483_cast_fp16 = conv(bias = const_272_to_fp16, dilations = input_481_dilations_0, groups = input_481_groups_0, pad = input_481_pad_0, pad_type = input_481_pad_type_0, strides = input_481_strides_0, weight = const_271_to_fp16, x = var_3715_cast_fp16)[name = string("input_483_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_485_cast_fp16 = relu(x = input_483_cast_fp16)[name = string("input_485_cast_fp16")];
            string input_487_pad_type_0 = const()[name = string("input_487_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_487_pad_0 = const()[name = string("input_487_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951424)))];
            int32 input_487_groups_0 = const()[name = string("input_487_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_487_strides_0 = const()[name = string("input_487_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_487_dilations_0 = const()[name = string("input_487_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_273_to_fp16 = const()[name = string("const_273_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1951552)))];
            tensor<fp16, [128]> const_274_to_fp16 = const()[name = string("const_274_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958016)))];
            tensor<fp16, [1, 128, 16, 16]> input_489_cast_fp16 = conv(bias = const_274_to_fp16, dilations = input_487_dilations_0, groups = input_487_groups_0, pad = input_487_pad_0, pad_type = input_487_pad_type_0, strides = input_487_strides_0, weight = const_273_to_fp16, x = input_485_cast_fp16)[name = string("input_489_cast_fp16")];
            string input_491_pad_type_0 = const()[name = string("input_491_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_491_strides_0 = const()[name = string("input_491_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_491_pad_0 = const()[name = string("input_491_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958336)))];
            tensor<int32, [2]> input_491_dilations_0 = const()[name = string("input_491_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_491_groups_0 = const()[name = string("input_491_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_275_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1958464))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1974912))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975232)))];
            tensor<fp16, [128]> const_276_to_fp16 = const()[name = string("const_276_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975424)))];
            tensor<fp16, [1, 128, 16, 16]> input_493_cast_fp16 = conv(bias = const_276_to_fp16, dilations = input_491_dilations_0, groups = input_491_groups_0, pad = input_491_pad_0, pad_type = input_491_pad_type_0, strides = input_491_strides_0, weight = const_275_to_fp16, x = input_489_cast_fp16)[name = string("input_493_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_15_cast_fp16 = relu(x = input_493_cast_fp16)[name = string("out1_15_cast_fp16")];
            string input_497_pad_type_0 = const()[name = string("input_497_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_497_strides_0 = const()[name = string("input_497_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_497_pad_0 = const()[name = string("input_497_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975744)))];
            tensor<int32, [2]> input_497_dilations_0 = const()[name = string("input_497_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_497_groups_0 = const()[name = string("input_497_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_277_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1975872))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992320))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992640)))];
            tensor<fp16, [128]> const_278_to_fp16 = const()[name = string("const_278_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1992832)))];
            tensor<fp16, [1, 128, 16, 16]> input_499_cast_fp16 = conv(bias = const_278_to_fp16, dilations = input_497_dilations_0, groups = input_497_groups_0, pad = input_497_pad_0, pad_type = input_497_pad_type_0, strides = input_497_strides_0, weight = const_277_to_fp16, x = var_3719_cast_fp16)[name = string("input_499_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_501_cast_fp16 = relu(x = input_499_cast_fp16)[name = string("input_501_cast_fp16")];
            string input_503_pad_type_0 = const()[name = string("input_503_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_503_pad_0 = const()[name = string("input_503_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1993152)))];
            int32 input_503_groups_0 = const()[name = string("input_503_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_503_strides_0 = const()[name = string("input_503_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_503_dilations_0 = const()[name = string("input_503_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_279_to_fp16 = const()[name = string("const_279_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1993280)))];
            tensor<fp16, [128]> const_280_to_fp16 = const()[name = string("const_280_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1999744)))];
            tensor<fp16, [1, 128, 16, 16]> input_505_cast_fp16 = conv(bias = const_280_to_fp16, dilations = input_503_dilations_0, groups = input_503_groups_0, pad = input_503_pad_0, pad_type = input_503_pad_type_0, strides = input_503_strides_0, weight = const_279_to_fp16, x = input_501_cast_fp16)[name = string("input_505_cast_fp16")];
            string input_507_pad_type_0 = const()[name = string("input_507_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_507_strides_0 = const()[name = string("input_507_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_507_pad_0 = const()[name = string("input_507_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2000064)))];
            tensor<int32, [2]> input_507_dilations_0 = const()[name = string("input_507_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_507_groups_0 = const()[name = string("input_507_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_281_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2000192))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2016640))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2016960)))];
            tensor<fp16, [128]> const_282_to_fp16 = const()[name = string("const_282_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017152)))];
            tensor<fp16, [1, 128, 16, 16]> input_509_cast_fp16 = conv(bias = const_282_to_fp16, dilations = input_507_dilations_0, groups = input_507_groups_0, pad = input_507_pad_0, pad_type = input_507_pad_type_0, strides = input_507_strides_0, weight = const_281_to_fp16, x = input_505_cast_fp16)[name = string("input_509_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_15_cast_fp16 = relu(x = input_509_cast_fp16)[name = string("out2_15_cast_fp16")];
            string input_513_pad_type_0 = const()[name = string("input_513_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_513_strides_0 = const()[name = string("input_513_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_513_pad_0 = const()[name = string("input_513_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017472)))];
            tensor<int32, [2]> input_513_dilations_0 = const()[name = string("input_513_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_513_groups_0 = const()[name = string("input_513_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_283_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2017600))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034048))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034368)))];
            tensor<fp16, [128]> const_284_to_fp16 = const()[name = string("const_284_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034560)))];
            tensor<fp16, [1, 128, 16, 16]> input_515_cast_fp16 = conv(bias = const_284_to_fp16, dilations = input_513_dilations_0, groups = input_513_groups_0, pad = input_513_pad_0, pad_type = input_513_pad_type_0, strides = input_513_strides_0, weight = const_283_to_fp16, x = var_3723_cast_fp16)[name = string("input_515_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_517_cast_fp16 = relu(x = input_515_cast_fp16)[name = string("input_517_cast_fp16")];
            string input_519_pad_type_0 = const()[name = string("input_519_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_519_pad_0 = const()[name = string("input_519_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2034880)))];
            int32 input_519_groups_0 = const()[name = string("input_519_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_519_strides_0 = const()[name = string("input_519_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_519_dilations_0 = const()[name = string("input_519_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 5, 5]> const_285_to_fp16 = const()[name = string("const_285_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2035008)))];
            tensor<fp16, [128]> const_286_to_fp16 = const()[name = string("const_286_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041472)))];
            tensor<fp16, [1, 128, 16, 16]> input_521_cast_fp16 = conv(bias = const_286_to_fp16, dilations = input_519_dilations_0, groups = input_519_groups_0, pad = input_519_pad_0, pad_type = input_519_pad_type_0, strides = input_519_strides_0, weight = const_285_to_fp16, x = input_517_cast_fp16)[name = string("input_521_cast_fp16")];
            string input_523_pad_type_0 = const()[name = string("input_523_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_523_strides_0 = const()[name = string("input_523_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_523_pad_0 = const()[name = string("input_523_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041792)))];
            tensor<int32, [2]> input_523_dilations_0 = const()[name = string("input_523_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_523_groups_0 = const()[name = string("input_523_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_287_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2041920))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058368))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058688)))];
            tensor<fp16, [128]> const_288_to_fp16 = const()[name = string("const_288_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2058880)))];
            tensor<fp16, [1, 128, 16, 16]> input_525_cast_fp16 = conv(bias = const_288_to_fp16, dilations = input_523_dilations_0, groups = input_523_groups_0, pad = input_523_pad_0, pad_type = input_523_pad_type_0, strides = input_523_strides_0, weight = const_287_to_fp16, x = input_521_cast_fp16)[name = string("input_525_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_15_cast_fp16 = relu(x = input_525_cast_fp16)[name = string("out3_15_cast_fp16")];
            bool input_527_interleave_0 = const()[name = string("input_527_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_527_cast_fp16 = concat(axis = var_86, interleave = input_527_interleave_0, values = (var_3711_cast_fp16, out1_15_cast_fp16, out2_15_cast_fp16, out3_15_cast_fp16))[name = string("input_527_cast_fp16")];
            string input_529_pad_type_0 = const()[name = string("input_529_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_529_strides_0 = const()[name = string("input_529_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_529_pad_0 = const()[name = string("input_529_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2059200)))];
            tensor<int32, [2]> input_529_dilations_0 = const()[name = string("input_529_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_529_groups_0 = const()[name = string("input_529_groups_0"), val = int32(1)];
            tensor<fp16, [128, 512, 1, 1]> model_key_encoder_xfpn_p5_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2059328))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2124928))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125248)))];
            tensor<fp16, [1, 128, 16, 16]> input_529_cast_fp16 = conv(dilations = input_529_dilations_0, groups = input_529_groups_0, pad = input_529_pad_0, pad_type = input_529_pad_type_0, strides = input_529_strides_0, weight = model_key_encoder_xfpn_p5_1x1_weight_to_fp16, x = input_527_cast_fp16)[name = string("input_529_cast_fp16")];
            fp32 y_11_scale_factor_height_0 = const()[name = string("y_11_scale_factor_height_0"), val = fp32(2)];
            fp32 y_11_scale_factor_width_0 = const()[name = string("y_11_scale_factor_width_0"), val = fp32(2)];
            tensor<fp16, [1, 128, 32, 32]> y_11_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = y_11_scale_factor_height_0, scale_factor_width = y_11_scale_factor_width_0, x = input_529_cast_fp16)[name = string("y_11_cast_fp16")];
            string x_17_pad_type_0 = const()[name = string("x_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_17_strides_0 = const()[name = string("x_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_17_pad_0 = const()[name = string("x_17_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125440)))];
            tensor<int32, [2]> x_17_dilations_0 = const()[name = string("x_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_17_groups_0 = const()[name = string("x_17_groups_0"), val = int32(1)];
            tensor<fp16, [128, 256, 1, 1]> model_key_encoder_xfpn_p4_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2125568))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158400))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158720)))];
            tensor<fp16, [1, 128, 32, 32]> x_17_cast_fp16 = conv(dilations = x_17_dilations_0, groups = x_17_groups_0, pad = x_17_pad_0, pad_type = x_17_pad_type_0, strides = x_17_strides_0, weight = model_key_encoder_xfpn_p4_1x1_weight_to_fp16, x = input_399_cast_fp16)[name = string("x_17_cast_fp16")];
            tensor<fp16, [1, 128, 32, 32]> input_531_cast_fp16 = add(x = x_17_cast_fp16, y = y_11_cast_fp16)[name = string("input_531_cast_fp16")];
            string input_631_pad_type_0 = const()[name = string("input_631_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_631_pad_0 = const()[name = string("input_631_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2158912)))];
            int32 input_631_groups_0 = const()[name = string("input_631_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_631_strides_0 = const()[name = string("input_631_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_631_dilations_0 = const()[name = string("input_631_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> model_key_encoder_xfpn_fpn_output4_weight_to_fp16 = const()[name = string("model_key_encoder_xfpn_fpn_output4_weight_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2159040)))];
            tensor<fp16, [1, 128, 32, 32]> input_631_cast_fp16 = conv(dilations = input_631_dilations_0, groups = input_631_groups_0, pad = input_631_pad_0, pad_type = input_631_pad_type_0, strides = input_631_strides_0, weight = model_key_encoder_xfpn_fpn_output4_weight_to_fp16, x = input_531_cast_fp16)[name = string("input_631_cast_fp16")];
            string key_k_pad_type_0 = const()[name = string("key_k_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> key_k_pad_0 = const()[name = string("key_k_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2161408)))];
            tensor<int32, [2]> key_k_strides_0 = const()[name = string("key_k_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> key_k_dilations_0 = const()[name = string("key_k_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 key_k_groups_0 = const()[name = string("key_k_groups_0"), val = int32(1)];
            tensor<fp16, [64, 128, 3, 3]> model_key_proj_key_proj_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2161536))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235328))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235520)))];
            tensor<fp16, [64]> model_key_proj_key_proj_bias_to_fp16 = const()[name = string("model_key_proj_key_proj_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235648)))];
            tensor<fp16, [1, 64, 32, 32]> key_k_cast_fp16 = conv(bias = model_key_proj_key_proj_bias_to_fp16, dilations = key_k_dilations_0, groups = key_k_groups_0, pad = key_k_pad_0, pad_type = key_k_pad_type_0, strides = key_k_strides_0, weight = model_key_proj_key_proj_weight_to_fp16, x = input_631_cast_fp16)[name = string("key_k_cast_fp16")];
            tensor<fp16, [1, 1, 512, 512]> other_masks_1_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [1, 1, 512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2235840))), scale = tensor<fp16, [1]>([0]), zero_point = tensor<int8, [1]>([0])];
            tensor<fp16, [24, 2, 3, 3]> model_value_encoder_mask_conv_weight_to_fp16 = const()[name = string("model_value_encoder_mask_conv_weight_to_fp16"), val = tensor<fp16, [24, 2, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2498176)))];
            tensor<fp16, [24]> model_value_encoder_mask_conv_bias_to_fp16 = const()[name = string("model_value_encoder_mask_conv_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2499136)))];
            string input_637_pad_type_0 = const()[name = string("input_637_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_637_strides_0 = const()[name = string("input_637_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_637_pad_0 = const()[name = string("input_637_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2499264)))];
            tensor<int32, [2]> input_637_dilations_0 = const()[name = string("input_637_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_637_groups_0 = const()[name = string("input_637_groups_0"), val = int32(1)];
            tensor<fp16, [24, 3, 3, 3]> const_289_to_fp16 = const()[name = string("const_289_to_fp16"), val = tensor<fp16, [24, 3, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2499392)))];
            tensor<fp16, [24]> const_290_to_fp16 = const()[name = string("const_290_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2500800)))];
            tensor<fp16, [1, 24, 256, 256]> input_639_cast_fp16 = conv(bias = const_290_to_fp16, dilations = input_637_dilations_0, groups = input_637_groups_0, pad = input_637_pad_0, pad_type = input_637_pad_type_0, strides = input_637_strides_0, weight = const_289_to_fp16, x = input_3_cast_fp16)[name = string("input_639_cast_fp16")];
            tensor<fp16, [1, 24, 256, 256]> x_33_cast_fp16 = relu(x = input_639_cast_fp16)[name = string("x_33_cast_fp16")];
            tensor<fp16, [144, 24, 1, 1]> const_291_to_fp16 = const()[name = string("const_291_to_fp16"), val = tensor<fp16, [144, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2501184)))];
            tensor<fp16, [144]> const_292_to_fp16 = const()[name = string("const_292_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2508160)))];
            tensor<fp16, [144, 1, 5, 5]> const_293_to_fp16 = const()[name = string("const_293_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2508672)))];
            tensor<fp16, [144]> const_294_to_fp16 = const()[name = string("const_294_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2515968)))];
            tensor<fp16, [144, 144, 1, 1]> const_295_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2516480))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2537280))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2537664)))];
            tensor<fp16, [144]> const_296_to_fp16 = const()[name = string("const_296_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2537920)))];
            tensor<fp16, [36, 36, 1, 1]> const_297_to_fp16 = const()[name = string("const_297_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2539456)))];
            tensor<fp16, [36, 1, 5, 5]> const_299_to_fp16 = const()[name = string("const_299_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2542464)))];
            tensor<fp16, [36, 36, 1, 1]> const_301_to_fp16 = const()[name = string("const_301_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2544704)))];
            tensor<fp16, [36, 36, 1, 1]> const_303_to_fp16 = const()[name = string("const_303_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2547712)))];
            tensor<fp16, [36, 1, 5, 5]> const_305_to_fp16 = const()[name = string("const_305_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2550720)))];
            tensor<fp16, [36, 36, 1, 1]> const_307_to_fp16 = const()[name = string("const_307_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2552960)))];
            tensor<fp16, [36, 36, 1, 1]> const_309_to_fp16 = const()[name = string("const_309_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2555968)))];
            tensor<fp16, [36, 1, 5, 5]> const_311_to_fp16 = const()[name = string("const_311_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2558976)))];
            tensor<fp16, [36, 36, 1, 1]> const_313_to_fp16 = const()[name = string("const_313_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2561216)))];
            tensor<fp16, [144, 144, 1, 1]> const_315_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2564224))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2585024))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2585408)))];
            tensor<fp16, [144]> const_316_to_fp16 = const()[name = string("const_316_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2585664)))];
            tensor<fp16, [144, 1, 5, 5]> const_317_to_fp16 = const()[name = string("const_317_to_fp16"), val = tensor<fp16, [144, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2586176)))];
            tensor<fp16, [144]> const_318_to_fp16 = const()[name = string("const_318_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2593472)))];
            tensor<fp16, [144, 144, 1, 1]> const_319_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [144, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2593984))), scale = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2614784))), zero_point = tensor<int8, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2615168)))];
            tensor<fp16, [144]> const_320_to_fp16 = const()[name = string("const_320_to_fp16"), val = tensor<fp16, [144]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2615424)))];
            tensor<fp16, [36, 36, 1, 1]> const_321_to_fp16 = const()[name = string("const_321_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2616960)))];
            tensor<fp16, [36, 1, 5, 5]> const_323_to_fp16 = const()[name = string("const_323_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2619968)))];
            tensor<fp16, [36, 36, 1, 1]> const_325_to_fp16 = const()[name = string("const_325_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2622208)))];
            tensor<fp16, [36, 36, 1, 1]> const_327_to_fp16 = const()[name = string("const_327_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2625216)))];
            tensor<fp16, [36, 1, 5, 5]> const_329_to_fp16 = const()[name = string("const_329_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2628224)))];
            tensor<fp16, [36, 36, 1, 1]> const_331_to_fp16 = const()[name = string("const_331_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2630464)))];
            tensor<fp16, [36, 36, 1, 1]> const_333_to_fp16 = const()[name = string("const_333_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2633472)))];
            tensor<fp16, [36, 1, 5, 5]> const_335_to_fp16 = const()[name = string("const_335_to_fp16"), val = tensor<fp16, [36, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2636480)))];
            tensor<fp16, [36, 36, 1, 1]> const_337_to_fp16 = const()[name = string("const_337_to_fp16"), val = tensor<fp16, [36, 36, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2638720)))];
            tensor<fp16, [256, 144, 1, 1]> const_339_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2641728))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2678656))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2679232)))];
            tensor<fp16, [256]> const_340_to_fp16 = const()[name = string("const_340_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2679552)))];
            tensor<fp16, [256, 1, 5, 5]> const_341_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2680256))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2686720))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687296)))];
            tensor<fp16, [256]> const_342_to_fp16 = const()[name = string("const_342_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687616)))];
            tensor<fp16, [256, 256, 1, 1]> const_343_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2688320))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2753920))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2754496)))];
            tensor<fp16, [256]> const_344_to_fp16 = const()[name = string("const_344_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2754816)))];
            tensor<fp16, [64, 64, 1, 1]> const_345_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2756544))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2760704))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2760896)))];
            tensor<fp16, [64, 1, 5, 5]> const_347_to_fp16 = const()[name = string("const_347_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2761344)))];
            tensor<fp16, [64, 64, 1, 1]> const_349_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2764928))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2769088))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2769280)))];
            tensor<fp16, [64, 64, 1, 1]> const_351_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2769728))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2773888))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2774080)))];
            tensor<fp16, [64, 1, 5, 5]> const_353_to_fp16 = const()[name = string("const_353_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2774528)))];
            tensor<fp16, [64, 64, 1, 1]> const_355_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2778112))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2782272))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2782464)))];
            tensor<fp16, [64, 64, 1, 1]> const_357_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2782912))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2787072))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2787264)))];
            tensor<fp16, [64, 1, 5, 5]> const_359_to_fp16 = const()[name = string("const_359_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2787712)))];
            tensor<fp16, [64, 64, 1, 1]> const_361_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2791296))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2795456))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2795648)))];
            tensor<fp16, [256, 256, 1, 1]> const_363_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2796096))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2861696))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2862272)))];
            tensor<fp16, [256]> const_364_to_fp16 = const()[name = string("const_364_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2862592)))];
            tensor<fp16, [256, 1, 5, 5]> const_365_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2863296))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2869760))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2870336)))];
            tensor<fp16, [256]> const_366_to_fp16 = const()[name = string("const_366_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2870656)))];
            tensor<fp16, [256, 256, 1, 1]> const_367_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2871360))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2936960))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2937536)))];
            tensor<fp16, [256]> const_368_to_fp16 = const()[name = string("const_368_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2937856)))];
            tensor<fp16, [64, 64, 1, 1]> const_369_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2939584))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2943744))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2943936)))];
            tensor<fp16, [64, 1, 5, 5]> const_371_to_fp16 = const()[name = string("const_371_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2944384)))];
            tensor<fp16, [64, 64, 1, 1]> const_373_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2947968))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2952128))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2952320)))];
            tensor<fp16, [64, 64, 1, 1]> const_375_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2952768))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2956928))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2957120)))];
            tensor<fp16, [64, 1, 5, 5]> const_377_to_fp16 = const()[name = string("const_377_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2957568)))];
            tensor<fp16, [64, 64, 1, 1]> const_379_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2961152))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2965312))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2965504)))];
            tensor<fp16, [64, 64, 1, 1]> const_381_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2965952))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2970112))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2970304)))];
            tensor<fp16, [64, 1, 5, 5]> const_383_to_fp16 = const()[name = string("const_383_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2970752)))];
            tensor<fp16, [64, 64, 1, 1]> const_385_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2974336))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2978496))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2978688)))];
            tensor<fp16, [256, 256, 1, 1]> const_387_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2979136))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3044736))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3045312)))];
            tensor<fp16, [256]> const_388_to_fp16 = const()[name = string("const_388_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3045632)))];
            tensor<fp16, [256, 1, 5, 5]> const_389_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3046336))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052800))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053376)))];
            tensor<fp16, [256]> const_390_to_fp16 = const()[name = string("const_390_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053696)))];
            tensor<fp16, [256, 256, 1, 1]> const_391_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3054400))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3120000))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3120576)))];
            tensor<fp16, [256]> const_392_to_fp16 = const()[name = string("const_392_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3120896)))];
            tensor<fp16, [64, 64, 1, 1]> const_393_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3122624))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3126784))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3126976)))];
            tensor<fp16, [64, 1, 5, 5]> const_395_to_fp16 = const()[name = string("const_395_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3127424)))];
            tensor<fp16, [64, 64, 1, 1]> const_397_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3131008))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3135168))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3135360)))];
            tensor<fp16, [64, 64, 1, 1]> const_399_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3135808))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3139968))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3140160)))];
            tensor<fp16, [64, 1, 5, 5]> const_401_to_fp16 = const()[name = string("const_401_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3140608)))];
            tensor<fp16, [64, 64, 1, 1]> const_403_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3144192))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148352))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148544)))];
            tensor<fp16, [64, 64, 1, 1]> const_405_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148992))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3153152))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3153344)))];
            tensor<fp16, [64, 1, 5, 5]> const_407_to_fp16 = const()[name = string("const_407_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3153792)))];
            tensor<fp16, [64, 64, 1, 1]> const_409_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3157376))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3161536))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3161728)))];
            tensor<fp16, [256, 256, 1, 1]> const_411_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3162176))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3227776))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3228352)))];
            tensor<fp16, [256]> const_412_to_fp16 = const()[name = string("const_412_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3228672)))];
            tensor<fp16, [256, 1, 5, 5]> const_413_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3229376))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3235840))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3236416)))];
            tensor<fp16, [256]> const_414_to_fp16 = const()[name = string("const_414_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3236736)))];
            tensor<fp16, [256, 256, 1, 1]> const_415_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3237440))), scale = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3303040))), zero_point = tensor<int8, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3303616)))];
            tensor<fp16, [256]> const_416_to_fp16 = const()[name = string("const_416_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3303936)))];
            tensor<fp16, [64, 64, 1, 1]> const_417_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3305664))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3309824))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3310016)))];
            tensor<fp16, [64, 1, 5, 5]> const_419_to_fp16 = const()[name = string("const_419_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3310464)))];
            tensor<fp16, [64, 64, 1, 1]> const_421_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3314048))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3318208))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3318400)))];
            tensor<fp16, [64, 64, 1, 1]> const_423_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3318848))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3323008))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3323200)))];
            tensor<fp16, [64, 1, 5, 5]> const_425_to_fp16 = const()[name = string("const_425_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3323648)))];
            tensor<fp16, [64, 64, 1, 1]> const_427_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3327232))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3331392))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3331584)))];
            tensor<fp16, [64, 64, 1, 1]> const_429_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3332032))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3336192))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3336384)))];
            tensor<fp16, [64, 1, 5, 5]> const_431_to_fp16 = const()[name = string("const_431_to_fp16"), val = tensor<fp16, [64, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3336832)))];
            tensor<fp16, [64, 64, 1, 1]> const_433_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3340416))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3344576))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3344768)))];
            tensor<fp16, [512, 256, 1, 1]> const_435_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3345216))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3476352))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3477440)))];
            tensor<fp16, [512]> const_436_to_fp16 = const()[name = string("const_436_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3478016)))];
            tensor<fp16, [512, 1, 5, 5]> const_437_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3479232))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3492096))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3493184)))];
            tensor<fp16, [512]> const_438_to_fp16 = const()[name = string("const_438_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3493760)))];
            tensor<fp16, [512, 512, 1, 1]> const_439_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3494976))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3757184))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3758272)))];
            tensor<fp16, [512]> const_440_to_fp16 = const()[name = string("const_440_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3758848)))];
            tensor<fp16, [128, 128, 1, 1]> const_441_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3761088))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3777536))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3777856)))];
            tensor<fp16, [128]> const_442_to_fp16 = const()[name = string("const_442_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778048)))];
            tensor<fp16, [128, 1, 5, 5]> const_443_to_fp16 = const()[name = string("const_443_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778496)))];
            tensor<fp16, [128]> const_444_to_fp16 = const()[name = string("const_444_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3784960)))];
            tensor<fp16, [128, 128, 1, 1]> const_445_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3785408))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3801856))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3802176)))];
            tensor<fp16, [128]> const_446_to_fp16 = const()[name = string("const_446_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3802368)))];
            tensor<fp16, [128, 128, 1, 1]> const_447_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3802816))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3819264))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3819584)))];
            tensor<fp16, [128]> const_448_to_fp16 = const()[name = string("const_448_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3819776)))];
            tensor<fp16, [128, 1, 5, 5]> const_449_to_fp16 = const()[name = string("const_449_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3820224)))];
            tensor<fp16, [128]> const_450_to_fp16 = const()[name = string("const_450_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3826688)))];
            tensor<fp16, [128, 128, 1, 1]> const_451_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3827136))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3843584))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3843904)))];
            tensor<fp16, [128]> const_452_to_fp16 = const()[name = string("const_452_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3844096)))];
            tensor<fp16, [128, 128, 1, 1]> const_453_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3844544))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3860992))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3861312)))];
            tensor<fp16, [128]> const_454_to_fp16 = const()[name = string("const_454_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3861504)))];
            tensor<fp16, [128, 1, 5, 5]> const_455_to_fp16 = const()[name = string("const_455_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3861952)))];
            tensor<fp16, [128]> const_456_to_fp16 = const()[name = string("const_456_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3868416)))];
            tensor<fp16, [128, 128, 1, 1]> const_457_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3868864))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3885312))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3885632)))];
            tensor<fp16, [128]> const_458_to_fp16 = const()[name = string("const_458_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3885824)))];
            tensor<fp16, [512, 512, 1, 1]> const_459_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3886272))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4148480))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4149568)))];
            tensor<fp16, [512]> const_460_to_fp16 = const()[name = string("const_460_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4150144)))];
            tensor<fp16, [512, 1, 5, 5]> const_461_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4151360))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4164224))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4165312)))];
            tensor<fp16, [512]> const_462_to_fp16 = const()[name = string("const_462_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4165888)))];
            tensor<fp16, [512, 512, 1, 1]> const_463_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [512, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4167104))), scale = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4429312))), zero_point = tensor<int8, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430400)))];
            tensor<fp16, [512]> const_464_to_fp16 = const()[name = string("const_464_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430976)))];
            tensor<fp16, [128, 128, 1, 1]> const_465_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4433216))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4449664))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4449984)))];
            tensor<fp16, [128]> const_466_to_fp16 = const()[name = string("const_466_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4450176)))];
            tensor<fp16, [128, 1, 5, 5]> const_467_to_fp16 = const()[name = string("const_467_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4450624)))];
            tensor<fp16, [128]> const_468_to_fp16 = const()[name = string("const_468_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4457088)))];
            tensor<fp16, [128, 128, 1, 1]> const_469_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4457536))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4473984))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4474304)))];
            tensor<fp16, [128]> const_470_to_fp16 = const()[name = string("const_470_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4474496)))];
            tensor<fp16, [128, 128, 1, 1]> const_471_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4474944))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4491392))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4491712)))];
            tensor<fp16, [128]> const_472_to_fp16 = const()[name = string("const_472_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4491904)))];
            tensor<fp16, [128, 1, 5, 5]> const_473_to_fp16 = const()[name = string("const_473_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4492352)))];
            tensor<fp16, [128]> const_474_to_fp16 = const()[name = string("const_474_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4498816)))];
            tensor<fp16, [128, 128, 1, 1]> const_475_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4499264))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4515712))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4516032)))];
            tensor<fp16, [128]> const_476_to_fp16 = const()[name = string("const_476_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4516224)))];
            tensor<fp16, [128, 128, 1, 1]> const_477_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4516672))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4533120))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4533440)))];
            tensor<fp16, [128]> const_478_to_fp16 = const()[name = string("const_478_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4533632)))];
            tensor<fp16, [128, 1, 5, 5]> const_479_to_fp16 = const()[name = string("const_479_to_fp16"), val = tensor<fp16, [128, 1, 5, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4534080)))];
            tensor<fp16, [128]> const_480_to_fp16 = const()[name = string("const_480_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4540544)))];
            tensor<fp16, [128, 128, 1, 1]> const_481_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4540992))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4557440))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4557760)))];
            tensor<fp16, [128]> const_482_to_fp16 = const()[name = string("const_482_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4557952)))];
            tensor<fp16, [128, 512, 1, 1]> model_value_encoder_backbone_xfpn_p5_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 512, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4558400))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4624000))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4624320)))];
            tensor<fp16, [128, 256, 1, 1]> model_value_encoder_backbone_xfpn_p4_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4624640))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4657472))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4657792)))];
            tensor<fp16, [128, 1, 3, 3]> model_value_encoder_backbone_xfpn_fpn_output4_weight_to_fp16 = const()[name = string("model_value_encoder_backbone_xfpn_fpn_output4_weight_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4658112)))];
            tensor<fp16, [128, 128, 1, 1]> model_value_encoder_fuser_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4660608))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4677056))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4677376)))];
            tensor<fp16, [128]> model_value_encoder_fuser_bias_to_fp16 = const()[name = string("model_value_encoder_fuser_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4677568)))];
            tensor<fp16, [192, 128, 3, 3]> model_value_encoder_hidden_reinforce_transform1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [192, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4678016))), scale = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4899264))), zero_point = tensor<int8, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4899712)))];
            tensor<fp16, [192]> model_value_encoder_hidden_reinforce_transform1_bias_to_fp16 = const()[name = string("model_value_encoder_hidden_reinforce_transform1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4899968)))];
            string var_7657_pad_type_0 = const()[name = string("op_7657_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> var_7657_pad_0 = const()[name = string("op_7657_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4900416)))];
            tensor<int32, [2]> var_7657_strides_0 = const()[name = string("op_7657_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_7657_dilations_0 = const()[name = string("op_7657_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_7657_groups_0 = const()[name = string("op_7657_groups_0"), val = int32(1)];
            tensor<fp16, [192, 64, 3, 3]> model_value_encoder_hidden_reinforce_transform2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [192, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4900544))), scale = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5011200))), zero_point = tensor<int8, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5011648)))];
            tensor<fp16, [1, 192, 32, 32]> var_7657_cast_fp16 = conv(dilations = var_7657_dilations_0, groups = var_7657_groups_0, pad = var_7657_pad_0, pad_type = var_7657_pad_type_0, strides = var_7657_strides_0, weight = model_value_encoder_hidden_reinforce_transform2_weight_to_fp16, x = hidden_state)[name = string("op_7657_cast_fp16")];
            int32 var_7769 = const()[name = string("op_7769"), val = int32(1)];
            string input_1279_pad_type_0 = const()[name = string("input_1279_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1279_strides_0 = const()[name = string("input_1279_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1279_pad_0 = const()[name = string("input_1279_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5013056)))];
            tensor<int32, [2]> input_1279_dilations_0 = const()[name = string("input_1279_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1279_groups_0 = const()[name = string("input_1279_groups_0"), val = int32(1)];
            tensor<fp16, [24, 24, 1, 1]> const_485_to_fp16 = const()[name = string("const_485_to_fp16"), val = tensor<fp16, [24, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5013184)))];
            tensor<fp16, [24]> const_486_to_fp16 = const()[name = string("const_486_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5014400)))];
            tensor<fp16, [1, 24, 128, 128]> input_1281_cast_fp16 = conv(bias = const_486_to_fp16, dilations = input_1279_dilations_0, groups = input_1279_groups_0, pad = input_1279_pad_0, pad_type = input_1279_pad_type_0, strides = input_1279_strides_0, weight = const_485_to_fp16, x = input_11_cast_fp16)[name = string("input_1281_cast_fp16")];
            tensor<fp16, [1, 24, 128, 128]> input_1945_cast_fp16 = relu(x = input_1281_cast_fp16)[name = string("input_1945_cast_fp16")];
            fp32 y_41_scale_factor_height_0 = const()[name = string("y_41_scale_factor_height_0"), val = fp32(2)];
            fp32 y_41_scale_factor_width_0 = const()[name = string("y_41_scale_factor_width_0"), val = fp32(2)];
            tensor<fp16, [1, 128, 64, 64]> y_41_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = y_41_scale_factor_height_0, scale_factor_width = y_41_scale_factor_width_0, x = input_531_cast_fp16)[name = string("y_41_cast_fp16")];
            string x_85_pad_type_0 = const()[name = string("x_85_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_85_strides_0 = const()[name = string("x_85_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_85_pad_0 = const()[name = string("x_85_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5014528)))];
            tensor<int32, [2]> x_85_dilations_0 = const()[name = string("x_85_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_85_groups_0 = const()[name = string("x_85_groups_0"), val = int32(1)];
            tensor<fp16, [128, 144, 1, 1]> model_key_encoder_xfpn_p3_1x1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 144, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5014656))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5033152))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5033472)))];
            tensor<fp16, [1, 128, 64, 64]> x_85_cast_fp16 = conv(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 = model_key_encoder_xfpn_p3_1x1_weight_to_fp16, x = input_143_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1799_cast_fp16 = add(x = x_85_cast_fp16, y = y_41_cast_fp16)[name = string("input_1799_cast_fp16")];
            string input_1801_pad_type_0 = const()[name = string("input_1801_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1801_pad_0 = const()[name = string("input_1801_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5033664)))];
            int32 input_1801_groups_0 = const()[name = string("input_1801_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1801_strides_0 = const()[name = string("input_1801_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1801_dilations_0 = const()[name = string("input_1801_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> model_key_encoder_xfpn_fpn_output3_weight_to_fp16 = const()[name = string("model_key_encoder_xfpn_fpn_output3_weight_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5033792)))];
            tensor<fp16, [1, 128, 64, 64]> input_1801_cast_fp16 = conv(dilations = input_1801_dilations_0, groups = input_1801_groups_0, pad = input_1801_pad_0, pad_type = input_1801_pad_type_0, strides = input_1801_strides_0, weight = model_key_encoder_xfpn_fpn_output3_weight_to_fp16, x = input_1799_cast_fp16)[name = string("input_1801_cast_fp16")];
            string input_1803_pad_type_0 = const()[name = string("input_1803_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1803_strides_0 = const()[name = string("input_1803_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1803_pad_0 = const()[name = string("input_1803_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5036160)))];
            tensor<int32, [2]> input_1803_dilations_0 = const()[name = string("input_1803_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1803_groups_0 = const()[name = string("input_1803_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_679_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5036288))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5052736))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053056)))];
            tensor<fp16, [128]> const_680_to_fp16 = const()[name = string("const_680_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053248)))];
            tensor<fp16, [1, 128, 64, 64]> input_1805_cast_fp16 = conv(bias = const_680_to_fp16, dilations = input_1803_dilations_0, groups = input_1803_groups_0, pad = input_1803_pad_0, pad_type = input_1803_pad_type_0, strides = input_1803_strides_0, weight = const_679_to_fp16, x = input_1801_cast_fp16)[name = string("input_1805_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_87_cast_fp16 = relu(x = input_1805_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> var_11571_begin_0 = const()[name = string("op_11571_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053568)))];
            tensor<int32, [4]> var_11571_end_0 = const()[name = string("op_11571_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053696)))];
            tensor<bool, [4]> var_11571_end_mask_0 = const()[name = string("op_11571_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11571_cast_fp16 = slice_by_index(begin = var_11571_begin_0, end = var_11571_end_0, end_mask = var_11571_end_mask_0, x = x_87_cast_fp16)[name = string("op_11571_cast_fp16")];
            tensor<int32, [4]> var_11575_begin_0 = const()[name = string("op_11575_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053824)))];
            tensor<int32, [4]> var_11575_end_0 = const()[name = string("op_11575_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5053952)))];
            tensor<bool, [4]> var_11575_end_mask_0 = const()[name = string("op_11575_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11575_cast_fp16 = slice_by_index(begin = var_11575_begin_0, end = var_11575_end_0, end_mask = var_11575_end_mask_0, x = x_87_cast_fp16)[name = string("op_11575_cast_fp16")];
            tensor<int32, [4]> var_11579_begin_0 = const()[name = string("op_11579_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054080)))];
            tensor<int32, [4]> var_11579_end_0 = const()[name = string("op_11579_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054208)))];
            tensor<bool, [4]> var_11579_end_mask_0 = const()[name = string("op_11579_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11579_cast_fp16 = slice_by_index(begin = var_11579_begin_0, end = var_11579_end_0, end_mask = var_11579_end_mask_0, x = x_87_cast_fp16)[name = string("op_11579_cast_fp16")];
            tensor<int32, [4]> var_11583_begin_0 = const()[name = string("op_11583_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054336)))];
            tensor<int32, [4]> var_11583_end_0 = const()[name = string("op_11583_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054464)))];
            tensor<bool, [4]> var_11583_end_mask_0 = const()[name = string("op_11583_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11583_cast_fp16 = slice_by_index(begin = var_11583_begin_0, end = var_11583_end_0, end_mask = var_11583_end_mask_0, x = x_87_cast_fp16)[name = string("op_11583_cast_fp16")];
            string input_1809_pad_type_0 = const()[name = string("input_1809_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1809_pad_0 = const()[name = string("input_1809_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054592)))];
            tensor<int32, [2]> input_1809_dilations_0 = const()[name = string("input_1809_dilations_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_1809_groups_0 = const()[name = string("input_1809_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1809_strides_0 = const()[name = string("input_1809_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_681_to_fp16 = const()[name = string("const_681_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5054720)))];
            tensor<fp16, [32]> const_682_to_fp16 = const()[name = string("const_682_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5055360)))];
            tensor<fp16, [1, 32, 64, 64]> input_1811_cast_fp16 = conv(bias = const_682_to_fp16, dilations = input_1809_dilations_0, groups = input_1809_groups_0, pad = input_1809_pad_0, pad_type = input_1809_pad_type_0, strides = input_1809_strides_0, weight = const_681_to_fp16, x = var_11575_cast_fp16)[name = string("input_1811_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out1_57_cast_fp16 = relu(x = input_1811_cast_fp16)[name = string("out1_57_cast_fp16")];
            string input_1815_pad_type_0 = const()[name = string("input_1815_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1815_pad_0 = const()[name = string("input_1815_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5055488)))];
            tensor<int32, [2]> input_1815_dilations_0 = const()[name = string("input_1815_dilations_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_1815_groups_0 = const()[name = string("input_1815_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1815_strides_0 = const()[name = string("input_1815_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_683_to_fp16 = const()[name = string("const_683_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5055616)))];
            tensor<fp16, [32]> const_684_to_fp16 = const()[name = string("const_684_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5056256)))];
            tensor<fp16, [1, 32, 64, 64]> input_1817_cast_fp16 = conv(bias = const_684_to_fp16, dilations = input_1815_dilations_0, groups = input_1815_groups_0, pad = input_1815_pad_0, pad_type = input_1815_pad_type_0, strides = input_1815_strides_0, weight = const_683_to_fp16, x = var_11579_cast_fp16)[name = string("input_1817_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out2_57_cast_fp16 = relu(x = input_1817_cast_fp16)[name = string("out2_57_cast_fp16")];
            string input_1821_pad_type_0 = const()[name = string("input_1821_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1821_pad_0 = const()[name = string("input_1821_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5056384)))];
            tensor<int32, [2]> input_1821_dilations_0 = const()[name = string("input_1821_dilations_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_1821_groups_0 = const()[name = string("input_1821_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1821_strides_0 = const()[name = string("input_1821_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_685_to_fp16 = const()[name = string("const_685_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5056512)))];
            tensor<fp16, [32]> const_686_to_fp16 = const()[name = string("const_686_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5057152)))];
            tensor<fp16, [1, 32, 64, 64]> input_1823_cast_fp16 = conv(bias = const_686_to_fp16, dilations = input_1821_dilations_0, groups = input_1821_groups_0, pad = input_1821_pad_0, pad_type = input_1821_pad_type_0, strides = input_1821_strides_0, weight = const_685_to_fp16, x = var_11583_cast_fp16)[name = string("input_1823_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out3_57_cast_fp16 = relu(x = input_1823_cast_fp16)[name = string("out3_57_cast_fp16")];
            bool input_1825_interleave_0 = const()[name = string("input_1825_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 64, 64]> input_1825_cast_fp16 = concat(axis = var_7769, interleave = input_1825_interleave_0, values = (var_11571_cast_fp16, out1_57_cast_fp16, out2_57_cast_fp16, out3_57_cast_fp16))[name = string("input_1825_cast_fp16")];
            string input_1827_pad_type_0 = const()[name = string("input_1827_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1827_strides_0 = const()[name = string("input_1827_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1827_pad_0 = const()[name = string("input_1827_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5057280)))];
            tensor<int32, [2]> input_1827_dilations_0 = const()[name = string("input_1827_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1827_groups_0 = const()[name = string("input_1827_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_687_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5057408))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5073856))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5074176)))];
            tensor<fp16, [128]> const_688_to_fp16 = const()[name = string("const_688_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5074368)))];
            tensor<fp16, [1, 128, 64, 64]> input_1829_cast_fp16 = conv(bias = const_688_to_fp16, dilations = input_1827_dilations_0, groups = input_1827_groups_0, pad = input_1827_pad_0, pad_type = input_1827_pad_type_0, strides = input_1827_strides_0, weight = const_687_to_fp16, x = input_1825_cast_fp16)[name = string("input_1829_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_89_cast_fp16 = relu(x = input_1829_cast_fp16)[name = string("x_89_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1831_cast_fp16 = add(x = x_89_cast_fp16, y = input_1801_cast_fp16)[name = string("input_1831_cast_fp16")];
            string input_1833_pad_type_0 = const()[name = string("input_1833_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1833_strides_0 = const()[name = string("input_1833_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1833_pad_0 = const()[name = string("input_1833_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5074688)))];
            tensor<int32, [2]> input_1833_dilations_0 = const()[name = string("input_1833_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1833_groups_0 = const()[name = string("input_1833_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_689_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5074816))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5091264))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5091584)))];
            tensor<fp16, [128]> const_690_to_fp16 = const()[name = string("const_690_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5091776)))];
            tensor<fp16, [1, 128, 64, 64]> input_1835_cast_fp16 = conv(bias = const_690_to_fp16, dilations = input_1833_dilations_0, groups = input_1833_groups_0, pad = input_1833_pad_0, pad_type = input_1833_pad_type_0, strides = input_1833_strides_0, weight = const_689_to_fp16, x = input_1831_cast_fp16)[name = string("input_1835_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1837_cast_fp16 = relu(x = input_1835_cast_fp16)[name = string("input_1837_cast_fp16")];
            string input_1839_pad_type_0 = const()[name = string("input_1839_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1839_pad_0 = const()[name = string("input_1839_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5092096)))];
            tensor<int32, [2]> input_1839_dilations_0 = const()[name = string("input_1839_dilations_0"), val = tensor<int32, [2]>([4, 4])];
            int32 input_1839_groups_0 = const()[name = string("input_1839_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1839_strides_0 = const()[name = string("input_1839_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> const_691_to_fp16 = const()[name = string("const_691_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5092224)))];
            tensor<fp16, [128]> const_692_to_fp16 = const()[name = string("const_692_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5094592)))];
            tensor<fp16, [1, 128, 64, 64]> input_1841_cast_fp16 = conv(bias = const_692_to_fp16, dilations = input_1839_dilations_0, groups = input_1839_groups_0, pad = input_1839_pad_0, pad_type = input_1839_pad_type_0, strides = input_1839_strides_0, weight = const_691_to_fp16, x = input_1837_cast_fp16)[name = string("input_1841_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1843_cast_fp16 = relu(x = input_1841_cast_fp16)[name = string("input_1843_cast_fp16")];
            string input_1845_pad_type_0 = const()[name = string("input_1845_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1845_strides_0 = const()[name = string("input_1845_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1845_pad_0 = const()[name = string("input_1845_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5094912)))];
            tensor<int32, [2]> input_1845_dilations_0 = const()[name = string("input_1845_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1845_groups_0 = const()[name = string("input_1845_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_693_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5095040))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5111488))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5111808)))];
            tensor<fp16, [128]> const_694_to_fp16 = const()[name = string("const_694_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5112000)))];
            tensor<fp16, [1, 128, 64, 64]> input_1847_cast_fp16 = conv(bias = const_694_to_fp16, dilations = input_1845_dilations_0, groups = input_1845_groups_0, pad = input_1845_pad_0, pad_type = input_1845_pad_type_0, strides = input_1845_strides_0, weight = const_693_to_fp16, x = input_1843_cast_fp16)[name = string("input_1847_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_91_cast_fp16 = relu(x = input_1847_cast_fp16)[name = string("x_91_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1849_cast_fp16 = add(x = x_91_cast_fp16, y = input_1831_cast_fp16)[name = string("input_1849_cast_fp16")];
            string input_1851_pad_type_0 = const()[name = string("input_1851_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1851_strides_0 = const()[name = string("input_1851_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1851_pad_0 = const()[name = string("input_1851_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5112320)))];
            tensor<int32, [2]> input_1851_dilations_0 = const()[name = string("input_1851_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1851_groups_0 = const()[name = string("input_1851_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_695_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5112448))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5128896))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129216)))];
            tensor<fp16, [128]> const_696_to_fp16 = const()[name = string("const_696_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129408)))];
            tensor<fp16, [1, 128, 64, 64]> input_1853_cast_fp16 = conv(bias = const_696_to_fp16, dilations = input_1851_dilations_0, groups = input_1851_groups_0, pad = input_1851_pad_0, pad_type = input_1851_pad_type_0, strides = input_1851_strides_0, weight = const_695_to_fp16, x = input_1849_cast_fp16)[name = string("input_1853_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_93_cast_fp16 = relu(x = input_1853_cast_fp16)[name = string("x_93_cast_fp16")];
            tensor<int32, [4]> var_11730_begin_0 = const()[name = string("op_11730_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129728)))];
            tensor<int32, [4]> var_11730_end_0 = const()[name = string("op_11730_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129856)))];
            tensor<bool, [4]> var_11730_end_mask_0 = const()[name = string("op_11730_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11730_cast_fp16 = slice_by_index(begin = var_11730_begin_0, end = var_11730_end_0, end_mask = var_11730_end_mask_0, x = x_93_cast_fp16)[name = string("op_11730_cast_fp16")];
            tensor<int32, [4]> var_11734_begin_0 = const()[name = string("op_11734_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5129984)))];
            tensor<int32, [4]> var_11734_end_0 = const()[name = string("op_11734_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130112)))];
            tensor<bool, [4]> var_11734_end_mask_0 = const()[name = string("op_11734_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11734_cast_fp16 = slice_by_index(begin = var_11734_begin_0, end = var_11734_end_0, end_mask = var_11734_end_mask_0, x = x_93_cast_fp16)[name = string("op_11734_cast_fp16")];
            tensor<int32, [4]> var_11738_begin_0 = const()[name = string("op_11738_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130240)))];
            tensor<int32, [4]> var_11738_end_0 = const()[name = string("op_11738_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130368)))];
            tensor<bool, [4]> var_11738_end_mask_0 = const()[name = string("op_11738_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11738_cast_fp16 = slice_by_index(begin = var_11738_begin_0, end = var_11738_end_0, end_mask = var_11738_end_mask_0, x = x_93_cast_fp16)[name = string("op_11738_cast_fp16")];
            tensor<int32, [4]> var_11742_begin_0 = const()[name = string("op_11742_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130496)))];
            tensor<int32, [4]> var_11742_end_0 = const()[name = string("op_11742_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130624)))];
            tensor<bool, [4]> var_11742_end_mask_0 = const()[name = string("op_11742_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 32, 64, 64]> var_11742_cast_fp16 = slice_by_index(begin = var_11742_begin_0, end = var_11742_end_0, end_mask = var_11742_end_mask_0, x = x_93_cast_fp16)[name = string("op_11742_cast_fp16")];
            string input_1857_pad_type_0 = const()[name = string("input_1857_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1857_pad_0 = const()[name = string("input_1857_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130752)))];
            tensor<int32, [2]> input_1857_dilations_0 = const()[name = string("input_1857_dilations_0"), val = tensor<int32, [2]>([6, 6])];
            int32 input_1857_groups_0 = const()[name = string("input_1857_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1857_strides_0 = const()[name = string("input_1857_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_697_to_fp16 = const()[name = string("const_697_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5130880)))];
            tensor<fp16, [32]> const_698_to_fp16 = const()[name = string("const_698_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5131520)))];
            tensor<fp16, [1, 32, 64, 64]> input_1859_cast_fp16 = conv(bias = const_698_to_fp16, dilations = input_1857_dilations_0, groups = input_1857_groups_0, pad = input_1857_pad_0, pad_type = input_1857_pad_type_0, strides = input_1857_strides_0, weight = const_697_to_fp16, x = var_11734_cast_fp16)[name = string("input_1859_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out1_59_cast_fp16 = relu(x = input_1859_cast_fp16)[name = string("out1_59_cast_fp16")];
            string input_1863_pad_type_0 = const()[name = string("input_1863_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1863_pad_0 = const()[name = string("input_1863_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5131648)))];
            tensor<int32, [2]> input_1863_dilations_0 = const()[name = string("input_1863_dilations_0"), val = tensor<int32, [2]>([6, 6])];
            int32 input_1863_groups_0 = const()[name = string("input_1863_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1863_strides_0 = const()[name = string("input_1863_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_699_to_fp16 = const()[name = string("const_699_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5131776)))];
            tensor<fp16, [32]> const_700_to_fp16 = const()[name = string("const_700_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132416)))];
            tensor<fp16, [1, 32, 64, 64]> input_1865_cast_fp16 = conv(bias = const_700_to_fp16, dilations = input_1863_dilations_0, groups = input_1863_groups_0, pad = input_1863_pad_0, pad_type = input_1863_pad_type_0, strides = input_1863_strides_0, weight = const_699_to_fp16, x = var_11738_cast_fp16)[name = string("input_1865_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out2_59_cast_fp16 = relu(x = input_1865_cast_fp16)[name = string("out2_59_cast_fp16")];
            string input_1869_pad_type_0 = const()[name = string("input_1869_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1869_pad_0 = const()[name = string("input_1869_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132544)))];
            tensor<int32, [2]> input_1869_dilations_0 = const()[name = string("input_1869_dilations_0"), val = tensor<int32, [2]>([6, 6])];
            int32 input_1869_groups_0 = const()[name = string("input_1869_groups_0"), val = int32(32)];
            tensor<int32, [2]> input_1869_strides_0 = const()[name = string("input_1869_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [32, 1, 3, 3]> const_701_to_fp16 = const()[name = string("const_701_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132672)))];
            tensor<fp16, [32]> const_702_to_fp16 = const()[name = string("const_702_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133312)))];
            tensor<fp16, [1, 32, 64, 64]> input_1871_cast_fp16 = conv(bias = const_702_to_fp16, dilations = input_1869_dilations_0, groups = input_1869_groups_0, pad = input_1869_pad_0, pad_type = input_1869_pad_type_0, strides = input_1869_strides_0, weight = const_701_to_fp16, x = var_11742_cast_fp16)[name = string("input_1871_cast_fp16")];
            tensor<fp16, [1, 32, 64, 64]> out3_59_cast_fp16 = relu(x = input_1871_cast_fp16)[name = string("out3_59_cast_fp16")];
            bool input_1873_interleave_0 = const()[name = string("input_1873_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 64, 64]> input_1873_cast_fp16 = concat(axis = var_7769, interleave = input_1873_interleave_0, values = (var_11730_cast_fp16, out1_59_cast_fp16, out2_59_cast_fp16, out3_59_cast_fp16))[name = string("input_1873_cast_fp16")];
            string input_1875_pad_type_0 = const()[name = string("input_1875_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1875_strides_0 = const()[name = string("input_1875_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1875_pad_0 = const()[name = string("input_1875_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133440)))];
            tensor<int32, [2]> input_1875_dilations_0 = const()[name = string("input_1875_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1875_groups_0 = const()[name = string("input_1875_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_703_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133568))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150016))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150336)))];
            tensor<fp16, [128]> const_704_to_fp16 = const()[name = string("const_704_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150528)))];
            tensor<fp16, [1, 128, 64, 64]> input_1877_cast_fp16 = conv(bias = const_704_to_fp16, dilations = input_1875_dilations_0, groups = input_1875_groups_0, pad = input_1875_pad_0, pad_type = input_1875_pad_type_0, strides = input_1875_strides_0, weight = const_703_to_fp16, x = input_1873_cast_fp16)[name = string("input_1877_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_95_cast_fp16 = relu(x = input_1877_cast_fp16)[name = string("x_95_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1879_cast_fp16 = add(x = x_95_cast_fp16, y = input_1849_cast_fp16)[name = string("input_1879_cast_fp16")];
            string input_1881_pad_type_0 = const()[name = string("input_1881_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1881_strides_0 = const()[name = string("input_1881_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1881_pad_0 = const()[name = string("input_1881_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150848)))];
            tensor<int32, [2]> input_1881_dilations_0 = const()[name = string("input_1881_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1881_groups_0 = const()[name = string("input_1881_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_705_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5150976))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5167424))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5167744)))];
            tensor<fp16, [128]> const_706_to_fp16 = const()[name = string("const_706_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5167936)))];
            tensor<fp16, [1, 128, 64, 64]> input_1883_cast_fp16 = conv(bias = const_706_to_fp16, dilations = input_1881_dilations_0, groups = input_1881_groups_0, pad = input_1881_pad_0, pad_type = input_1881_pad_type_0, strides = input_1881_strides_0, weight = const_705_to_fp16, x = input_1879_cast_fp16)[name = string("input_1883_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1885_cast_fp16 = relu(x = input_1883_cast_fp16)[name = string("input_1885_cast_fp16")];
            string input_1887_pad_type_0 = const()[name = string("input_1887_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1887_pad_0 = const()[name = string("input_1887_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5168256)))];
            tensor<int32, [2]> input_1887_dilations_0 = const()[name = string("input_1887_dilations_0"), val = tensor<int32, [2]>([6, 6])];
            int32 input_1887_groups_0 = const()[name = string("input_1887_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_1887_strides_0 = const()[name = string("input_1887_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [128, 1, 3, 3]> const_707_to_fp16 = const()[name = string("const_707_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5168384)))];
            tensor<fp16, [128]> const_708_to_fp16 = const()[name = string("const_708_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5170752)))];
            tensor<fp16, [1, 128, 64, 64]> input_1889_cast_fp16 = conv(bias = const_708_to_fp16, dilations = input_1887_dilations_0, groups = input_1887_groups_0, pad = input_1887_pad_0, pad_type = input_1887_pad_type_0, strides = input_1887_strides_0, weight = const_707_to_fp16, x = input_1885_cast_fp16)[name = string("input_1889_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1891_cast_fp16 = relu(x = input_1889_cast_fp16)[name = string("input_1891_cast_fp16")];
            string input_1893_pad_type_0 = const()[name = string("input_1893_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1893_strides_0 = const()[name = string("input_1893_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1893_pad_0 = const()[name = string("input_1893_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5171072)))];
            tensor<int32, [2]> input_1893_dilations_0 = const()[name = string("input_1893_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1893_groups_0 = const()[name = string("input_1893_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1, 1]> const_709_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [128, 128, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5171200))), scale = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5187648))), zero_point = tensor<int8, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5187968)))];
            tensor<fp16, [128]> const_710_to_fp16 = const()[name = string("const_710_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5188160)))];
            tensor<fp16, [1, 128, 64, 64]> input_1895_cast_fp16 = conv(bias = const_710_to_fp16, dilations = input_1893_dilations_0, groups = input_1893_groups_0, pad = input_1893_pad_0, pad_type = input_1893_pad_type_0, strides = input_1893_strides_0, weight = const_709_to_fp16, x = input_1891_cast_fp16)[name = string("input_1895_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> x_97_cast_fp16 = relu(x = input_1895_cast_fp16)[name = string("x_97_cast_fp16")];
            tensor<fp16, [1, 128, 64, 64]> input_1933_cast_fp16 = add(x = x_97_cast_fp16, y = input_1879_cast_fp16)[name = string("input_1933_cast_fp16")];
            tensor<int32, [4]> a_sq_1_perm_0 = const()[name = string("a_sq_1_perm_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5188480)))];
            tensor<fp16, [1, 64, 1, 2048]> a_sq_1_cast_fp16 = transpose(perm = a_sq_1_perm_0, x = prev_key)[name = string("transpose_2")];
            tensor<fp16, [1, 64, 1, 2048]> input_1899_cast_fp16 = mul(x = a_sq_1_cast_fp16, y = a_sq_1_cast_fp16)[name = string("input_1899_cast_fp16")];
            string a_sq_3_pad_type_0 = const()[name = string("a_sq_3_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> a_sq_3_strides_0 = const()[name = string("a_sq_3_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> a_sq_3_pad_0 = const()[name = string("a_sq_3_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5188608)))];
            tensor<int32, [2]> a_sq_3_dilations_0 = const()[name = string("a_sq_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 a_sq_3_groups_0 = const()[name = string("a_sq_3_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 64, 1, 1]> model_memory_op_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [1024, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5188736))), scale = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5254336))), zero_point = tensor<int8, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5256448)))];
            tensor<fp16, [1, 1024, 1, 2048]> a_sq_3_cast_fp16 = conv(dilations = a_sq_3_dilations_0, groups = a_sq_3_groups_0, pad = a_sq_3_pad_0, pad_type = a_sq_3_pad_type_0, strides = a_sq_3_strides_0, weight = model_memory_op_conv_weight_to_fp16, x = input_1899_cast_fp16)[name = string("a_sq_3_cast_fp16")];
            tensor<int32, [4]> a_sq_5_perm_0 = const()[name = string("a_sq_5_perm_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5257536)))];
            tensor<int32, [4]> var_11916 = const()[name = string("op_11916"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5257664)))];
            tensor<fp16, [1, 64, 1, 1024]> var_11917_cast_fp16 = reshape(shape = var_11916, x = key_k_cast_fp16)[name = string("op_11917_cast_fp16")];
            string p_1_equation_0 = const()[name = string("p_1_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 2048, 1, 1024]> p_1_cast_fp16 = einsum(equation = p_1_equation_0, values = (prev_key, var_11917_cast_fp16))[name = string("p_1_cast_fp16")];
            fp16 var_11922_promoted_to_fp16 = const()[name = string("op_11922_promoted_to_fp16"), val = fp16(2)];
            tensor<fp16, [1, 2048, 1, 1024]> var_11923_cast_fp16 = mul(x = p_1_cast_fp16, y = var_11922_promoted_to_fp16)[name = string("op_11923_cast_fp16")];
            tensor<fp16, [1, 2048, 1, 1024]> a_sq_5_cast_fp16 = transpose(perm = a_sq_5_perm_0, x = a_sq_3_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 1, 1024]> var_11925_cast_fp16 = sub(x = var_11923_cast_fp16, y = a_sq_5_cast_fp16)[name = string("op_11925_cast_fp16")];
            fp16 _inversed_affinity_1_y_0_to_fp16 = const()[name = string("_inversed_affinity_1_y_0_to_fp16"), val = fp16(0.125)];
            tensor<fp16, [1, 2048, 1, 1024]> _inversed_affinity_1_cast_fp16 = mul(x = var_11925_cast_fp16, y = _inversed_affinity_1_y_0_to_fp16)[name = string("_inversed_affinity_1_cast_fp16")];
            tensor<int32, [4]> affinity0_1_begin_0 = const()[name = string("affinity0_1_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5257792)))];
            tensor<int32, [4]> affinity0_1_end_0 = const()[name = string("affinity0_1_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5257920)))];
            tensor<bool, [4]> affinity0_1_end_mask_0 = const()[name = string("affinity0_1_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 1024, 1, 1024]> affinity0_1_cast_fp16 = slice_by_index(begin = affinity0_1_begin_0, end = affinity0_1_end_0, end_mask = affinity0_1_end_mask_0, x = _inversed_affinity_1_cast_fp16)[name = string("affinity0_1_cast_fp16")];
            tensor<int32, [4]> affinity1_1_begin_0 = const()[name = string("affinity1_1_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258048)))];
            tensor<int32, [4]> affinity1_1_end_0 = const()[name = string("affinity1_1_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258176)))];
            tensor<bool, [4]> affinity1_1_end_mask_0 = const()[name = string("affinity1_1_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 1024, 1, 1024]> affinity1_1_cast_fp16 = slice_by_index(begin = affinity1_1_begin_0, end = affinity1_1_end_0, end_mask = affinity1_1_end_mask_0, x = _inversed_affinity_1_cast_fp16)[name = string("affinity1_1_cast_fp16")];
            fp16 var_11953_to_fp16 = const()[name = string("op_11953_to_fp16"), val = fp16(0.5)];
            tensor<fp16, [1, 1024, 1, 1024]> var_11954_cast_fp16 = sub(x = affinity1_1_cast_fp16, y = var_11953_to_fp16)[name = string("op_11954_cast_fp16")];
            int32 var_11956 = const()[name = string("op_11956"), val = int32(1)];
            bool input_1901_interleave_0 = const()[name = string("input_1901_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 2048, 1, 1024]> input_1901_cast_fp16 = concat(axis = var_11956, interleave = input_1901_interleave_0, values = (affinity0_1_cast_fp16, var_11954_cast_fp16))[name = string("input_1901_cast_fp16")];
            int32 var_11958 = const()[name = string("op_11958"), val = int32(1)];
            tensor<fp16, [1, 2048, 1, 1024]> var_11960_cast_fp16 = softmax(axis = var_11958, x = input_1901_cast_fp16)[name = string("op_11960_cast_fp16")];
            string mem_1_equation_0 = const()[name = string("mem_1_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 128, 1, 1024]> mem_1_cast_fp16 = einsum(equation = mem_1_equation_0, values = (prev_value, var_11960_cast_fp16))[name = string("mem_1_cast_fp16")];
            tensor<int32, [4]> var_11965 = const()[name = string("op_11965"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258304)))];
            tensor<fp16, [1, 128, 32, 32]> mem_3_cast_fp16 = reshape(shape = var_11965, x = mem_1_cast_fp16)[name = string("mem_3_cast_fp16")];
            int32 var_11968 = const()[name = string("op_11968"), val = int32(1)];
            bool x_99_interleave_0 = const()[name = string("x_99_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> x_99_cast_fp16 = concat(axis = var_11968, interleave = x_99_interleave_0, values = (input_631_cast_fp16, mem_3_cast_fp16))[name = string("x_99_cast_fp16")];
            int32 var_11976 = const()[name = string("op_11976"), val = int32(1)];
            bool var_11980 = const()[name = string("op_11980"), val = bool(true)];
            bool input_1903_interleave_0 = const()[name = string("input_1903_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 32, 32]> input_1903_cast_fp16 = concat(axis = var_11976, interleave = input_1903_interleave_0, values = (x_99_cast_fp16, hidden_state))[name = string("input_1903_cast_fp16")];
            tensor<fp16, [1, 320, 32, 32]> input_1905_cast_fp16 = relu(x = input_1903_cast_fp16)[name = string("input_1905_cast_fp16")];
            string input_1907_pad_type_0 = const()[name = string("input_1907_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1907_pad_0 = const()[name = string("input_1907_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258432)))];
            tensor<int32, [2]> input_1907_strides_0 = const()[name = string("input_1907_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1907_dilations_0 = const()[name = string("input_1907_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1907_groups_0 = const()[name = string("input_1907_groups_0"), val = int32(1)];
            tensor<fp16, [64, 320, 3, 3]> model_decoder_fuser_block1_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 320, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5258560))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5442944))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5443136)))];
            tensor<fp16, [64]> model_decoder_fuser_block1_conv1_bias_to_fp16 = const()[name = string("model_decoder_fuser_block1_conv1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5443264)))];
            tensor<fp16, [1, 64, 32, 32]> input_1907_cast_fp16 = conv(bias = model_decoder_fuser_block1_conv1_bias_to_fp16, dilations = input_1907_dilations_0, groups = input_1907_groups_0, pad = input_1907_pad_0, pad_type = input_1907_pad_type_0, strides = input_1907_strides_0, weight = model_decoder_fuser_block1_conv1_weight_to_fp16, x = input_1905_cast_fp16)[name = string("input_1907_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1909_cast_fp16 = relu(x = input_1907_cast_fp16)[name = string("input_1909_cast_fp16")];
            string y_43_pad_type_0 = const()[name = string("y_43_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_43_pad_0 = const()[name = string("y_43_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5443456)))];
            tensor<int32, [2]> y_43_strides_0 = const()[name = string("y_43_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_43_dilations_0 = const()[name = string("y_43_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_43_groups_0 = const()[name = string("y_43_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_fuser_block1_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5443584))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480512))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480704)))];
            tensor<fp16, [64]> model_decoder_fuser_block1_conv2_bias_to_fp16 = const()[name = string("model_decoder_fuser_block1_conv2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480832)))];
            tensor<fp16, [1, 64, 32, 32]> y_43_cast_fp16 = conv(bias = model_decoder_fuser_block1_conv2_bias_to_fp16, dilations = y_43_dilations_0, groups = y_43_groups_0, pad = y_43_pad_0, pad_type = y_43_pad_type_0, strides = y_43_strides_0, weight = model_decoder_fuser_block1_conv2_weight_to_fp16, x = input_1909_cast_fp16)[name = string("y_43_cast_fp16")];
            string x_101_pad_type_0 = const()[name = string("x_101_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_101_pad_0 = const()[name = string("x_101_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5481024)))];
            tensor<int32, [2]> x_101_strides_0 = const()[name = string("x_101_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_101_dilations_0 = const()[name = string("x_101_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_101_groups_0 = const()[name = string("x_101_groups_0"), val = int32(1)];
            tensor<fp16, [64, 320, 3, 3]> model_decoder_fuser_block1_downsample_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 320, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5481152))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5665536))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5665728)))];
            tensor<fp16, [64]> model_decoder_fuser_block1_downsample_bias_to_fp16 = const()[name = string("model_decoder_fuser_block1_downsample_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5665856)))];
            tensor<fp16, [1, 64, 32, 32]> x_101_cast_fp16 = conv(bias = model_decoder_fuser_block1_downsample_bias_to_fp16, dilations = x_101_dilations_0, groups = x_101_groups_0, pad = x_101_pad_0, pad_type = x_101_pad_type_0, strides = x_101_strides_0, weight = model_decoder_fuser_block1_downsample_weight_to_fp16, x = input_1903_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> x_103_cast_fp16 = add(x = x_101_cast_fp16, y = y_43_cast_fp16)[name = string("x_103_cast_fp16")];
            tensor<int32, [2]> var_12029 = const()[name = string("op_12029"), val = tensor<int32, [2]>([32, 32])];
            tensor<int32, [2]> var_12030 = const()[name = string("op_12030"), val = tensor<int32, [2]>([32, 32])];
            string input_1911_pad_type_0 = const()[name = string("input_1911_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1911_pad_0 = const()[name = string("input_1911_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5666048)))];
            bool input_1911_exclude_padding_from_average_0 = const()[name = string("input_1911_exclude_padding_from_average_0"), val = bool(false)];
            bool input_1911_ceil_mode_0 = const()[name = string("input_1911_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 64, 1, 1]> input_1911_cast_fp16 = avg_pool(ceil_mode = input_1911_ceil_mode_0, exclude_padding_from_average = input_1911_exclude_padding_from_average_0, kernel_sizes = var_12029, pad = input_1911_pad_0, pad_type = input_1911_pad_type_0, strides = var_12030, x = x_103_cast_fp16)[name = string("input_1911_cast_fp16")];
            string input_1913_pad_type_0 = const()[name = string("input_1913_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1913_strides_0 = const()[name = string("input_1913_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1913_pad_0 = const()[name = string("input_1913_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5666176)))];
            tensor<int32, [2]> input_1913_dilations_0 = const()[name = string("input_1913_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1913_groups_0 = const()[name = string("input_1913_groups_0"), val = int32(1)];
            tensor<fp16, [4, 64, 1, 1]> model_decoder_fuser_attention_ChannelGate_mlp_1_weight_to_fp16 = const()[name = string("model_decoder_fuser_attention_ChannelGate_mlp_1_weight_to_fp16"), val = tensor<fp16, [4, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5666304)))];
            tensor<fp16, [4]> model_decoder_fuser_attention_ChannelGate_mlp_1_bias_to_fp16 = const()[name = string("model_decoder_fuser_attention_ChannelGate_mlp_1_bias_to_fp16"), val = tensor<fp16, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5666880)))];
            tensor<fp16, [1, 4, 1, 1]> input_1913_cast_fp16 = conv(bias = model_decoder_fuser_attention_ChannelGate_mlp_1_bias_to_fp16, dilations = input_1913_dilations_0, groups = input_1913_groups_0, pad = input_1913_pad_0, pad_type = input_1913_pad_type_0, strides = input_1913_strides_0, weight = model_decoder_fuser_attention_ChannelGate_mlp_1_weight_to_fp16, x = input_1911_cast_fp16)[name = string("input_1913_cast_fp16")];
            tensor<fp16, [1, 4, 1, 1]> input_1915_cast_fp16 = relu(x = input_1913_cast_fp16)[name = string("input_1915_cast_fp16")];
            string x_105_pad_type_0 = const()[name = string("x_105_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_105_strides_0 = const()[name = string("x_105_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_105_pad_0 = const()[name = string("x_105_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5667008)))];
            tensor<int32, [2]> x_105_dilations_0 = const()[name = string("x_105_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_105_groups_0 = const()[name = string("x_105_groups_0"), val = int32(1)];
            tensor<fp16, [64, 4, 1, 1]> model_decoder_fuser_attention_ChannelGate_mlp_3_weight_to_fp16 = const()[name = string("model_decoder_fuser_attention_ChannelGate_mlp_3_weight_to_fp16"), val = tensor<fp16, [64, 4, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5667136)))];
            tensor<fp16, [64]> model_decoder_fuser_attention_ChannelGate_mlp_3_bias_to_fp16 = const()[name = string("model_decoder_fuser_attention_ChannelGate_mlp_3_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5667712)))];
            tensor<fp16, [1, 64, 1, 1]> x_105_cast_fp16 = conv(bias = model_decoder_fuser_attention_ChannelGate_mlp_3_bias_to_fp16, dilations = x_105_dilations_0, groups = x_105_groups_0, pad = x_105_pad_0, pad_type = x_105_pad_type_0, strides = x_105_strides_0, weight = model_decoder_fuser_attention_ChannelGate_mlp_3_weight_to_fp16, x = input_1915_cast_fp16)[name = string("x_105_cast_fp16")];
            tensor<int32, [2]> var_12054 = const()[name = string("op_12054"), val = tensor<int32, [2]>([32, 32])];
            tensor<int32, [2]> var_12055 = const()[name = string("op_12055"), val = tensor<int32, [2]>([32, 32])];
            string input_1917_pad_type_0 = const()[name = string("input_1917_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1917_pad_0 = const()[name = string("input_1917_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5667904)))];
            bool input_1917_ceil_mode_0 = const()[name = string("input_1917_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 64, 1, 1]> input_1917_cast_fp16 = max_pool(ceil_mode = input_1917_ceil_mode_0, kernel_sizes = var_12054, pad = input_1917_pad_0, pad_type = input_1917_pad_type_0, strides = var_12055, x = x_103_cast_fp16)[name = string("input_1917_cast_fp16")];
            string input_1919_pad_type_0 = const()[name = string("input_1919_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1919_strides_0 = const()[name = string("input_1919_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1919_pad_0 = const()[name = string("input_1919_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668032)))];
            tensor<int32, [2]> input_1919_dilations_0 = const()[name = string("input_1919_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1919_groups_0 = const()[name = string("input_1919_groups_0"), val = int32(1)];
            tensor<fp16, [1, 4, 1, 1]> input_1919_cast_fp16 = conv(bias = model_decoder_fuser_attention_ChannelGate_mlp_1_bias_to_fp16, dilations = input_1919_dilations_0, groups = input_1919_groups_0, pad = input_1919_pad_0, pad_type = input_1919_pad_type_0, strides = input_1919_strides_0, weight = model_decoder_fuser_attention_ChannelGate_mlp_1_weight_to_fp16, x = input_1917_cast_fp16)[name = string("input_1919_cast_fp16")];
            tensor<fp16, [1, 4, 1, 1]> input_1921_cast_fp16 = relu(x = input_1919_cast_fp16)[name = string("input_1921_cast_fp16")];
            string y_45_pad_type_0 = const()[name = string("y_45_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> y_45_strides_0 = const()[name = string("y_45_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> y_45_pad_0 = const()[name = string("y_45_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668160)))];
            tensor<int32, [2]> y_45_dilations_0 = const()[name = string("y_45_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_45_groups_0 = const()[name = string("y_45_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1, 1]> y_45_cast_fp16 = conv(bias = model_decoder_fuser_attention_ChannelGate_mlp_3_bias_to_fp16, dilations = y_45_dilations_0, groups = y_45_groups_0, pad = y_45_pad_0, pad_type = y_45_pad_type_0, strides = y_45_strides_0, weight = model_decoder_fuser_attention_ChannelGate_mlp_3_weight_to_fp16, x = input_1921_cast_fp16)[name = string("y_45_cast_fp16")];
            tensor<fp16, [1, 64, 1, 1]> channel_att_sum_1_cast_fp16 = add(x = x_105_cast_fp16, y = y_45_cast_fp16)[name = string("channel_att_sum_1_cast_fp16")];
            tensor<fp16, [1, 64, 1, 1]> y_47_cast_fp16 = sigmoid(x = channel_att_sum_1_cast_fp16)[name = string("y_47_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> x_107_cast_fp16 = mul(x = x_103_cast_fp16, y = y_47_cast_fp16)[name = string("x_107_cast_fp16")];
            tensor<int32, [1]> reduce_max_0_axes_0 = const()[name = string("reduce_max_0_axes_0"), val = tensor<int32, [1]>([1])];
            bool reduce_max_0_keep_dims_0 = const()[name = string("reduce_max_0_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 1, 32, 32]> reduce_max_0_cast_fp16 = reduce_max(axes = reduce_max_0_axes_0, keep_dims = reduce_max_0_keep_dims_0, x = x_107_cast_fp16)[name = string("reduce_max_0_cast_fp16")];
            tensor<int32, [1]> var_12083_axes_0 = const()[name = string("op_12083_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1, 32, 32]> var_12083_cast_fp16 = reduce_mean(axes = var_12083_axes_0, keep_dims = var_11980, x = x_107_cast_fp16)[name = string("op_12083_cast_fp16")];
            bool input_1923_interleave_0 = const()[name = string("input_1923_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 2, 32, 32]> input_1923_cast_fp16 = concat(axis = var_11976, interleave = input_1923_interleave_0, values = (reduce_max_0_cast_fp16, var_12083_cast_fp16))[name = string("input_1923_cast_fp16")];
            string x_out_1_pad_type_0 = const()[name = string("x_out_1_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_out_1_pad_0 = const()[name = string("x_out_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668288)))];
            tensor<int32, [2]> x_out_1_strides_0 = const()[name = string("x_out_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_out_1_dilations_0 = const()[name = string("x_out_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_out_1_groups_0 = const()[name = string("x_out_1_groups_0"), val = int32(1)];
            tensor<fp16, [1, 2, 7, 7]> model_decoder_fuser_attention_SpatialGate_spatial_conv_weight_to_fp16 = const()[name = string("model_decoder_fuser_attention_SpatialGate_spatial_conv_weight_to_fp16"), val = tensor<fp16, [1, 2, 7, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668416)))];
            tensor<fp16, [1]> model_decoder_fuser_attention_SpatialGate_spatial_conv_bias_to_fp16 = const()[name = string("model_decoder_fuser_attention_SpatialGate_spatial_conv_bias_to_fp16"), val = tensor<fp16, [1]>([0.212158203])];
            tensor<fp16, [1, 1, 32, 32]> x_out_1_cast_fp16 = conv(bias = model_decoder_fuser_attention_SpatialGate_spatial_conv_bias_to_fp16, dilations = x_out_1_dilations_0, groups = x_out_1_groups_0, pad = x_out_1_pad_0, pad_type = x_out_1_pad_type_0, strides = x_out_1_strides_0, weight = model_decoder_fuser_attention_SpatialGate_spatial_conv_weight_to_fp16, x = input_1923_cast_fp16)[name = string("x_out_1_cast_fp16")];
            tensor<fp16, [1, 1, 32, 32]> y_49_cast_fp16 = sigmoid(x = x_out_1_cast_fp16)[name = string("y_49_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> y_51_cast_fp16 = mul(x = x_107_cast_fp16, y = y_49_cast_fp16)[name = string("y_51_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1925_cast_fp16 = add(x = x_103_cast_fp16, y = y_51_cast_fp16)[name = string("input_1925_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1927_cast_fp16 = relu(x = input_1925_cast_fp16)[name = string("input_1927_cast_fp16")];
            string input_1929_pad_type_0 = const()[name = string("input_1929_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1929_pad_0 = const()[name = string("input_1929_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668736)))];
            tensor<int32, [2]> input_1929_strides_0 = const()[name = string("input_1929_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1929_dilations_0 = const()[name = string("input_1929_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1929_groups_0 = const()[name = string("input_1929_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_fuser_block2_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5668864))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5705792))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5705984)))];
            tensor<fp16, [64]> model_decoder_fuser_block2_conv1_bias_to_fp16 = const()[name = string("model_decoder_fuser_block2_conv1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5706112)))];
            tensor<fp16, [1, 64, 32, 32]> input_1929_cast_fp16 = conv(bias = model_decoder_fuser_block2_conv1_bias_to_fp16, dilations = input_1929_dilations_0, groups = input_1929_groups_0, pad = input_1929_pad_0, pad_type = input_1929_pad_type_0, strides = input_1929_strides_0, weight = model_decoder_fuser_block2_conv1_weight_to_fp16, x = input_1927_cast_fp16)[name = string("input_1929_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1931_cast_fp16 = relu(x = input_1929_cast_fp16)[name = string("input_1931_cast_fp16")];
            string y_53_pad_type_0 = const()[name = string("y_53_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_53_pad_0 = const()[name = string("y_53_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5706304)))];
            tensor<int32, [2]> y_53_strides_0 = const()[name = string("y_53_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_53_dilations_0 = const()[name = string("y_53_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_53_groups_0 = const()[name = string("y_53_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_fuser_block2_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5706432))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5743360))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5743552)))];
            tensor<fp16, [64]> model_decoder_fuser_block2_conv2_bias_to_fp16 = const()[name = string("model_decoder_fuser_block2_conv2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5743680)))];
            tensor<fp16, [1, 64, 32, 32]> y_53_cast_fp16 = conv(bias = model_decoder_fuser_block2_conv2_bias_to_fp16, dilations = y_53_dilations_0, groups = y_53_groups_0, pad = y_53_pad_0, pad_type = y_53_pad_type_0, strides = y_53_strides_0, weight = model_decoder_fuser_block2_conv2_weight_to_fp16, x = input_1931_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_1935_cast_fp16 = add(x = input_1925_cast_fp16, y = y_53_cast_fp16)[name = string("input_1935_cast_fp16")];
            string x_109_pad_type_0 = const()[name = string("x_109_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_109_pad_0 = const()[name = string("x_109_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5743872)))];
            tensor<int32, [2]> x_109_strides_0 = const()[name = string("x_109_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_109_dilations_0 = const()[name = string("x_109_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_109_groups_0 = const()[name = string("x_109_groups_0"), val = int32(1)];
            tensor<fp16, [64, 128, 3, 3]> model_decoder_up_16_8_skip_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5744000))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817792))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817984)))];
            tensor<fp16, [64]> model_decoder_up_16_8_skip_conv_bias_to_fp16 = const()[name = string("model_decoder_up_16_8_skip_conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5818112)))];
            tensor<fp16, [1, 64, 64, 64]> x_109_cast_fp16 = conv(bias = model_decoder_up_16_8_skip_conv_bias_to_fp16, dilations = x_109_dilations_0, groups = x_109_groups_0, pad = x_109_pad_0, pad_type = x_109_pad_type_0, strides = x_109_strides_0, weight = model_decoder_up_16_8_skip_conv_weight_to_fp16, x = input_1933_cast_fp16)[name = string("x_109_cast_fp16")];
            fp32 y_55_scale_factor_height_0 = const()[name = string("y_55_scale_factor_height_0"), val = fp32(2)];
            fp32 y_55_scale_factor_width_0 = const()[name = string("y_55_scale_factor_width_0"), val = fp32(2)];
            bool y_55_align_corners_0 = const()[name = string("y_55_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 64, 64]> y_55_cast_fp16 = upsample_bilinear(align_corners = y_55_align_corners_0, scale_factor_height = y_55_scale_factor_height_0, scale_factor_width = y_55_scale_factor_width_0, x = input_1935_cast_fp16)[name = string("y_55_cast_fp16")];
            tensor<fp16, [1, 64, 64, 64]> input_1937_cast_fp16 = add(x = x_109_cast_fp16, y = y_55_cast_fp16)[name = string("input_1937_cast_fp16")];
            tensor<fp16, [1, 64, 64, 64]> input_1939_cast_fp16 = relu(x = input_1937_cast_fp16)[name = string("input_1939_cast_fp16")];
            string input_1941_pad_type_0 = const()[name = string("input_1941_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1941_pad_0 = const()[name = string("input_1941_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5818304)))];
            tensor<int32, [2]> input_1941_strides_0 = const()[name = string("input_1941_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1941_dilations_0 = const()[name = string("input_1941_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1941_groups_0 = const()[name = string("input_1941_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_up_16_8_out_conv_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5818432))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5855360))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5855552)))];
            tensor<fp16, [64]> model_decoder_up_16_8_out_conv_conv1_bias_to_fp16 = const()[name = string("model_decoder_up_16_8_out_conv_conv1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5855680)))];
            tensor<fp16, [1, 64, 64, 64]> input_1941_cast_fp16 = conv(bias = model_decoder_up_16_8_out_conv_conv1_bias_to_fp16, dilations = input_1941_dilations_0, groups = input_1941_groups_0, pad = input_1941_pad_0, pad_type = input_1941_pad_type_0, strides = input_1941_strides_0, weight = model_decoder_up_16_8_out_conv_conv1_weight_to_fp16, x = input_1939_cast_fp16)[name = string("input_1941_cast_fp16")];
            tensor<fp16, [1, 64, 64, 64]> input_1943_cast_fp16 = relu(x = input_1941_cast_fp16)[name = string("input_1943_cast_fp16")];
            string y_57_pad_type_0 = const()[name = string("y_57_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_57_pad_0 = const()[name = string("y_57_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5855872)))];
            tensor<int32, [2]> y_57_strides_0 = const()[name = string("y_57_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_57_dilations_0 = const()[name = string("y_57_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_57_groups_0 = const()[name = string("y_57_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_up_16_8_out_conv_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5856000))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5892928))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5893120)))];
            tensor<fp16, [64]> model_decoder_up_16_8_out_conv_conv2_bias_to_fp16 = const()[name = string("model_decoder_up_16_8_out_conv_conv2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5893248)))];
            tensor<fp16, [1, 64, 64, 64]> y_57_cast_fp16 = conv(bias = model_decoder_up_16_8_out_conv_conv2_bias_to_fp16, dilations = y_57_dilations_0, groups = y_57_groups_0, pad = y_57_pad_0, pad_type = y_57_pad_type_0, strides = y_57_strides_0, weight = model_decoder_up_16_8_out_conv_conv2_weight_to_fp16, x = input_1943_cast_fp16)[name = string("y_57_cast_fp16")];
            tensor<fp16, [1, 64, 64, 64]> x_111_cast_fp16 = add(x = input_1937_cast_fp16, y = y_57_cast_fp16)[name = string("x_111_cast_fp16")];
            fp16 var_11974_to_fp16 = const()[name = string("op_11974_to_fp16"), val = fp16(-2000)];
            fp16 var_11975_to_fp16 = const()[name = string("op_11975_to_fp16"), val = fp16(2000)];
            tensor<fp16, [1, 64, 64, 64]> input_1947_cast_fp16 = clip(alpha = var_11974_to_fp16, beta = var_11975_to_fp16, x = x_111_cast_fp16)[name = string("input_1947_cast_fp16")];
            string x_113_pad_type_0 = const()[name = string("x_113_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_113_pad_0 = const()[name = string("x_113_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5893440)))];
            tensor<int32, [2]> x_113_strides_0 = const()[name = string("x_113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_113_dilations_0 = const()[name = string("x_113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_113_groups_0 = const()[name = string("x_113_groups_0"), val = int32(1)];
            tensor<fp16, [64, 24, 3, 3]> model_decoder_up_8_4_skip_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5893568))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5907456))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5907648)))];
            tensor<fp16, [64]> model_decoder_up_8_4_skip_conv_bias_to_fp16 = const()[name = string("model_decoder_up_8_4_skip_conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5907776)))];
            tensor<fp16, [1, 64, 128, 128]> x_113_cast_fp16 = conv(bias = model_decoder_up_8_4_skip_conv_bias_to_fp16, dilations = x_113_dilations_0, groups = x_113_groups_0, pad = x_113_pad_0, pad_type = x_113_pad_type_0, strides = x_113_strides_0, weight = model_decoder_up_8_4_skip_conv_weight_to_fp16, x = input_1945_cast_fp16)[name = string("x_113_cast_fp16")];
            fp32 y_59_scale_factor_height_0 = const()[name = string("y_59_scale_factor_height_0"), val = fp32(2)];
            fp32 y_59_scale_factor_width_0 = const()[name = string("y_59_scale_factor_width_0"), val = fp32(2)];
            bool y_59_align_corners_0 = const()[name = string("y_59_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 128, 128]> y_59_cast_fp16 = upsample_bilinear(align_corners = y_59_align_corners_0, scale_factor_height = y_59_scale_factor_height_0, scale_factor_width = y_59_scale_factor_width_0, x = input_1947_cast_fp16)[name = string("y_59_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> input_1949_cast_fp16 = add(x = x_113_cast_fp16, y = y_59_cast_fp16)[name = string("input_1949_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> input_1951_cast_fp16 = relu(x = input_1949_cast_fp16)[name = string("input_1951_cast_fp16")];
            string input_1953_pad_type_0 = const()[name = string("input_1953_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1953_pad_0 = const()[name = string("input_1953_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5907968)))];
            tensor<int32, [2]> input_1953_strides_0 = const()[name = string("input_1953_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1953_dilations_0 = const()[name = string("input_1953_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1953_groups_0 = const()[name = string("input_1953_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_up_8_4_out_conv_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5908096))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945024))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945216)))];
            tensor<fp16, [64]> model_decoder_up_8_4_out_conv_conv1_bias_to_fp16 = const()[name = string("model_decoder_up_8_4_out_conv_conv1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945344)))];
            tensor<fp16, [1, 64, 128, 128]> input_1953_cast_fp16 = conv(bias = model_decoder_up_8_4_out_conv_conv1_bias_to_fp16, dilations = input_1953_dilations_0, groups = input_1953_groups_0, pad = input_1953_pad_0, pad_type = input_1953_pad_type_0, strides = input_1953_strides_0, weight = model_decoder_up_8_4_out_conv_conv1_weight_to_fp16, x = input_1951_cast_fp16)[name = string("input_1953_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> input_1955_cast_fp16 = relu(x = input_1953_cast_fp16)[name = string("input_1955_cast_fp16")];
            string y_61_pad_type_0 = const()[name = string("y_61_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_61_pad_0 = const()[name = string("y_61_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945536)))];
            tensor<int32, [2]> y_61_strides_0 = const()[name = string("y_61_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_61_dilations_0 = const()[name = string("y_61_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_61_groups_0 = const()[name = string("y_61_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_up_8_4_out_conv_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5945664))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5982592))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5982784)))];
            tensor<fp16, [64]> model_decoder_up_8_4_out_conv_conv2_bias_to_fp16 = const()[name = string("model_decoder_up_8_4_out_conv_conv2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5982912)))];
            tensor<fp16, [1, 64, 128, 128]> y_61_cast_fp16 = conv(bias = model_decoder_up_8_4_out_conv_conv2_bias_to_fp16, dilations = y_61_dilations_0, groups = y_61_groups_0, pad = y_61_pad_0, pad_type = y_61_pad_type_0, strides = y_61_strides_0, weight = model_decoder_up_8_4_out_conv_conv2_weight_to_fp16, x = input_1955_cast_fp16)[name = string("y_61_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> x_115_cast_fp16 = add(x = input_1949_cast_fp16, y = y_61_cast_fp16)[name = string("x_115_cast_fp16")];
            tensor<fp16, [1, 64, 128, 128]> input_1957_cast_fp16 = clip(alpha = var_11974_to_fp16, beta = var_11975_to_fp16, x = x_115_cast_fp16)[name = string("input_1957_cast_fp16")];
            string x_117_pad_type_0 = const()[name = string("x_117_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_117_pad_0 = const()[name = string("x_117_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5983104)))];
            tensor<int32, [2]> x_117_strides_0 = const()[name = string("x_117_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> x_117_dilations_0 = const()[name = string("x_117_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_117_groups_0 = const()[name = string("x_117_groups_0"), val = int32(1)];
            tensor<fp16, [16, 24, 3, 3]> model_decoder_up_4_2_skip_conv_weight_to_fp16 = const()[name = string("model_decoder_up_4_2_skip_conv_weight_to_fp16"), val = tensor<fp16, [16, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5983232)))];
            tensor<fp16, [16]> model_decoder_up_4_2_skip_conv_bias_to_fp16 = const()[name = string("model_decoder_up_4_2_skip_conv_bias_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5990208)))];
            tensor<fp16, [1, 16, 256, 256]> x_117_cast_fp16 = conv(bias = model_decoder_up_4_2_skip_conv_bias_to_fp16, dilations = x_117_dilations_0, groups = x_117_groups_0, pad = x_117_pad_0, pad_type = x_117_pad_type_0, strides = x_117_strides_0, weight = model_decoder_up_4_2_skip_conv_weight_to_fp16, x = input_9_cast_fp16)[name = string("x_117_cast_fp16")];
            string input_1959_pad_type_0 = const()[name = string("input_1959_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_1959_strides_0 = const()[name = string("input_1959_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_1959_pad_0 = const()[name = string("input_1959_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5990336)))];
            tensor<int32, [2]> input_1959_dilations_0 = const()[name = string("input_1959_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1959_groups_0 = const()[name = string("input_1959_groups_0"), val = int32(1)];
            tensor<fp16, [16, 64, 1, 1]> model_decoder_up_4_2_reduce_channel_weight_to_fp16 = const()[name = string("model_decoder_up_4_2_reduce_channel_weight_to_fp16"), val = tensor<fp16, [16, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5990464)))];
            tensor<fp16, [16]> model_decoder_up_4_2_reduce_channel_bias_to_fp16 = const()[name = string("model_decoder_up_4_2_reduce_channel_bias_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5992576)))];
            tensor<fp16, [1, 16, 128, 128]> input_1959_cast_fp16 = conv(bias = model_decoder_up_4_2_reduce_channel_bias_to_fp16, dilations = input_1959_dilations_0, groups = input_1959_groups_0, pad = input_1959_pad_0, pad_type = input_1959_pad_type_0, strides = input_1959_strides_0, weight = model_decoder_up_4_2_reduce_channel_weight_to_fp16, x = input_1957_cast_fp16)[name = string("input_1959_cast_fp16")];
            fp32 var_12198_scale_factor_height_0 = const()[name = string("op_12198_scale_factor_height_0"), val = fp32(2)];
            fp32 var_12198_scale_factor_width_0 = const()[name = string("op_12198_scale_factor_width_0"), val = fp32(2)];
            bool var_12198_align_corners_0 = const()[name = string("op_12198_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 16, 256, 256]> var_12198_cast_fp16 = upsample_bilinear(align_corners = var_12198_align_corners_0, scale_factor_height = var_12198_scale_factor_height_0, scale_factor_width = var_12198_scale_factor_width_0, x = input_1959_cast_fp16)[name = string("op_12198_cast_fp16")];
            bool input_1961_interleave_0 = const()[name = string("input_1961_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 32, 256, 256]> input_1961_cast_fp16 = concat(axis = var_11976, interleave = input_1961_interleave_0, values = (x_117_cast_fp16, var_12198_cast_fp16))[name = string("input_1961_cast_fp16")];
            tensor<fp16, [1, 32, 256, 256]> input_1963_cast_fp16 = relu(x = input_1961_cast_fp16)[name = string("input_1963_cast_fp16")];
            string input_1965_pad_type_0 = const()[name = string("input_1965_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1965_pad_0 = const()[name = string("input_1965_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5992704)))];
            tensor<int32, [2]> input_1965_strides_0 = const()[name = string("input_1965_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_1965_dilations_0 = const()[name = string("input_1965_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_1965_groups_0 = const()[name = string("input_1965_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3, 3]> model_decoder_up_4_2_out_conv_conv1_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [32, 32, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5992832))), scale = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002112))), zero_point = tensor<int8, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002240)))];
            tensor<fp16, [32]> model_decoder_up_4_2_out_conv_conv1_bias_to_fp16 = const()[name = string("model_decoder_up_4_2_out_conv_conv1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002368)))];
            tensor<fp16, [1, 32, 256, 256]> input_1965_cast_fp16 = conv(bias = model_decoder_up_4_2_out_conv_conv1_bias_to_fp16, dilations = input_1965_dilations_0, groups = input_1965_groups_0, pad = input_1965_pad_0, pad_type = input_1965_pad_type_0, strides = input_1965_strides_0, weight = model_decoder_up_4_2_out_conv_conv1_weight_to_fp16, x = input_1963_cast_fp16)[name = string("input_1965_cast_fp16")];
            tensor<fp16, [1, 32, 256, 256]> input_1967_cast_fp16 = relu(x = input_1965_cast_fp16)[name = string("input_1967_cast_fp16")];
            string y_63_pad_type_0 = const()[name = string("y_63_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> y_63_pad_0 = const()[name = string("y_63_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002496)))];
            tensor<int32, [2]> y_63_strides_0 = const()[name = string("y_63_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> y_63_dilations_0 = const()[name = string("y_63_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 y_63_groups_0 = const()[name = string("y_63_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3, 3]> model_decoder_up_4_2_out_conv_conv2_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [32, 32, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6002624))), scale = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6011904))), zero_point = tensor<int8, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6012032)))];
            tensor<fp16, [32]> model_decoder_up_4_2_out_conv_conv2_bias_to_fp16 = const()[name = string("model_decoder_up_4_2_out_conv_conv2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6012160)))];
            tensor<fp16, [1, 32, 256, 256]> y_63_cast_fp16 = conv(bias = model_decoder_up_4_2_out_conv_conv2_bias_to_fp16, dilations = y_63_dilations_0, groups = y_63_groups_0, pad = y_63_pad_0, pad_type = y_63_pad_type_0, strides = y_63_strides_0, weight = model_decoder_up_4_2_out_conv_conv2_weight_to_fp16, x = input_1967_cast_fp16)[name = string("y_63_cast_fp16")];
            tensor<fp16, [1, 32, 256, 256]> input_1969_cast_fp16 = add(x = input_1961_cast_fp16, y = y_63_cast_fp16)[name = string("input_1969_cast_fp16")];
            tensor<fp16, [1, 32, 256, 256]> input_1971_cast_fp16 = relu(x = input_1969_cast_fp16)[name = string("input_1971_cast_fp16")];
            string logits_1_pad_type_0 = const()[name = string("logits_1_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> logits_1_pad_0 = const()[name = string("logits_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6012288)))];
            tensor<int32, [2]> logits_1_strides_0 = const()[name = string("logits_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> logits_1_dilations_0 = const()[name = string("logits_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 logits_1_groups_0 = const()[name = string("logits_1_groups_0"), val = int32(1)];
            tensor<fp16, [1, 32, 3, 3]> model_decoder_pred_weight_to_fp16 = const()[name = string("model_decoder_pred_weight_to_fp16"), val = tensor<fp16, [1, 32, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6012416)))];
            tensor<fp16, [1]> model_decoder_pred_bias_to_fp16 = const()[name = string("model_decoder_pred_bias_to_fp16"), val = tensor<fp16, [1]>([-0.10168457])];
            tensor<fp16, [1, 1, 256, 256]> logits_1_cast_fp16 = conv(bias = model_decoder_pred_bias_to_fp16, dilations = logits_1_dilations_0, groups = logits_1_groups_0, pad = logits_1_pad_0, pad_type = logits_1_pad_type_0, strides = logits_1_strides_0, weight = model_decoder_pred_weight_to_fp16, x = input_1971_cast_fp16)[name = string("logits_1_cast_fp16")];
            string g_1_pad_type_0 = const()[name = string("g_1_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> g_1_strides_0 = const()[name = string("g_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> g_1_pad_0 = const()[name = string("g_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6013056)))];
            tensor<int32, [2]> g_1_dilations_0 = const()[name = string("g_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 g_1_groups_0 = const()[name = string("g_1_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 1, 1]> model_decoder_quality_pred_g16_conv_weight_to_fp16 = constexpr_affine_dequantize()[axis = int32(0), quantized_data = tensor<int8, [64, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6013184))), scale = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017344))), zero_point = tensor<int8, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017536)))];
            tensor<fp16, [64]> model_decoder_quality_pred_g16_conv_bias_to_fp16 = const()[name = string("model_decoder_quality_pred_g16_conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017664)))];
            tensor<fp16, [1, 64, 32, 32]> g_1_cast_fp16 = conv(bias = model_decoder_quality_pred_g16_conv_bias_to_fp16, dilations = g_1_dilations_0, groups = g_1_groups_0, pad = g_1_pad_0, pad_type = g_1_pad_type_0, strides = g_1_strides_0, weight = model_decoder_quality_pred_g16_conv_weight_to_fp16, x = input_1935_cast_fp16)[name = string("g_1_cast_fp16")];
            tensor<int32, [2]> var_12239 = const()[name = string("op_12239"), val = tensor<int32, [2]>([32, 32])];
            tensor<int32, [2]> var_12240 = const()[name = string("op_12240"), val = tensor<int32, [2]>([32, 32])];
            string input_1973_pad_type_0 = const()[name = string("input_1973_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_1973_pad_0 = const()[name = string("input_1973_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017856)))];
            bool input_1973_ceil_mode_0 = const()[name = string("input_1973_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 64, 1, 1]> input_1973_cast_fp16 = max_pool(ceil_mode = input_1973_ceil_mode_0, kernel_sizes = var_12239, pad = input_1973_pad_0, pad_type = input_1973_pad_type_0, strides = var_12240, x = g_1_cast_fp16)[name = string("input_1973_cast_fp16")];
            string qualitys_1_pad_type_0 = const()[name = string("qualitys_1_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> qualitys_1_strides_0 = const()[name = string("qualitys_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> qualitys_1_pad_0 = const()[name = string("qualitys_1_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6017984)))];
            tensor<int32, [2]> qualitys_1_dilations_0 = const()[name = string("qualitys_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 qualitys_1_groups_0 = const()[name = string("qualitys_1_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1, 1]> model_decoder_quality_pred_transform_weight_to_fp16 = const()[name = string("model_decoder_quality_pred_transform_weight_to_fp16"), val = tensor<fp16, [1, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6018112)))];
            tensor<fp16, [1]> model_decoder_quality_pred_transform_bias_to_fp16 = const()[name = string("model_decoder_quality_pred_transform_bias_to_fp16"), val = tensor<fp16, [1]>([0.0545654297])];
            tensor<fp16, [1, 1, 1, 1]> qualitys_1_cast_fp16 = conv(bias = model_decoder_quality_pred_transform_bias_to_fp16, dilations = qualitys_1_dilations_0, groups = qualitys_1_groups_0, pad = qualitys_1_pad_0, pad_type = qualitys_1_pad_type_0, strides = qualitys_1_strides_0, weight = model_decoder_quality_pred_transform_weight_to_fp16, x = input_1973_cast_fp16)[name = string("qualitys_1_cast_fp16")];
            fp32 logits_3_scale_factor_height_0 = const()[name = string("logits_3_scale_factor_height_0"), val = fp32(2)];
            fp32 logits_3_scale_factor_width_0 = const()[name = string("logits_3_scale_factor_width_0"), val = fp32(2)];
            bool logits_3_align_corners_0 = const()[name = string("logits_3_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 1, 512, 512]> logits_3_cast_fp16 = upsample_bilinear(align_corners = logits_3_align_corners_0, scale_factor_height = logits_3_scale_factor_height_0, scale_factor_width = logits_3_scale_factor_width_0, x = logits_1_cast_fp16)[name = string("logits_3_cast_fp16")];
            fp16 var_12306_to_fp16 = const()[name = string("op_12306_to_fp16"), val = fp16(2)];
            tensor<fp16, [1, 1, 512, 512]> var_12307_cast_fp16 = mul(x = logits_3_cast_fp16, y = var_12306_to_fp16)[name = string("op_12307_cast_fp16")];
            tensor<fp16, [1, 1, 512, 512]> prob_cast_fp16 = sigmoid(x = logits_3_cast_fp16)[name = string("prob_cast_fp16")];
            tensor<fp16, [1, 1, 1, 1]> update_q = sigmoid(x = qualitys_1_cast_fp16)[name = string("op_16845_cast_fp16")];
            int32 var_16879 = const()[name = string("op_16879"), val = int32(1)];
            bool input_2687_interleave_0 = const()[name = string("input_2687_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 2, 512, 512]> input_2687_cast_fp16 = concat(axis = var_16879, interleave = input_2687_interleave_0, values = (prob_cast_fp16, other_masks_1_to_fp16))[name = string("input_2687_cast_fp16")];
            string coord_features_pad_type_0 = const()[name = string("coord_features_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> coord_features_pad_0 = const()[name = string("coord_features_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6251328)))];
            tensor<int32, [2]> coord_features_strides_0 = const()[name = string("coord_features_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> coord_features_dilations_0 = const()[name = string("coord_features_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 coord_features_groups_0 = const()[name = string("coord_features_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 256, 256]> coord_features_cast_fp16 = conv(bias = model_value_encoder_mask_conv_bias_to_fp16, dilations = coord_features_dilations_0, groups = coord_features_groups_0, pad = coord_features_pad_0, pad_type = coord_features_pad_type_0, strides = coord_features_strides_0, weight = model_value_encoder_mask_conv_weight_to_fp16, x = input_2687_cast_fp16)[name = string("coord_features_cast_fp16")];
            tensor<fp16, [1, 24, 256, 256]> input_2695_cast_fp16 = add(x = x_33_cast_fp16, y = coord_features_cast_fp16)[name = string("input_2695_cast_fp16")];
            tensor<int32, [2]> var_19696 = const()[name = string("op_19696"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_19697 = const()[name = string("op_19697"), val = tensor<int32, [2]>([2, 2])];
            string input_2697_pad_type_0 = const()[name = string("input_2697_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2697_pad_0 = const()[name = string("input_2697_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6251456)))];
            bool input_2697_ceil_mode_0 = const()[name = string("input_2697_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 24, 128, 128]> input_2697_cast_fp16 = max_pool(ceil_mode = input_2697_ceil_mode_0, kernel_sizes = var_19696, pad = input_2697_pad_0, pad_type = input_2697_pad_type_0, strides = var_19697, x = input_2695_cast_fp16)[name = string("input_2697_cast_fp16")];
            string input_2703_pad_type_0 = const()[name = string("input_2703_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2703_strides_0 = const()[name = string("input_2703_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2703_pad_0 = const()[name = string("input_2703_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6251584)))];
            tensor<int32, [2]> input_2703_dilations_0 = const()[name = string("input_2703_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2703_groups_0 = const()[name = string("input_2703_groups_0"), val = int32(1)];
            tensor<fp16, [1, 144, 128, 128]> input_2705_cast_fp16 = conv(bias = const_292_to_fp16, dilations = input_2703_dilations_0, groups = input_2703_groups_0, pad = input_2703_pad_0, pad_type = input_2703_pad_type_0, strides = input_2703_strides_0, weight = const_291_to_fp16, x = input_2697_cast_fp16)[name = string("input_2705_cast_fp16")];
            tensor<fp16, [1, 144, 128, 128]> input_2707_cast_fp16 = relu(x = input_2705_cast_fp16)[name = string("input_2707_cast_fp16")];
            string input_2709_pad_type_0 = const()[name = string("input_2709_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2709_pad_0 = const()[name = string("input_2709_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6251712)))];
            tensor<int32, [2]> input_2709_strides_0 = const()[name = string("input_2709_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_2709_groups_0 = const()[name = string("input_2709_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_2709_dilations_0 = const()[name = string("input_2709_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 144, 64, 64]> input_2711_cast_fp16 = conv(bias = const_294_to_fp16, dilations = input_2709_dilations_0, groups = input_2709_groups_0, pad = input_2709_pad_0, pad_type = input_2709_pad_type_0, strides = input_2709_strides_0, weight = const_293_to_fp16, x = input_2707_cast_fp16)[name = string("input_2711_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_2713_cast_fp16 = relu(x = input_2711_cast_fp16)[name = string("input_2713_cast_fp16")];
            string input_2715_pad_type_0 = const()[name = string("input_2715_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2715_strides_0 = const()[name = string("input_2715_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2715_pad_0 = const()[name = string("input_2715_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6251840)))];
            tensor<int32, [2]> input_2715_dilations_0 = const()[name = string("input_2715_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2715_groups_0 = const()[name = string("input_2715_groups_0"), val = int32(1)];
            tensor<fp16, [1, 144, 64, 64]> x_183_cast_fp16 = conv(bias = const_296_to_fp16, dilations = input_2715_dilations_0, groups = input_2715_groups_0, pad = input_2715_pad_0, pad_type = input_2715_pad_type_0, strides = input_2715_strides_0, weight = const_295_to_fp16, x = input_2713_cast_fp16)[name = string("x_183_cast_fp16")];
            tensor<int32, [4]> var_19735_begin_0 = const()[name = string("op_19735_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6251968)))];
            tensor<int32, [4]> var_19735_end_0 = const()[name = string("op_19735_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6252096)))];
            tensor<bool, [4]> var_19735_end_mask_0 = const()[name = string("op_19735_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_19735_cast_fp16 = slice_by_index(begin = var_19735_begin_0, end = var_19735_end_0, end_mask = var_19735_end_mask_0, x = x_183_cast_fp16)[name = string("op_19735_cast_fp16")];
            tensor<int32, [4]> var_19739_begin_0 = const()[name = string("op_19739_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6252224)))];
            tensor<int32, [4]> var_19739_end_0 = const()[name = string("op_19739_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6252352)))];
            tensor<bool, [4]> var_19739_end_mask_0 = const()[name = string("op_19739_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_19739_cast_fp16 = slice_by_index(begin = var_19739_begin_0, end = var_19739_end_0, end_mask = var_19739_end_mask_0, x = x_183_cast_fp16)[name = string("op_19739_cast_fp16")];
            tensor<int32, [4]> var_19743_begin_0 = const()[name = string("op_19743_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6252480)))];
            tensor<int32, [4]> var_19743_end_0 = const()[name = string("op_19743_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6252608)))];
            tensor<bool, [4]> var_19743_end_mask_0 = const()[name = string("op_19743_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_19743_cast_fp16 = slice_by_index(begin = var_19743_begin_0, end = var_19743_end_0, end_mask = var_19743_end_mask_0, x = x_183_cast_fp16)[name = string("op_19743_cast_fp16")];
            tensor<int32, [4]> var_19747_begin_0 = const()[name = string("op_19747_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6252736)))];
            tensor<int32, [4]> var_19747_end_0 = const()[name = string("op_19747_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6252864)))];
            tensor<bool, [4]> var_19747_end_mask_0 = const()[name = string("op_19747_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_19747_cast_fp16 = slice_by_index(begin = var_19747_begin_0, end = var_19747_end_0, end_mask = var_19747_end_mask_0, x = x_183_cast_fp16)[name = string("op_19747_cast_fp16")];
            string input_2719_pad_type_0 = const()[name = string("input_2719_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2719_strides_0 = const()[name = string("input_2719_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2719_pad_0 = const()[name = string("input_2719_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6252992)))];
            tensor<int32, [2]> input_2719_dilations_0 = const()[name = string("input_2719_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2719_groups_0 = const()[name = string("input_2719_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_948_to_fp16 = const()[name = string("const_948_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6253120)))];
            tensor<fp16, [1, 36, 64, 64]> input_2721_cast_fp16 = conv(bias = const_948_to_fp16, dilations = input_2719_dilations_0, groups = input_2719_groups_0, pad = input_2719_pad_0, pad_type = input_2719_pad_type_0, strides = input_2719_strides_0, weight = const_297_to_fp16, x = var_19739_cast_fp16)[name = string("input_2721_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_2723_cast_fp16 = relu(x = input_2721_cast_fp16)[name = string("input_2723_cast_fp16")];
            string input_2725_pad_type_0 = const()[name = string("input_2725_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2725_pad_0 = const()[name = string("input_2725_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6253312)))];
            int32 input_2725_groups_0 = const()[name = string("input_2725_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_2725_strides_0 = const()[name = string("input_2725_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2725_dilations_0 = const()[name = string("input_2725_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36]> const_950_to_fp16 = const()[name = string("const_950_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6253440)))];
            tensor<fp16, [1, 36, 64, 64]> input_2727_cast_fp16 = conv(bias = const_950_to_fp16, dilations = input_2725_dilations_0, groups = input_2725_groups_0, pad = input_2725_pad_0, pad_type = input_2725_pad_type_0, strides = input_2725_strides_0, weight = const_299_to_fp16, x = input_2723_cast_fp16)[name = string("input_2727_cast_fp16")];
            string input_2729_pad_type_0 = const()[name = string("input_2729_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2729_strides_0 = const()[name = string("input_2729_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2729_pad_0 = const()[name = string("input_2729_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6253632)))];
            tensor<int32, [2]> input_2729_dilations_0 = const()[name = string("input_2729_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2729_groups_0 = const()[name = string("input_2729_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_952_to_fp16 = const()[name = string("const_952_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6253760)))];
            tensor<fp16, [1, 36, 64, 64]> input_2731_cast_fp16 = conv(bias = const_952_to_fp16, dilations = input_2729_dilations_0, groups = input_2729_groups_0, pad = input_2729_pad_0, pad_type = input_2729_pad_type_0, strides = input_2729_strides_0, weight = const_301_to_fp16, x = input_2727_cast_fp16)[name = string("input_2731_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_81_cast_fp16 = relu(x = input_2731_cast_fp16)[name = string("out1_81_cast_fp16")];
            string input_2735_pad_type_0 = const()[name = string("input_2735_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2735_strides_0 = const()[name = string("input_2735_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2735_pad_0 = const()[name = string("input_2735_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6253952)))];
            tensor<int32, [2]> input_2735_dilations_0 = const()[name = string("input_2735_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2735_groups_0 = const()[name = string("input_2735_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_954_to_fp16 = const()[name = string("const_954_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6254080)))];
            tensor<fp16, [1, 36, 64, 64]> input_2737_cast_fp16 = conv(bias = const_954_to_fp16, dilations = input_2735_dilations_0, groups = input_2735_groups_0, pad = input_2735_pad_0, pad_type = input_2735_pad_type_0, strides = input_2735_strides_0, weight = const_303_to_fp16, x = var_19743_cast_fp16)[name = string("input_2737_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_2739_cast_fp16 = relu(x = input_2737_cast_fp16)[name = string("input_2739_cast_fp16")];
            string input_2741_pad_type_0 = const()[name = string("input_2741_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2741_pad_0 = const()[name = string("input_2741_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6254272)))];
            int32 input_2741_groups_0 = const()[name = string("input_2741_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_2741_strides_0 = const()[name = string("input_2741_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2741_dilations_0 = const()[name = string("input_2741_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36]> const_956_to_fp16 = const()[name = string("const_956_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6254400)))];
            tensor<fp16, [1, 36, 64, 64]> input_2743_cast_fp16 = conv(bias = const_956_to_fp16, dilations = input_2741_dilations_0, groups = input_2741_groups_0, pad = input_2741_pad_0, pad_type = input_2741_pad_type_0, strides = input_2741_strides_0, weight = const_305_to_fp16, x = input_2739_cast_fp16)[name = string("input_2743_cast_fp16")];
            string input_2745_pad_type_0 = const()[name = string("input_2745_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2745_strides_0 = const()[name = string("input_2745_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2745_pad_0 = const()[name = string("input_2745_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6254592)))];
            tensor<int32, [2]> input_2745_dilations_0 = const()[name = string("input_2745_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2745_groups_0 = const()[name = string("input_2745_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_958_to_fp16 = const()[name = string("const_958_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6254720)))];
            tensor<fp16, [1, 36, 64, 64]> input_2747_cast_fp16 = conv(bias = const_958_to_fp16, dilations = input_2745_dilations_0, groups = input_2745_groups_0, pad = input_2745_pad_0, pad_type = input_2745_pad_type_0, strides = input_2745_strides_0, weight = const_307_to_fp16, x = input_2743_cast_fp16)[name = string("input_2747_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_81_cast_fp16 = relu(x = input_2747_cast_fp16)[name = string("out2_81_cast_fp16")];
            string input_2751_pad_type_0 = const()[name = string("input_2751_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2751_strides_0 = const()[name = string("input_2751_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2751_pad_0 = const()[name = string("input_2751_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6254912)))];
            tensor<int32, [2]> input_2751_dilations_0 = const()[name = string("input_2751_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2751_groups_0 = const()[name = string("input_2751_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_960_to_fp16 = const()[name = string("const_960_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6255040)))];
            tensor<fp16, [1, 36, 64, 64]> input_2753_cast_fp16 = conv(bias = const_960_to_fp16, dilations = input_2751_dilations_0, groups = input_2751_groups_0, pad = input_2751_pad_0, pad_type = input_2751_pad_type_0, strides = input_2751_strides_0, weight = const_309_to_fp16, x = var_19747_cast_fp16)[name = string("input_2753_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_2755_cast_fp16 = relu(x = input_2753_cast_fp16)[name = string("input_2755_cast_fp16")];
            string input_2757_pad_type_0 = const()[name = string("input_2757_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2757_pad_0 = const()[name = string("input_2757_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6255232)))];
            int32 input_2757_groups_0 = const()[name = string("input_2757_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_2757_strides_0 = const()[name = string("input_2757_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2757_dilations_0 = const()[name = string("input_2757_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36]> const_962_to_fp16 = const()[name = string("const_962_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6255360)))];
            tensor<fp16, [1, 36, 64, 64]> input_2759_cast_fp16 = conv(bias = const_962_to_fp16, dilations = input_2757_dilations_0, groups = input_2757_groups_0, pad = input_2757_pad_0, pad_type = input_2757_pad_type_0, strides = input_2757_strides_0, weight = const_311_to_fp16, x = input_2755_cast_fp16)[name = string("input_2759_cast_fp16")];
            string input_2761_pad_type_0 = const()[name = string("input_2761_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2761_strides_0 = const()[name = string("input_2761_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2761_pad_0 = const()[name = string("input_2761_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6255552)))];
            tensor<int32, [2]> input_2761_dilations_0 = const()[name = string("input_2761_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2761_groups_0 = const()[name = string("input_2761_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_964_to_fp16 = const()[name = string("const_964_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6255680)))];
            tensor<fp16, [1, 36, 64, 64]> input_2763_cast_fp16 = conv(bias = const_964_to_fp16, dilations = input_2761_dilations_0, groups = input_2761_groups_0, pad = input_2761_pad_0, pad_type = input_2761_pad_type_0, strides = input_2761_strides_0, weight = const_313_to_fp16, x = input_2759_cast_fp16)[name = string("input_2763_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_81_cast_fp16 = relu(x = input_2763_cast_fp16)[name = string("out3_81_cast_fp16")];
            bool input_2765_interleave_0 = const()[name = string("input_2765_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_2765_cast_fp16 = concat(axis = var_16879, interleave = input_2765_interleave_0, values = (var_19735_cast_fp16, out1_81_cast_fp16, out2_81_cast_fp16, out3_81_cast_fp16))[name = string("input_2765_cast_fp16")];
            string input_2767_pad_type_0 = const()[name = string("input_2767_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2767_strides_0 = const()[name = string("input_2767_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2767_pad_0 = const()[name = string("input_2767_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6255872)))];
            tensor<int32, [2]> input_2767_dilations_0 = const()[name = string("input_2767_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2767_groups_0 = const()[name = string("input_2767_groups_0"), val = int32(1)];
            tensor<fp16, [1, 144, 64, 64]> input_2769_cast_fp16 = conv(bias = const_316_to_fp16, dilations = input_2767_dilations_0, groups = input_2767_groups_0, pad = input_2767_pad_0, pad_type = input_2767_pad_type_0, strides = input_2767_strides_0, weight = const_315_to_fp16, x = input_2765_cast_fp16)[name = string("input_2769_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_2771_cast_fp16 = relu(x = input_2769_cast_fp16)[name = string("input_2771_cast_fp16")];
            string input_2773_pad_type_0 = const()[name = string("input_2773_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2773_pad_0 = const()[name = string("input_2773_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6256000)))];
            int32 input_2773_groups_0 = const()[name = string("input_2773_groups_0"), val = int32(144)];
            tensor<int32, [2]> input_2773_strides_0 = const()[name = string("input_2773_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2773_dilations_0 = const()[name = string("input_2773_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 144, 64, 64]> input_2775_cast_fp16 = conv(bias = const_318_to_fp16, dilations = input_2773_dilations_0, groups = input_2773_groups_0, pad = input_2773_pad_0, pad_type = input_2773_pad_type_0, strides = input_2773_strides_0, weight = const_317_to_fp16, x = input_2771_cast_fp16)[name = string("input_2775_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> input_2777_cast_fp16 = relu(x = input_2775_cast_fp16)[name = string("input_2777_cast_fp16")];
            string input_2779_pad_type_0 = const()[name = string("input_2779_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2779_strides_0 = const()[name = string("input_2779_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2779_pad_0 = const()[name = string("input_2779_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6256128)))];
            tensor<int32, [2]> input_2779_dilations_0 = const()[name = string("input_2779_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2779_groups_0 = const()[name = string("input_2779_groups_0"), val = int32(1)];
            tensor<fp16, [1, 144, 64, 64]> y_111_cast_fp16 = conv(bias = const_320_to_fp16, dilations = input_2779_dilations_0, groups = input_2779_groups_0, pad = input_2779_pad_0, pad_type = input_2779_pad_type_0, strides = input_2779_strides_0, weight = const_319_to_fp16, x = input_2777_cast_fp16)[name = string("y_111_cast_fp16")];
            tensor<fp16, [1, 144, 64, 64]> x_185_cast_fp16 = add(x = input_2765_cast_fp16, y = y_111_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> var_19847_begin_0 = const()[name = string("op_19847_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6256256)))];
            tensor<int32, [4]> var_19847_end_0 = const()[name = string("op_19847_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6256384)))];
            tensor<bool, [4]> var_19847_end_mask_0 = const()[name = string("op_19847_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_19847_cast_fp16 = slice_by_index(begin = var_19847_begin_0, end = var_19847_end_0, end_mask = var_19847_end_mask_0, x = x_185_cast_fp16)[name = string("op_19847_cast_fp16")];
            tensor<int32, [4]> var_19851_begin_0 = const()[name = string("op_19851_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6256512)))];
            tensor<int32, [4]> var_19851_end_0 = const()[name = string("op_19851_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6256640)))];
            tensor<bool, [4]> var_19851_end_mask_0 = const()[name = string("op_19851_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_19851_cast_fp16 = slice_by_index(begin = var_19851_begin_0, end = var_19851_end_0, end_mask = var_19851_end_mask_0, x = x_185_cast_fp16)[name = string("op_19851_cast_fp16")];
            tensor<int32, [4]> var_19855_begin_0 = const()[name = string("op_19855_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6256768)))];
            tensor<int32, [4]> var_19855_end_0 = const()[name = string("op_19855_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6256896)))];
            tensor<bool, [4]> var_19855_end_mask_0 = const()[name = string("op_19855_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_19855_cast_fp16 = slice_by_index(begin = var_19855_begin_0, end = var_19855_end_0, end_mask = var_19855_end_mask_0, x = x_185_cast_fp16)[name = string("op_19855_cast_fp16")];
            tensor<int32, [4]> var_19859_begin_0 = const()[name = string("op_19859_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6257024)))];
            tensor<int32, [4]> var_19859_end_0 = const()[name = string("op_19859_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6257152)))];
            tensor<bool, [4]> var_19859_end_mask_0 = const()[name = string("op_19859_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 36, 64, 64]> var_19859_cast_fp16 = slice_by_index(begin = var_19859_begin_0, end = var_19859_end_0, end_mask = var_19859_end_mask_0, x = x_185_cast_fp16)[name = string("op_19859_cast_fp16")];
            string input_2783_pad_type_0 = const()[name = string("input_2783_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2783_strides_0 = const()[name = string("input_2783_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2783_pad_0 = const()[name = string("input_2783_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6257280)))];
            tensor<int32, [2]> input_2783_dilations_0 = const()[name = string("input_2783_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2783_groups_0 = const()[name = string("input_2783_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_972_to_fp16 = const()[name = string("const_972_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6257408)))];
            tensor<fp16, [1, 36, 64, 64]> input_2785_cast_fp16 = conv(bias = const_972_to_fp16, dilations = input_2783_dilations_0, groups = input_2783_groups_0, pad = input_2783_pad_0, pad_type = input_2783_pad_type_0, strides = input_2783_strides_0, weight = const_321_to_fp16, x = var_19851_cast_fp16)[name = string("input_2785_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_2787_cast_fp16 = relu(x = input_2785_cast_fp16)[name = string("input_2787_cast_fp16")];
            string input_2789_pad_type_0 = const()[name = string("input_2789_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2789_pad_0 = const()[name = string("input_2789_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6257600)))];
            int32 input_2789_groups_0 = const()[name = string("input_2789_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_2789_strides_0 = const()[name = string("input_2789_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2789_dilations_0 = const()[name = string("input_2789_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36]> const_974_to_fp16 = const()[name = string("const_974_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6257728)))];
            tensor<fp16, [1, 36, 64, 64]> input_2791_cast_fp16 = conv(bias = const_974_to_fp16, dilations = input_2789_dilations_0, groups = input_2789_groups_0, pad = input_2789_pad_0, pad_type = input_2789_pad_type_0, strides = input_2789_strides_0, weight = const_323_to_fp16, x = input_2787_cast_fp16)[name = string("input_2791_cast_fp16")];
            string input_2793_pad_type_0 = const()[name = string("input_2793_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2793_strides_0 = const()[name = string("input_2793_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2793_pad_0 = const()[name = string("input_2793_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6257920)))];
            tensor<int32, [2]> input_2793_dilations_0 = const()[name = string("input_2793_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2793_groups_0 = const()[name = string("input_2793_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_976_to_fp16 = const()[name = string("const_976_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6258048)))];
            tensor<fp16, [1, 36, 64, 64]> input_2795_cast_fp16 = conv(bias = const_976_to_fp16, dilations = input_2793_dilations_0, groups = input_2793_groups_0, pad = input_2793_pad_0, pad_type = input_2793_pad_type_0, strides = input_2793_strides_0, weight = const_325_to_fp16, x = input_2791_cast_fp16)[name = string("input_2795_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out1_83_cast_fp16 = relu(x = input_2795_cast_fp16)[name = string("out1_83_cast_fp16")];
            string input_2799_pad_type_0 = const()[name = string("input_2799_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2799_strides_0 = const()[name = string("input_2799_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2799_pad_0 = const()[name = string("input_2799_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6258240)))];
            tensor<int32, [2]> input_2799_dilations_0 = const()[name = string("input_2799_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2799_groups_0 = const()[name = string("input_2799_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_978_to_fp16 = const()[name = string("const_978_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6258368)))];
            tensor<fp16, [1, 36, 64, 64]> input_2801_cast_fp16 = conv(bias = const_978_to_fp16, dilations = input_2799_dilations_0, groups = input_2799_groups_0, pad = input_2799_pad_0, pad_type = input_2799_pad_type_0, strides = input_2799_strides_0, weight = const_327_to_fp16, x = var_19855_cast_fp16)[name = string("input_2801_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_2803_cast_fp16 = relu(x = input_2801_cast_fp16)[name = string("input_2803_cast_fp16")];
            string input_2805_pad_type_0 = const()[name = string("input_2805_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2805_pad_0 = const()[name = string("input_2805_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6258560)))];
            int32 input_2805_groups_0 = const()[name = string("input_2805_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_2805_strides_0 = const()[name = string("input_2805_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2805_dilations_0 = const()[name = string("input_2805_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36]> const_980_to_fp16 = const()[name = string("const_980_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6258688)))];
            tensor<fp16, [1, 36, 64, 64]> input_2807_cast_fp16 = conv(bias = const_980_to_fp16, dilations = input_2805_dilations_0, groups = input_2805_groups_0, pad = input_2805_pad_0, pad_type = input_2805_pad_type_0, strides = input_2805_strides_0, weight = const_329_to_fp16, x = input_2803_cast_fp16)[name = string("input_2807_cast_fp16")];
            string input_2809_pad_type_0 = const()[name = string("input_2809_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2809_strides_0 = const()[name = string("input_2809_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2809_pad_0 = const()[name = string("input_2809_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6258880)))];
            tensor<int32, [2]> input_2809_dilations_0 = const()[name = string("input_2809_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2809_groups_0 = const()[name = string("input_2809_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_982_to_fp16 = const()[name = string("const_982_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6259008)))];
            tensor<fp16, [1, 36, 64, 64]> input_2811_cast_fp16 = conv(bias = const_982_to_fp16, dilations = input_2809_dilations_0, groups = input_2809_groups_0, pad = input_2809_pad_0, pad_type = input_2809_pad_type_0, strides = input_2809_strides_0, weight = const_331_to_fp16, x = input_2807_cast_fp16)[name = string("input_2811_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out2_83_cast_fp16 = relu(x = input_2811_cast_fp16)[name = string("out2_83_cast_fp16")];
            string input_2815_pad_type_0 = const()[name = string("input_2815_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2815_strides_0 = const()[name = string("input_2815_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2815_pad_0 = const()[name = string("input_2815_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6259200)))];
            tensor<int32, [2]> input_2815_dilations_0 = const()[name = string("input_2815_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2815_groups_0 = const()[name = string("input_2815_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_984_to_fp16 = const()[name = string("const_984_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6259328)))];
            tensor<fp16, [1, 36, 64, 64]> input_2817_cast_fp16 = conv(bias = const_984_to_fp16, dilations = input_2815_dilations_0, groups = input_2815_groups_0, pad = input_2815_pad_0, pad_type = input_2815_pad_type_0, strides = input_2815_strides_0, weight = const_333_to_fp16, x = var_19859_cast_fp16)[name = string("input_2817_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> input_2819_cast_fp16 = relu(x = input_2817_cast_fp16)[name = string("input_2819_cast_fp16")];
            string input_2821_pad_type_0 = const()[name = string("input_2821_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2821_pad_0 = const()[name = string("input_2821_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6259520)))];
            int32 input_2821_groups_0 = const()[name = string("input_2821_groups_0"), val = int32(36)];
            tensor<int32, [2]> input_2821_strides_0 = const()[name = string("input_2821_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2821_dilations_0 = const()[name = string("input_2821_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [36]> const_986_to_fp16 = const()[name = string("const_986_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6259648)))];
            tensor<fp16, [1, 36, 64, 64]> input_2823_cast_fp16 = conv(bias = const_986_to_fp16, dilations = input_2821_dilations_0, groups = input_2821_groups_0, pad = input_2821_pad_0, pad_type = input_2821_pad_type_0, strides = input_2821_strides_0, weight = const_335_to_fp16, x = input_2819_cast_fp16)[name = string("input_2823_cast_fp16")];
            string input_2825_pad_type_0 = const()[name = string("input_2825_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2825_strides_0 = const()[name = string("input_2825_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2825_pad_0 = const()[name = string("input_2825_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6259840)))];
            tensor<int32, [2]> input_2825_dilations_0 = const()[name = string("input_2825_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2825_groups_0 = const()[name = string("input_2825_groups_0"), val = int32(1)];
            tensor<fp16, [36]> const_988_to_fp16 = const()[name = string("const_988_to_fp16"), val = tensor<fp16, [36]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6259968)))];
            tensor<fp16, [1, 36, 64, 64]> input_2827_cast_fp16 = conv(bias = const_988_to_fp16, dilations = input_2825_dilations_0, groups = input_2825_groups_0, pad = input_2825_pad_0, pad_type = input_2825_pad_type_0, strides = input_2825_strides_0, weight = const_337_to_fp16, x = input_2823_cast_fp16)[name = string("input_2827_cast_fp16")];
            tensor<fp16, [1, 36, 64, 64]> out3_83_cast_fp16 = relu(x = input_2827_cast_fp16)[name = string("out3_83_cast_fp16")];
            bool input_2829_interleave_0 = const()[name = string("input_2829_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 144, 64, 64]> input_2829_cast_fp16 = concat(axis = var_16879, interleave = input_2829_interleave_0, values = (var_19847_cast_fp16, out1_83_cast_fp16, out2_83_cast_fp16, out3_83_cast_fp16))[name = string("input_2829_cast_fp16")];
            string input_2831_pad_type_0 = const()[name = string("input_2831_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2831_strides_0 = const()[name = string("input_2831_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2831_pad_0 = const()[name = string("input_2831_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6260160)))];
            tensor<int32, [2]> input_2831_dilations_0 = const()[name = string("input_2831_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2831_groups_0 = const()[name = string("input_2831_groups_0"), val = int32(1)];
            tensor<fp16, [1, 256, 64, 64]> input_2833_cast_fp16 = conv(bias = const_340_to_fp16, dilations = input_2831_dilations_0, groups = input_2831_groups_0, pad = input_2831_pad_0, pad_type = input_2831_pad_type_0, strides = input_2831_strides_0, weight = const_339_to_fp16, x = input_2829_cast_fp16)[name = string("input_2833_cast_fp16")];
            tensor<fp16, [1, 256, 64, 64]> input_2835_cast_fp16 = relu(x = input_2833_cast_fp16)[name = string("input_2835_cast_fp16")];
            string input_2837_pad_type_0 = const()[name = string("input_2837_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2837_pad_0 = const()[name = string("input_2837_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6260288)))];
            tensor<int32, [2]> input_2837_strides_0 = const()[name = string("input_2837_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_2837_groups_0 = const()[name = string("input_2837_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_2837_dilations_0 = const()[name = string("input_2837_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 256, 32, 32]> input_2839_cast_fp16 = conv(bias = const_342_to_fp16, dilations = input_2837_dilations_0, groups = input_2837_groups_0, pad = input_2837_pad_0, pad_type = input_2837_pad_type_0, strides = input_2837_strides_0, weight = const_341_to_fp16, x = input_2835_cast_fp16)[name = string("input_2839_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_2841_cast_fp16 = relu(x = input_2839_cast_fp16)[name = string("input_2841_cast_fp16")];
            string input_2843_pad_type_0 = const()[name = string("input_2843_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2843_strides_0 = const()[name = string("input_2843_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2843_pad_0 = const()[name = string("input_2843_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6260416)))];
            tensor<int32, [2]> input_2843_dilations_0 = const()[name = string("input_2843_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2843_groups_0 = const()[name = string("input_2843_groups_0"), val = int32(1)];
            tensor<fp16, [1, 256, 32, 32]> x_187_cast_fp16 = conv(bias = const_344_to_fp16, dilations = input_2843_dilations_0, groups = input_2843_groups_0, pad = input_2843_pad_0, pad_type = input_2843_pad_type_0, strides = input_2843_strides_0, weight = const_343_to_fp16, x = input_2841_cast_fp16)[name = string("x_187_cast_fp16")];
            tensor<int32, [4]> var_19958_begin_0 = const()[name = string("op_19958_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6260544)))];
            tensor<int32, [4]> var_19958_end_0 = const()[name = string("op_19958_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6260672)))];
            tensor<bool, [4]> var_19958_end_mask_0 = const()[name = string("op_19958_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_19958_cast_fp16 = slice_by_index(begin = var_19958_begin_0, end = var_19958_end_0, end_mask = var_19958_end_mask_0, x = x_187_cast_fp16)[name = string("op_19958_cast_fp16")];
            tensor<int32, [4]> var_19962_begin_0 = const()[name = string("op_19962_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6260800)))];
            tensor<int32, [4]> var_19962_end_0 = const()[name = string("op_19962_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6260928)))];
            tensor<bool, [4]> var_19962_end_mask_0 = const()[name = string("op_19962_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_19962_cast_fp16 = slice_by_index(begin = var_19962_begin_0, end = var_19962_end_0, end_mask = var_19962_end_mask_0, x = x_187_cast_fp16)[name = string("op_19962_cast_fp16")];
            tensor<int32, [4]> var_19966_begin_0 = const()[name = string("op_19966_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6261056)))];
            tensor<int32, [4]> var_19966_end_0 = const()[name = string("op_19966_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6261184)))];
            tensor<bool, [4]> var_19966_end_mask_0 = const()[name = string("op_19966_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_19966_cast_fp16 = slice_by_index(begin = var_19966_begin_0, end = var_19966_end_0, end_mask = var_19966_end_mask_0, x = x_187_cast_fp16)[name = string("op_19966_cast_fp16")];
            tensor<int32, [4]> var_19970_begin_0 = const()[name = string("op_19970_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6261312)))];
            tensor<int32, [4]> var_19970_end_0 = const()[name = string("op_19970_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6261440)))];
            tensor<bool, [4]> var_19970_end_mask_0 = const()[name = string("op_19970_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_19970_cast_fp16 = slice_by_index(begin = var_19970_begin_0, end = var_19970_end_0, end_mask = var_19970_end_mask_0, x = x_187_cast_fp16)[name = string("op_19970_cast_fp16")];
            string input_2847_pad_type_0 = const()[name = string("input_2847_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2847_strides_0 = const()[name = string("input_2847_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2847_pad_0 = const()[name = string("input_2847_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6261568)))];
            tensor<int32, [2]> input_2847_dilations_0 = const()[name = string("input_2847_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2847_groups_0 = const()[name = string("input_2847_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_996_to_fp16 = const()[name = string("const_996_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6261696)))];
            tensor<fp16, [1, 64, 32, 32]> input_2849_cast_fp16 = conv(bias = const_996_to_fp16, dilations = input_2847_dilations_0, groups = input_2847_groups_0, pad = input_2847_pad_0, pad_type = input_2847_pad_type_0, strides = input_2847_strides_0, weight = const_345_to_fp16, x = var_19962_cast_fp16)[name = string("input_2849_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_2851_cast_fp16 = relu(x = input_2849_cast_fp16)[name = string("input_2851_cast_fp16")];
            string input_2853_pad_type_0 = const()[name = string("input_2853_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2853_pad_0 = const()[name = string("input_2853_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6261888)))];
            int32 input_2853_groups_0 = const()[name = string("input_2853_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_2853_strides_0 = const()[name = string("input_2853_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2853_dilations_0 = const()[name = string("input_2853_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_998_to_fp16 = const()[name = string("const_998_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6262016)))];
            tensor<fp16, [1, 64, 32, 32]> input_2855_cast_fp16 = conv(bias = const_998_to_fp16, dilations = input_2853_dilations_0, groups = input_2853_groups_0, pad = input_2853_pad_0, pad_type = input_2853_pad_type_0, strides = input_2853_strides_0, weight = const_347_to_fp16, x = input_2851_cast_fp16)[name = string("input_2855_cast_fp16")];
            string input_2857_pad_type_0 = const()[name = string("input_2857_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2857_strides_0 = const()[name = string("input_2857_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2857_pad_0 = const()[name = string("input_2857_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6262208)))];
            tensor<int32, [2]> input_2857_dilations_0 = const()[name = string("input_2857_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2857_groups_0 = const()[name = string("input_2857_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1000_to_fp16 = const()[name = string("const_1000_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6262336)))];
            tensor<fp16, [1, 64, 32, 32]> input_2859_cast_fp16 = conv(bias = const_1000_to_fp16, dilations = input_2857_dilations_0, groups = input_2857_groups_0, pad = input_2857_pad_0, pad_type = input_2857_pad_type_0, strides = input_2857_strides_0, weight = const_349_to_fp16, x = input_2855_cast_fp16)[name = string("input_2859_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_85_cast_fp16 = relu(x = input_2859_cast_fp16)[name = string("out1_85_cast_fp16")];
            string input_2863_pad_type_0 = const()[name = string("input_2863_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2863_strides_0 = const()[name = string("input_2863_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2863_pad_0 = const()[name = string("input_2863_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6262528)))];
            tensor<int32, [2]> input_2863_dilations_0 = const()[name = string("input_2863_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2863_groups_0 = const()[name = string("input_2863_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1002_to_fp16 = const()[name = string("const_1002_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6262656)))];
            tensor<fp16, [1, 64, 32, 32]> input_2865_cast_fp16 = conv(bias = const_1002_to_fp16, dilations = input_2863_dilations_0, groups = input_2863_groups_0, pad = input_2863_pad_0, pad_type = input_2863_pad_type_0, strides = input_2863_strides_0, weight = const_351_to_fp16, x = var_19966_cast_fp16)[name = string("input_2865_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_2867_cast_fp16 = relu(x = input_2865_cast_fp16)[name = string("input_2867_cast_fp16")];
            string input_2869_pad_type_0 = const()[name = string("input_2869_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2869_pad_0 = const()[name = string("input_2869_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6262848)))];
            int32 input_2869_groups_0 = const()[name = string("input_2869_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_2869_strides_0 = const()[name = string("input_2869_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2869_dilations_0 = const()[name = string("input_2869_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1004_to_fp16 = const()[name = string("const_1004_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6262976)))];
            tensor<fp16, [1, 64, 32, 32]> input_2871_cast_fp16 = conv(bias = const_1004_to_fp16, dilations = input_2869_dilations_0, groups = input_2869_groups_0, pad = input_2869_pad_0, pad_type = input_2869_pad_type_0, strides = input_2869_strides_0, weight = const_353_to_fp16, x = input_2867_cast_fp16)[name = string("input_2871_cast_fp16")];
            string input_2873_pad_type_0 = const()[name = string("input_2873_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2873_strides_0 = const()[name = string("input_2873_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2873_pad_0 = const()[name = string("input_2873_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6263168)))];
            tensor<int32, [2]> input_2873_dilations_0 = const()[name = string("input_2873_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2873_groups_0 = const()[name = string("input_2873_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1006_to_fp16 = const()[name = string("const_1006_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6263296)))];
            tensor<fp16, [1, 64, 32, 32]> input_2875_cast_fp16 = conv(bias = const_1006_to_fp16, dilations = input_2873_dilations_0, groups = input_2873_groups_0, pad = input_2873_pad_0, pad_type = input_2873_pad_type_0, strides = input_2873_strides_0, weight = const_355_to_fp16, x = input_2871_cast_fp16)[name = string("input_2875_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_85_cast_fp16 = relu(x = input_2875_cast_fp16)[name = string("out2_85_cast_fp16")];
            string input_2879_pad_type_0 = const()[name = string("input_2879_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2879_strides_0 = const()[name = string("input_2879_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2879_pad_0 = const()[name = string("input_2879_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6263488)))];
            tensor<int32, [2]> input_2879_dilations_0 = const()[name = string("input_2879_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2879_groups_0 = const()[name = string("input_2879_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1008_to_fp16 = const()[name = string("const_1008_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6263616)))];
            tensor<fp16, [1, 64, 32, 32]> input_2881_cast_fp16 = conv(bias = const_1008_to_fp16, dilations = input_2879_dilations_0, groups = input_2879_groups_0, pad = input_2879_pad_0, pad_type = input_2879_pad_type_0, strides = input_2879_strides_0, weight = const_357_to_fp16, x = var_19970_cast_fp16)[name = string("input_2881_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_2883_cast_fp16 = relu(x = input_2881_cast_fp16)[name = string("input_2883_cast_fp16")];
            string input_2885_pad_type_0 = const()[name = string("input_2885_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2885_pad_0 = const()[name = string("input_2885_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6263808)))];
            int32 input_2885_groups_0 = const()[name = string("input_2885_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_2885_strides_0 = const()[name = string("input_2885_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2885_dilations_0 = const()[name = string("input_2885_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1010_to_fp16 = const()[name = string("const_1010_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6263936)))];
            tensor<fp16, [1, 64, 32, 32]> input_2887_cast_fp16 = conv(bias = const_1010_to_fp16, dilations = input_2885_dilations_0, groups = input_2885_groups_0, pad = input_2885_pad_0, pad_type = input_2885_pad_type_0, strides = input_2885_strides_0, weight = const_359_to_fp16, x = input_2883_cast_fp16)[name = string("input_2887_cast_fp16")];
            string input_2889_pad_type_0 = const()[name = string("input_2889_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2889_strides_0 = const()[name = string("input_2889_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2889_pad_0 = const()[name = string("input_2889_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6264128)))];
            tensor<int32, [2]> input_2889_dilations_0 = const()[name = string("input_2889_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2889_groups_0 = const()[name = string("input_2889_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1012_to_fp16 = const()[name = string("const_1012_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6264256)))];
            tensor<fp16, [1, 64, 32, 32]> input_2891_cast_fp16 = conv(bias = const_1012_to_fp16, dilations = input_2889_dilations_0, groups = input_2889_groups_0, pad = input_2889_pad_0, pad_type = input_2889_pad_type_0, strides = input_2889_strides_0, weight = const_361_to_fp16, x = input_2887_cast_fp16)[name = string("input_2891_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_85_cast_fp16 = relu(x = input_2891_cast_fp16)[name = string("out3_85_cast_fp16")];
            bool input_2893_interleave_0 = const()[name = string("input_2893_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_2893_cast_fp16 = concat(axis = var_16879, interleave = input_2893_interleave_0, values = (var_19958_cast_fp16, out1_85_cast_fp16, out2_85_cast_fp16, out3_85_cast_fp16))[name = string("input_2893_cast_fp16")];
            string input_2895_pad_type_0 = const()[name = string("input_2895_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2895_strides_0 = const()[name = string("input_2895_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2895_pad_0 = const()[name = string("input_2895_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6264448)))];
            tensor<int32, [2]> input_2895_dilations_0 = const()[name = string("input_2895_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2895_groups_0 = const()[name = string("input_2895_groups_0"), val = int32(1)];
            tensor<fp16, [1, 256, 32, 32]> input_2897_cast_fp16 = conv(bias = const_364_to_fp16, dilations = input_2895_dilations_0, groups = input_2895_groups_0, pad = input_2895_pad_0, pad_type = input_2895_pad_type_0, strides = input_2895_strides_0, weight = const_363_to_fp16, x = input_2893_cast_fp16)[name = string("input_2897_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_2899_cast_fp16 = relu(x = input_2897_cast_fp16)[name = string("input_2899_cast_fp16")];
            string input_2901_pad_type_0 = const()[name = string("input_2901_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2901_pad_0 = const()[name = string("input_2901_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6264576)))];
            int32 input_2901_groups_0 = const()[name = string("input_2901_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_2901_strides_0 = const()[name = string("input_2901_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2901_dilations_0 = const()[name = string("input_2901_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 256, 32, 32]> input_2903_cast_fp16 = conv(bias = const_366_to_fp16, dilations = input_2901_dilations_0, groups = input_2901_groups_0, pad = input_2901_pad_0, pad_type = input_2901_pad_type_0, strides = input_2901_strides_0, weight = const_365_to_fp16, x = input_2899_cast_fp16)[name = string("input_2903_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_2905_cast_fp16 = relu(x = input_2903_cast_fp16)[name = string("input_2905_cast_fp16")];
            string input_2907_pad_type_0 = const()[name = string("input_2907_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2907_strides_0 = const()[name = string("input_2907_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2907_pad_0 = const()[name = string("input_2907_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6264704)))];
            tensor<int32, [2]> input_2907_dilations_0 = const()[name = string("input_2907_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2907_groups_0 = const()[name = string("input_2907_groups_0"), val = int32(1)];
            tensor<fp16, [1, 256, 32, 32]> y_113_cast_fp16 = conv(bias = const_368_to_fp16, dilations = input_2907_dilations_0, groups = input_2907_groups_0, pad = input_2907_pad_0, pad_type = input_2907_pad_type_0, strides = input_2907_strides_0, weight = const_367_to_fp16, x = input_2905_cast_fp16)[name = string("y_113_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_189_cast_fp16 = add(x = input_2893_cast_fp16, y = y_113_cast_fp16)[name = string("x_189_cast_fp16")];
            tensor<int32, [4]> var_20070_begin_0 = const()[name = string("op_20070_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6264832)))];
            tensor<int32, [4]> var_20070_end_0 = const()[name = string("op_20070_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6264960)))];
            tensor<bool, [4]> var_20070_end_mask_0 = const()[name = string("op_20070_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20070_cast_fp16 = slice_by_index(begin = var_20070_begin_0, end = var_20070_end_0, end_mask = var_20070_end_mask_0, x = x_189_cast_fp16)[name = string("op_20070_cast_fp16")];
            tensor<int32, [4]> var_20074_begin_0 = const()[name = string("op_20074_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6265088)))];
            tensor<int32, [4]> var_20074_end_0 = const()[name = string("op_20074_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6265216)))];
            tensor<bool, [4]> var_20074_end_mask_0 = const()[name = string("op_20074_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20074_cast_fp16 = slice_by_index(begin = var_20074_begin_0, end = var_20074_end_0, end_mask = var_20074_end_mask_0, x = x_189_cast_fp16)[name = string("op_20074_cast_fp16")];
            tensor<int32, [4]> var_20078_begin_0 = const()[name = string("op_20078_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6265344)))];
            tensor<int32, [4]> var_20078_end_0 = const()[name = string("op_20078_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6265472)))];
            tensor<bool, [4]> var_20078_end_mask_0 = const()[name = string("op_20078_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20078_cast_fp16 = slice_by_index(begin = var_20078_begin_0, end = var_20078_end_0, end_mask = var_20078_end_mask_0, x = x_189_cast_fp16)[name = string("op_20078_cast_fp16")];
            tensor<int32, [4]> var_20082_begin_0 = const()[name = string("op_20082_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6265600)))];
            tensor<int32, [4]> var_20082_end_0 = const()[name = string("op_20082_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6265728)))];
            tensor<bool, [4]> var_20082_end_mask_0 = const()[name = string("op_20082_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20082_cast_fp16 = slice_by_index(begin = var_20082_begin_0, end = var_20082_end_0, end_mask = var_20082_end_mask_0, x = x_189_cast_fp16)[name = string("op_20082_cast_fp16")];
            string input_2911_pad_type_0 = const()[name = string("input_2911_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2911_strides_0 = const()[name = string("input_2911_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2911_pad_0 = const()[name = string("input_2911_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6265856)))];
            tensor<int32, [2]> input_2911_dilations_0 = const()[name = string("input_2911_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2911_groups_0 = const()[name = string("input_2911_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1020_to_fp16 = const()[name = string("const_1020_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6265984)))];
            tensor<fp16, [1, 64, 32, 32]> input_2913_cast_fp16 = conv(bias = const_1020_to_fp16, dilations = input_2911_dilations_0, groups = input_2911_groups_0, pad = input_2911_pad_0, pad_type = input_2911_pad_type_0, strides = input_2911_strides_0, weight = const_369_to_fp16, x = var_20074_cast_fp16)[name = string("input_2913_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_2915_cast_fp16 = relu(x = input_2913_cast_fp16)[name = string("input_2915_cast_fp16")];
            string input_2917_pad_type_0 = const()[name = string("input_2917_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2917_pad_0 = const()[name = string("input_2917_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6266176)))];
            int32 input_2917_groups_0 = const()[name = string("input_2917_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_2917_strides_0 = const()[name = string("input_2917_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2917_dilations_0 = const()[name = string("input_2917_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1022_to_fp16 = const()[name = string("const_1022_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6266304)))];
            tensor<fp16, [1, 64, 32, 32]> input_2919_cast_fp16 = conv(bias = const_1022_to_fp16, dilations = input_2917_dilations_0, groups = input_2917_groups_0, pad = input_2917_pad_0, pad_type = input_2917_pad_type_0, strides = input_2917_strides_0, weight = const_371_to_fp16, x = input_2915_cast_fp16)[name = string("input_2919_cast_fp16")];
            string input_2921_pad_type_0 = const()[name = string("input_2921_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2921_strides_0 = const()[name = string("input_2921_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2921_pad_0 = const()[name = string("input_2921_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6266496)))];
            tensor<int32, [2]> input_2921_dilations_0 = const()[name = string("input_2921_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2921_groups_0 = const()[name = string("input_2921_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1024_to_fp16 = const()[name = string("const_1024_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6266624)))];
            tensor<fp16, [1, 64, 32, 32]> input_2923_cast_fp16 = conv(bias = const_1024_to_fp16, dilations = input_2921_dilations_0, groups = input_2921_groups_0, pad = input_2921_pad_0, pad_type = input_2921_pad_type_0, strides = input_2921_strides_0, weight = const_373_to_fp16, x = input_2919_cast_fp16)[name = string("input_2923_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_87_cast_fp16 = relu(x = input_2923_cast_fp16)[name = string("out1_87_cast_fp16")];
            string input_2927_pad_type_0 = const()[name = string("input_2927_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2927_strides_0 = const()[name = string("input_2927_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2927_pad_0 = const()[name = string("input_2927_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6266816)))];
            tensor<int32, [2]> input_2927_dilations_0 = const()[name = string("input_2927_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2927_groups_0 = const()[name = string("input_2927_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1026_to_fp16 = const()[name = string("const_1026_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6266944)))];
            tensor<fp16, [1, 64, 32, 32]> input_2929_cast_fp16 = conv(bias = const_1026_to_fp16, dilations = input_2927_dilations_0, groups = input_2927_groups_0, pad = input_2927_pad_0, pad_type = input_2927_pad_type_0, strides = input_2927_strides_0, weight = const_375_to_fp16, x = var_20078_cast_fp16)[name = string("input_2929_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_2931_cast_fp16 = relu(x = input_2929_cast_fp16)[name = string("input_2931_cast_fp16")];
            string input_2933_pad_type_0 = const()[name = string("input_2933_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2933_pad_0 = const()[name = string("input_2933_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6267136)))];
            int32 input_2933_groups_0 = const()[name = string("input_2933_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_2933_strides_0 = const()[name = string("input_2933_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2933_dilations_0 = const()[name = string("input_2933_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1028_to_fp16 = const()[name = string("const_1028_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6267264)))];
            tensor<fp16, [1, 64, 32, 32]> input_2935_cast_fp16 = conv(bias = const_1028_to_fp16, dilations = input_2933_dilations_0, groups = input_2933_groups_0, pad = input_2933_pad_0, pad_type = input_2933_pad_type_0, strides = input_2933_strides_0, weight = const_377_to_fp16, x = input_2931_cast_fp16)[name = string("input_2935_cast_fp16")];
            string input_2937_pad_type_0 = const()[name = string("input_2937_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2937_strides_0 = const()[name = string("input_2937_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2937_pad_0 = const()[name = string("input_2937_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6267456)))];
            tensor<int32, [2]> input_2937_dilations_0 = const()[name = string("input_2937_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2937_groups_0 = const()[name = string("input_2937_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1030_to_fp16 = const()[name = string("const_1030_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6267584)))];
            tensor<fp16, [1, 64, 32, 32]> input_2939_cast_fp16 = conv(bias = const_1030_to_fp16, dilations = input_2937_dilations_0, groups = input_2937_groups_0, pad = input_2937_pad_0, pad_type = input_2937_pad_type_0, strides = input_2937_strides_0, weight = const_379_to_fp16, x = input_2935_cast_fp16)[name = string("input_2939_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_87_cast_fp16 = relu(x = input_2939_cast_fp16)[name = string("out2_87_cast_fp16")];
            string input_2943_pad_type_0 = const()[name = string("input_2943_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2943_strides_0 = const()[name = string("input_2943_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2943_pad_0 = const()[name = string("input_2943_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6267776)))];
            tensor<int32, [2]> input_2943_dilations_0 = const()[name = string("input_2943_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2943_groups_0 = const()[name = string("input_2943_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1032_to_fp16 = const()[name = string("const_1032_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6267904)))];
            tensor<fp16, [1, 64, 32, 32]> input_2945_cast_fp16 = conv(bias = const_1032_to_fp16, dilations = input_2943_dilations_0, groups = input_2943_groups_0, pad = input_2943_pad_0, pad_type = input_2943_pad_type_0, strides = input_2943_strides_0, weight = const_381_to_fp16, x = var_20082_cast_fp16)[name = string("input_2945_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_2947_cast_fp16 = relu(x = input_2945_cast_fp16)[name = string("input_2947_cast_fp16")];
            string input_2949_pad_type_0 = const()[name = string("input_2949_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2949_pad_0 = const()[name = string("input_2949_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6268096)))];
            int32 input_2949_groups_0 = const()[name = string("input_2949_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_2949_strides_0 = const()[name = string("input_2949_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2949_dilations_0 = const()[name = string("input_2949_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1034_to_fp16 = const()[name = string("const_1034_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6268224)))];
            tensor<fp16, [1, 64, 32, 32]> input_2951_cast_fp16 = conv(bias = const_1034_to_fp16, dilations = input_2949_dilations_0, groups = input_2949_groups_0, pad = input_2949_pad_0, pad_type = input_2949_pad_type_0, strides = input_2949_strides_0, weight = const_383_to_fp16, x = input_2947_cast_fp16)[name = string("input_2951_cast_fp16")];
            string input_2953_pad_type_0 = const()[name = string("input_2953_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2953_strides_0 = const()[name = string("input_2953_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2953_pad_0 = const()[name = string("input_2953_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6268416)))];
            tensor<int32, [2]> input_2953_dilations_0 = const()[name = string("input_2953_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2953_groups_0 = const()[name = string("input_2953_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1036_to_fp16 = const()[name = string("const_1036_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6268544)))];
            tensor<fp16, [1, 64, 32, 32]> input_2955_cast_fp16 = conv(bias = const_1036_to_fp16, dilations = input_2953_dilations_0, groups = input_2953_groups_0, pad = input_2953_pad_0, pad_type = input_2953_pad_type_0, strides = input_2953_strides_0, weight = const_385_to_fp16, x = input_2951_cast_fp16)[name = string("input_2955_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_87_cast_fp16 = relu(x = input_2955_cast_fp16)[name = string("out3_87_cast_fp16")];
            bool input_2957_interleave_0 = const()[name = string("input_2957_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_2957_cast_fp16 = concat(axis = var_16879, interleave = input_2957_interleave_0, values = (var_20070_cast_fp16, out1_87_cast_fp16, out2_87_cast_fp16, out3_87_cast_fp16))[name = string("input_2957_cast_fp16")];
            string input_2959_pad_type_0 = const()[name = string("input_2959_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2959_strides_0 = const()[name = string("input_2959_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2959_pad_0 = const()[name = string("input_2959_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6268736)))];
            tensor<int32, [2]> input_2959_dilations_0 = const()[name = string("input_2959_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2959_groups_0 = const()[name = string("input_2959_groups_0"), val = int32(1)];
            tensor<fp16, [1, 256, 32, 32]> input_2961_cast_fp16 = conv(bias = const_388_to_fp16, dilations = input_2959_dilations_0, groups = input_2959_groups_0, pad = input_2959_pad_0, pad_type = input_2959_pad_type_0, strides = input_2959_strides_0, weight = const_387_to_fp16, x = input_2957_cast_fp16)[name = string("input_2961_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_2963_cast_fp16 = relu(x = input_2961_cast_fp16)[name = string("input_2963_cast_fp16")];
            string input_2965_pad_type_0 = const()[name = string("input_2965_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2965_pad_0 = const()[name = string("input_2965_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6268864)))];
            int32 input_2965_groups_0 = const()[name = string("input_2965_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_2965_strides_0 = const()[name = string("input_2965_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2965_dilations_0 = const()[name = string("input_2965_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 256, 32, 32]> input_2967_cast_fp16 = conv(bias = const_390_to_fp16, dilations = input_2965_dilations_0, groups = input_2965_groups_0, pad = input_2965_pad_0, pad_type = input_2965_pad_type_0, strides = input_2965_strides_0, weight = const_389_to_fp16, x = input_2963_cast_fp16)[name = string("input_2967_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_2969_cast_fp16 = relu(x = input_2967_cast_fp16)[name = string("input_2969_cast_fp16")];
            string input_2971_pad_type_0 = const()[name = string("input_2971_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2971_strides_0 = const()[name = string("input_2971_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2971_pad_0 = const()[name = string("input_2971_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6268992)))];
            tensor<int32, [2]> input_2971_dilations_0 = const()[name = string("input_2971_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2971_groups_0 = const()[name = string("input_2971_groups_0"), val = int32(1)];
            tensor<fp16, [1, 256, 32, 32]> y_115_cast_fp16 = conv(bias = const_392_to_fp16, dilations = input_2971_dilations_0, groups = input_2971_groups_0, pad = input_2971_pad_0, pad_type = input_2971_pad_type_0, strides = input_2971_strides_0, weight = const_391_to_fp16, x = input_2969_cast_fp16)[name = string("y_115_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_191_cast_fp16 = add(x = input_2957_cast_fp16, y = y_115_cast_fp16)[name = string("x_191_cast_fp16")];
            tensor<int32, [4]> var_20182_begin_0 = const()[name = string("op_20182_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6269120)))];
            tensor<int32, [4]> var_20182_end_0 = const()[name = string("op_20182_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6269248)))];
            tensor<bool, [4]> var_20182_end_mask_0 = const()[name = string("op_20182_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20182_cast_fp16 = slice_by_index(begin = var_20182_begin_0, end = var_20182_end_0, end_mask = var_20182_end_mask_0, x = x_191_cast_fp16)[name = string("op_20182_cast_fp16")];
            tensor<int32, [4]> var_20186_begin_0 = const()[name = string("op_20186_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6269376)))];
            tensor<int32, [4]> var_20186_end_0 = const()[name = string("op_20186_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6269504)))];
            tensor<bool, [4]> var_20186_end_mask_0 = const()[name = string("op_20186_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20186_cast_fp16 = slice_by_index(begin = var_20186_begin_0, end = var_20186_end_0, end_mask = var_20186_end_mask_0, x = x_191_cast_fp16)[name = string("op_20186_cast_fp16")];
            tensor<int32, [4]> var_20190_begin_0 = const()[name = string("op_20190_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6269632)))];
            tensor<int32, [4]> var_20190_end_0 = const()[name = string("op_20190_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6269760)))];
            tensor<bool, [4]> var_20190_end_mask_0 = const()[name = string("op_20190_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20190_cast_fp16 = slice_by_index(begin = var_20190_begin_0, end = var_20190_end_0, end_mask = var_20190_end_mask_0, x = x_191_cast_fp16)[name = string("op_20190_cast_fp16")];
            tensor<int32, [4]> var_20194_begin_0 = const()[name = string("op_20194_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6269888)))];
            tensor<int32, [4]> var_20194_end_0 = const()[name = string("op_20194_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6270016)))];
            tensor<bool, [4]> var_20194_end_mask_0 = const()[name = string("op_20194_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20194_cast_fp16 = slice_by_index(begin = var_20194_begin_0, end = var_20194_end_0, end_mask = var_20194_end_mask_0, x = x_191_cast_fp16)[name = string("op_20194_cast_fp16")];
            string input_2975_pad_type_0 = const()[name = string("input_2975_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2975_strides_0 = const()[name = string("input_2975_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2975_pad_0 = const()[name = string("input_2975_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6270144)))];
            tensor<int32, [2]> input_2975_dilations_0 = const()[name = string("input_2975_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2975_groups_0 = const()[name = string("input_2975_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1044_to_fp16 = const()[name = string("const_1044_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6270272)))];
            tensor<fp16, [1, 64, 32, 32]> input_2977_cast_fp16 = conv(bias = const_1044_to_fp16, dilations = input_2975_dilations_0, groups = input_2975_groups_0, pad = input_2975_pad_0, pad_type = input_2975_pad_type_0, strides = input_2975_strides_0, weight = const_393_to_fp16, x = var_20186_cast_fp16)[name = string("input_2977_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_2979_cast_fp16 = relu(x = input_2977_cast_fp16)[name = string("input_2979_cast_fp16")];
            string input_2981_pad_type_0 = const()[name = string("input_2981_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2981_pad_0 = const()[name = string("input_2981_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6270464)))];
            int32 input_2981_groups_0 = const()[name = string("input_2981_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_2981_strides_0 = const()[name = string("input_2981_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2981_dilations_0 = const()[name = string("input_2981_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1046_to_fp16 = const()[name = string("const_1046_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6270592)))];
            tensor<fp16, [1, 64, 32, 32]> input_2983_cast_fp16 = conv(bias = const_1046_to_fp16, dilations = input_2981_dilations_0, groups = input_2981_groups_0, pad = input_2981_pad_0, pad_type = input_2981_pad_type_0, strides = input_2981_strides_0, weight = const_395_to_fp16, x = input_2979_cast_fp16)[name = string("input_2983_cast_fp16")];
            string input_2985_pad_type_0 = const()[name = string("input_2985_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2985_strides_0 = const()[name = string("input_2985_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2985_pad_0 = const()[name = string("input_2985_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6270784)))];
            tensor<int32, [2]> input_2985_dilations_0 = const()[name = string("input_2985_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2985_groups_0 = const()[name = string("input_2985_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1048_to_fp16 = const()[name = string("const_1048_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6270912)))];
            tensor<fp16, [1, 64, 32, 32]> input_2987_cast_fp16 = conv(bias = const_1048_to_fp16, dilations = input_2985_dilations_0, groups = input_2985_groups_0, pad = input_2985_pad_0, pad_type = input_2985_pad_type_0, strides = input_2985_strides_0, weight = const_397_to_fp16, x = input_2983_cast_fp16)[name = string("input_2987_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_89_cast_fp16 = relu(x = input_2987_cast_fp16)[name = string("out1_89_cast_fp16")];
            string input_2991_pad_type_0 = const()[name = string("input_2991_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_2991_strides_0 = const()[name = string("input_2991_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_2991_pad_0 = const()[name = string("input_2991_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6271104)))];
            tensor<int32, [2]> input_2991_dilations_0 = const()[name = string("input_2991_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_2991_groups_0 = const()[name = string("input_2991_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1050_to_fp16 = const()[name = string("const_1050_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6271232)))];
            tensor<fp16, [1, 64, 32, 32]> input_2993_cast_fp16 = conv(bias = const_1050_to_fp16, dilations = input_2991_dilations_0, groups = input_2991_groups_0, pad = input_2991_pad_0, pad_type = input_2991_pad_type_0, strides = input_2991_strides_0, weight = const_399_to_fp16, x = var_20190_cast_fp16)[name = string("input_2993_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_2995_cast_fp16 = relu(x = input_2993_cast_fp16)[name = string("input_2995_cast_fp16")];
            string input_2997_pad_type_0 = const()[name = string("input_2997_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_2997_pad_0 = const()[name = string("input_2997_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6271424)))];
            int32 input_2997_groups_0 = const()[name = string("input_2997_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_2997_strides_0 = const()[name = string("input_2997_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_2997_dilations_0 = const()[name = string("input_2997_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1052_to_fp16 = const()[name = string("const_1052_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6271552)))];
            tensor<fp16, [1, 64, 32, 32]> input_2999_cast_fp16 = conv(bias = const_1052_to_fp16, dilations = input_2997_dilations_0, groups = input_2997_groups_0, pad = input_2997_pad_0, pad_type = input_2997_pad_type_0, strides = input_2997_strides_0, weight = const_401_to_fp16, x = input_2995_cast_fp16)[name = string("input_2999_cast_fp16")];
            string input_3001_pad_type_0 = const()[name = string("input_3001_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3001_strides_0 = const()[name = string("input_3001_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3001_pad_0 = const()[name = string("input_3001_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6271744)))];
            tensor<int32, [2]> input_3001_dilations_0 = const()[name = string("input_3001_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3001_groups_0 = const()[name = string("input_3001_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1054_to_fp16 = const()[name = string("const_1054_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6271872)))];
            tensor<fp16, [1, 64, 32, 32]> input_3003_cast_fp16 = conv(bias = const_1054_to_fp16, dilations = input_3001_dilations_0, groups = input_3001_groups_0, pad = input_3001_pad_0, pad_type = input_3001_pad_type_0, strides = input_3001_strides_0, weight = const_403_to_fp16, x = input_2999_cast_fp16)[name = string("input_3003_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_89_cast_fp16 = relu(x = input_3003_cast_fp16)[name = string("out2_89_cast_fp16")];
            string input_3007_pad_type_0 = const()[name = string("input_3007_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3007_strides_0 = const()[name = string("input_3007_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3007_pad_0 = const()[name = string("input_3007_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6272064)))];
            tensor<int32, [2]> input_3007_dilations_0 = const()[name = string("input_3007_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3007_groups_0 = const()[name = string("input_3007_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1056_to_fp16 = const()[name = string("const_1056_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6272192)))];
            tensor<fp16, [1, 64, 32, 32]> input_3009_cast_fp16 = conv(bias = const_1056_to_fp16, dilations = input_3007_dilations_0, groups = input_3007_groups_0, pad = input_3007_pad_0, pad_type = input_3007_pad_type_0, strides = input_3007_strides_0, weight = const_405_to_fp16, x = var_20194_cast_fp16)[name = string("input_3009_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_3011_cast_fp16 = relu(x = input_3009_cast_fp16)[name = string("input_3011_cast_fp16")];
            string input_3013_pad_type_0 = const()[name = string("input_3013_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3013_pad_0 = const()[name = string("input_3013_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6272384)))];
            int32 input_3013_groups_0 = const()[name = string("input_3013_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_3013_strides_0 = const()[name = string("input_3013_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3013_dilations_0 = const()[name = string("input_3013_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1058_to_fp16 = const()[name = string("const_1058_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6272512)))];
            tensor<fp16, [1, 64, 32, 32]> input_3015_cast_fp16 = conv(bias = const_1058_to_fp16, dilations = input_3013_dilations_0, groups = input_3013_groups_0, pad = input_3013_pad_0, pad_type = input_3013_pad_type_0, strides = input_3013_strides_0, weight = const_407_to_fp16, x = input_3011_cast_fp16)[name = string("input_3015_cast_fp16")];
            string input_3017_pad_type_0 = const()[name = string("input_3017_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3017_strides_0 = const()[name = string("input_3017_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3017_pad_0 = const()[name = string("input_3017_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6272704)))];
            tensor<int32, [2]> input_3017_dilations_0 = const()[name = string("input_3017_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3017_groups_0 = const()[name = string("input_3017_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1060_to_fp16 = const()[name = string("const_1060_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6272832)))];
            tensor<fp16, [1, 64, 32, 32]> input_3019_cast_fp16 = conv(bias = const_1060_to_fp16, dilations = input_3017_dilations_0, groups = input_3017_groups_0, pad = input_3017_pad_0, pad_type = input_3017_pad_type_0, strides = input_3017_strides_0, weight = const_409_to_fp16, x = input_3015_cast_fp16)[name = string("input_3019_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_89_cast_fp16 = relu(x = input_3019_cast_fp16)[name = string("out3_89_cast_fp16")];
            bool input_3021_interleave_0 = const()[name = string("input_3021_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_3021_cast_fp16 = concat(axis = var_16879, interleave = input_3021_interleave_0, values = (var_20182_cast_fp16, out1_89_cast_fp16, out2_89_cast_fp16, out3_89_cast_fp16))[name = string("input_3021_cast_fp16")];
            string input_3023_pad_type_0 = const()[name = string("input_3023_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3023_strides_0 = const()[name = string("input_3023_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3023_pad_0 = const()[name = string("input_3023_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6273024)))];
            tensor<int32, [2]> input_3023_dilations_0 = const()[name = string("input_3023_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3023_groups_0 = const()[name = string("input_3023_groups_0"), val = int32(1)];
            tensor<fp16, [1, 256, 32, 32]> input_3025_cast_fp16 = conv(bias = const_412_to_fp16, dilations = input_3023_dilations_0, groups = input_3023_groups_0, pad = input_3023_pad_0, pad_type = input_3023_pad_type_0, strides = input_3023_strides_0, weight = const_411_to_fp16, x = input_3021_cast_fp16)[name = string("input_3025_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_3027_cast_fp16 = relu(x = input_3025_cast_fp16)[name = string("input_3027_cast_fp16")];
            string input_3029_pad_type_0 = const()[name = string("input_3029_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3029_pad_0 = const()[name = string("input_3029_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6273152)))];
            int32 input_3029_groups_0 = const()[name = string("input_3029_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_3029_strides_0 = const()[name = string("input_3029_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3029_dilations_0 = const()[name = string("input_3029_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 256, 32, 32]> input_3031_cast_fp16 = conv(bias = const_414_to_fp16, dilations = input_3029_dilations_0, groups = input_3029_groups_0, pad = input_3029_pad_0, pad_type = input_3029_pad_type_0, strides = input_3029_strides_0, weight = const_413_to_fp16, x = input_3027_cast_fp16)[name = string("input_3031_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> input_3033_cast_fp16 = relu(x = input_3031_cast_fp16)[name = string("input_3033_cast_fp16")];
            string input_3035_pad_type_0 = const()[name = string("input_3035_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3035_strides_0 = const()[name = string("input_3035_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3035_pad_0 = const()[name = string("input_3035_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6273280)))];
            tensor<int32, [2]> input_3035_dilations_0 = const()[name = string("input_3035_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3035_groups_0 = const()[name = string("input_3035_groups_0"), val = int32(1)];
            tensor<fp16, [1, 256, 32, 32]> y_117_cast_fp16 = conv(bias = const_416_to_fp16, dilations = input_3035_dilations_0, groups = input_3035_groups_0, pad = input_3035_pad_0, pad_type = input_3035_pad_type_0, strides = input_3035_strides_0, weight = const_415_to_fp16, x = input_3033_cast_fp16)[name = string("y_117_cast_fp16")];
            tensor<fp16, [1, 256, 32, 32]> x_193_cast_fp16 = add(x = input_3021_cast_fp16, y = y_117_cast_fp16)[name = string("x_193_cast_fp16")];
            tensor<int32, [4]> var_20294_begin_0 = const()[name = string("op_20294_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6273408)))];
            tensor<int32, [4]> var_20294_end_0 = const()[name = string("op_20294_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6273536)))];
            tensor<bool, [4]> var_20294_end_mask_0 = const()[name = string("op_20294_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20294_cast_fp16 = slice_by_index(begin = var_20294_begin_0, end = var_20294_end_0, end_mask = var_20294_end_mask_0, x = x_193_cast_fp16)[name = string("op_20294_cast_fp16")];
            tensor<int32, [4]> var_20298_begin_0 = const()[name = string("op_20298_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6273664)))];
            tensor<int32, [4]> var_20298_end_0 = const()[name = string("op_20298_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6273792)))];
            tensor<bool, [4]> var_20298_end_mask_0 = const()[name = string("op_20298_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20298_cast_fp16 = slice_by_index(begin = var_20298_begin_0, end = var_20298_end_0, end_mask = var_20298_end_mask_0, x = x_193_cast_fp16)[name = string("op_20298_cast_fp16")];
            tensor<int32, [4]> var_20302_begin_0 = const()[name = string("op_20302_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6273920)))];
            tensor<int32, [4]> var_20302_end_0 = const()[name = string("op_20302_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6274048)))];
            tensor<bool, [4]> var_20302_end_mask_0 = const()[name = string("op_20302_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20302_cast_fp16 = slice_by_index(begin = var_20302_begin_0, end = var_20302_end_0, end_mask = var_20302_end_mask_0, x = x_193_cast_fp16)[name = string("op_20302_cast_fp16")];
            tensor<int32, [4]> var_20306_begin_0 = const()[name = string("op_20306_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6274176)))];
            tensor<int32, [4]> var_20306_end_0 = const()[name = string("op_20306_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6274304)))];
            tensor<bool, [4]> var_20306_end_mask_0 = const()[name = string("op_20306_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20306_cast_fp16 = slice_by_index(begin = var_20306_begin_0, end = var_20306_end_0, end_mask = var_20306_end_mask_0, x = x_193_cast_fp16)[name = string("op_20306_cast_fp16")];
            string input_3039_pad_type_0 = const()[name = string("input_3039_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3039_strides_0 = const()[name = string("input_3039_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3039_pad_0 = const()[name = string("input_3039_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6274432)))];
            tensor<int32, [2]> input_3039_dilations_0 = const()[name = string("input_3039_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3039_groups_0 = const()[name = string("input_3039_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1068_to_fp16 = const()[name = string("const_1068_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6274560)))];
            tensor<fp16, [1, 64, 32, 32]> input_3041_cast_fp16 = conv(bias = const_1068_to_fp16, dilations = input_3039_dilations_0, groups = input_3039_groups_0, pad = input_3039_pad_0, pad_type = input_3039_pad_type_0, strides = input_3039_strides_0, weight = const_417_to_fp16, x = var_20298_cast_fp16)[name = string("input_3041_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_3043_cast_fp16 = relu(x = input_3041_cast_fp16)[name = string("input_3043_cast_fp16")];
            string input_3045_pad_type_0 = const()[name = string("input_3045_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3045_pad_0 = const()[name = string("input_3045_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6274752)))];
            int32 input_3045_groups_0 = const()[name = string("input_3045_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_3045_strides_0 = const()[name = string("input_3045_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3045_dilations_0 = const()[name = string("input_3045_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1070_to_fp16 = const()[name = string("const_1070_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6274880)))];
            tensor<fp16, [1, 64, 32, 32]> input_3047_cast_fp16 = conv(bias = const_1070_to_fp16, dilations = input_3045_dilations_0, groups = input_3045_groups_0, pad = input_3045_pad_0, pad_type = input_3045_pad_type_0, strides = input_3045_strides_0, weight = const_419_to_fp16, x = input_3043_cast_fp16)[name = string("input_3047_cast_fp16")];
            string input_3049_pad_type_0 = const()[name = string("input_3049_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3049_strides_0 = const()[name = string("input_3049_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3049_pad_0 = const()[name = string("input_3049_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6275072)))];
            tensor<int32, [2]> input_3049_dilations_0 = const()[name = string("input_3049_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3049_groups_0 = const()[name = string("input_3049_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1072_to_fp16 = const()[name = string("const_1072_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6275200)))];
            tensor<fp16, [1, 64, 32, 32]> input_3051_cast_fp16 = conv(bias = const_1072_to_fp16, dilations = input_3049_dilations_0, groups = input_3049_groups_0, pad = input_3049_pad_0, pad_type = input_3049_pad_type_0, strides = input_3049_strides_0, weight = const_421_to_fp16, x = input_3047_cast_fp16)[name = string("input_3051_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out1_91_cast_fp16 = relu(x = input_3051_cast_fp16)[name = string("out1_91_cast_fp16")];
            string input_3055_pad_type_0 = const()[name = string("input_3055_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3055_strides_0 = const()[name = string("input_3055_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3055_pad_0 = const()[name = string("input_3055_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6275392)))];
            tensor<int32, [2]> input_3055_dilations_0 = const()[name = string("input_3055_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3055_groups_0 = const()[name = string("input_3055_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1074_to_fp16 = const()[name = string("const_1074_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6275520)))];
            tensor<fp16, [1, 64, 32, 32]> input_3057_cast_fp16 = conv(bias = const_1074_to_fp16, dilations = input_3055_dilations_0, groups = input_3055_groups_0, pad = input_3055_pad_0, pad_type = input_3055_pad_type_0, strides = input_3055_strides_0, weight = const_423_to_fp16, x = var_20302_cast_fp16)[name = string("input_3057_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_3059_cast_fp16 = relu(x = input_3057_cast_fp16)[name = string("input_3059_cast_fp16")];
            string input_3061_pad_type_0 = const()[name = string("input_3061_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3061_pad_0 = const()[name = string("input_3061_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6275712)))];
            int32 input_3061_groups_0 = const()[name = string("input_3061_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_3061_strides_0 = const()[name = string("input_3061_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3061_dilations_0 = const()[name = string("input_3061_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1076_to_fp16 = const()[name = string("const_1076_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6275840)))];
            tensor<fp16, [1, 64, 32, 32]> input_3063_cast_fp16 = conv(bias = const_1076_to_fp16, dilations = input_3061_dilations_0, groups = input_3061_groups_0, pad = input_3061_pad_0, pad_type = input_3061_pad_type_0, strides = input_3061_strides_0, weight = const_425_to_fp16, x = input_3059_cast_fp16)[name = string("input_3063_cast_fp16")];
            string input_3065_pad_type_0 = const()[name = string("input_3065_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3065_strides_0 = const()[name = string("input_3065_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3065_pad_0 = const()[name = string("input_3065_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6276032)))];
            tensor<int32, [2]> input_3065_dilations_0 = const()[name = string("input_3065_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3065_groups_0 = const()[name = string("input_3065_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1078_to_fp16 = const()[name = string("const_1078_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6276160)))];
            tensor<fp16, [1, 64, 32, 32]> input_3067_cast_fp16 = conv(bias = const_1078_to_fp16, dilations = input_3065_dilations_0, groups = input_3065_groups_0, pad = input_3065_pad_0, pad_type = input_3065_pad_type_0, strides = input_3065_strides_0, weight = const_427_to_fp16, x = input_3063_cast_fp16)[name = string("input_3067_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out2_91_cast_fp16 = relu(x = input_3067_cast_fp16)[name = string("out2_91_cast_fp16")];
            string input_3071_pad_type_0 = const()[name = string("input_3071_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3071_strides_0 = const()[name = string("input_3071_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3071_pad_0 = const()[name = string("input_3071_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6276352)))];
            tensor<int32, [2]> input_3071_dilations_0 = const()[name = string("input_3071_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3071_groups_0 = const()[name = string("input_3071_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1080_to_fp16 = const()[name = string("const_1080_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6276480)))];
            tensor<fp16, [1, 64, 32, 32]> input_3073_cast_fp16 = conv(bias = const_1080_to_fp16, dilations = input_3071_dilations_0, groups = input_3071_groups_0, pad = input_3071_pad_0, pad_type = input_3071_pad_type_0, strides = input_3071_strides_0, weight = const_429_to_fp16, x = var_20306_cast_fp16)[name = string("input_3073_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> input_3075_cast_fp16 = relu(x = input_3073_cast_fp16)[name = string("input_3075_cast_fp16")];
            string input_3077_pad_type_0 = const()[name = string("input_3077_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3077_pad_0 = const()[name = string("input_3077_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6276672)))];
            int32 input_3077_groups_0 = const()[name = string("input_3077_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_3077_strides_0 = const()[name = string("input_3077_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3077_dilations_0 = const()[name = string("input_3077_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> const_1082_to_fp16 = const()[name = string("const_1082_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6276800)))];
            tensor<fp16, [1, 64, 32, 32]> input_3079_cast_fp16 = conv(bias = const_1082_to_fp16, dilations = input_3077_dilations_0, groups = input_3077_groups_0, pad = input_3077_pad_0, pad_type = input_3077_pad_type_0, strides = input_3077_strides_0, weight = const_431_to_fp16, x = input_3075_cast_fp16)[name = string("input_3079_cast_fp16")];
            string input_3081_pad_type_0 = const()[name = string("input_3081_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3081_strides_0 = const()[name = string("input_3081_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3081_pad_0 = const()[name = string("input_3081_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6276992)))];
            tensor<int32, [2]> input_3081_dilations_0 = const()[name = string("input_3081_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3081_groups_0 = const()[name = string("input_3081_groups_0"), val = int32(1)];
            tensor<fp16, [64]> const_1084_to_fp16 = const()[name = string("const_1084_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6277120)))];
            tensor<fp16, [1, 64, 32, 32]> input_3083_cast_fp16 = conv(bias = const_1084_to_fp16, dilations = input_3081_dilations_0, groups = input_3081_groups_0, pad = input_3081_pad_0, pad_type = input_3081_pad_type_0, strides = input_3081_strides_0, weight = const_433_to_fp16, x = input_3079_cast_fp16)[name = string("input_3083_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> out3_91_cast_fp16 = relu(x = input_3083_cast_fp16)[name = string("out3_91_cast_fp16")];
            bool input_3085_interleave_0 = const()[name = string("input_3085_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 32, 32]> input_3085_cast_fp16 = concat(axis = var_16879, interleave = input_3085_interleave_0, values = (var_20294_cast_fp16, out1_91_cast_fp16, out2_91_cast_fp16, out3_91_cast_fp16))[name = string("input_3085_cast_fp16")];
            string input_3087_pad_type_0 = const()[name = string("input_3087_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3087_strides_0 = const()[name = string("input_3087_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3087_pad_0 = const()[name = string("input_3087_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6277312)))];
            tensor<int32, [2]> input_3087_dilations_0 = const()[name = string("input_3087_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3087_groups_0 = const()[name = string("input_3087_groups_0"), val = int32(1)];
            tensor<fp16, [1, 512, 32, 32]> input_3089_cast_fp16 = conv(bias = const_436_to_fp16, dilations = input_3087_dilations_0, groups = input_3087_groups_0, pad = input_3087_pad_0, pad_type = input_3087_pad_type_0, strides = input_3087_strides_0, weight = const_435_to_fp16, x = input_3085_cast_fp16)[name = string("input_3089_cast_fp16")];
            tensor<fp16, [1, 512, 32, 32]> input_3091_cast_fp16 = relu(x = input_3089_cast_fp16)[name = string("input_3091_cast_fp16")];
            string input_3093_pad_type_0 = const()[name = string("input_3093_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3093_pad_0 = const()[name = string("input_3093_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6277440)))];
            tensor<int32, [2]> input_3093_strides_0 = const()[name = string("input_3093_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_3093_groups_0 = const()[name = string("input_3093_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_3093_dilations_0 = const()[name = string("input_3093_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 512, 16, 16]> input_3095_cast_fp16 = conv(bias = const_438_to_fp16, dilations = input_3093_dilations_0, groups = input_3093_groups_0, pad = input_3093_pad_0, pad_type = input_3093_pad_type_0, strides = input_3093_strides_0, weight = const_437_to_fp16, x = input_3091_cast_fp16)[name = string("input_3095_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_3097_cast_fp16 = relu(x = input_3095_cast_fp16)[name = string("input_3097_cast_fp16")];
            string input_3099_pad_type_0 = const()[name = string("input_3099_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3099_strides_0 = const()[name = string("input_3099_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3099_pad_0 = const()[name = string("input_3099_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6277568)))];
            tensor<int32, [2]> input_3099_dilations_0 = const()[name = string("input_3099_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3099_groups_0 = const()[name = string("input_3099_groups_0"), val = int32(1)];
            tensor<fp16, [1, 512, 16, 16]> x_195_cast_fp16 = conv(bias = const_440_to_fp16, dilations = input_3099_dilations_0, groups = input_3099_groups_0, pad = input_3099_pad_0, pad_type = input_3099_pad_type_0, strides = input_3099_strides_0, weight = const_439_to_fp16, x = input_3097_cast_fp16)[name = string("x_195_cast_fp16")];
            tensor<int32, [4]> var_20405_begin_0 = const()[name = string("op_20405_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6277696)))];
            tensor<int32, [4]> var_20405_end_0 = const()[name = string("op_20405_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6277824)))];
            tensor<bool, [4]> var_20405_end_mask_0 = const()[name = string("op_20405_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_20405_cast_fp16 = slice_by_index(begin = var_20405_begin_0, end = var_20405_end_0, end_mask = var_20405_end_mask_0, x = x_195_cast_fp16)[name = string("op_20405_cast_fp16")];
            tensor<int32, [4]> var_20409_begin_0 = const()[name = string("op_20409_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6277952)))];
            tensor<int32, [4]> var_20409_end_0 = const()[name = string("op_20409_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6278080)))];
            tensor<bool, [4]> var_20409_end_mask_0 = const()[name = string("op_20409_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_20409_cast_fp16 = slice_by_index(begin = var_20409_begin_0, end = var_20409_end_0, end_mask = var_20409_end_mask_0, x = x_195_cast_fp16)[name = string("op_20409_cast_fp16")];
            tensor<int32, [4]> var_20413_begin_0 = const()[name = string("op_20413_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6278208)))];
            tensor<int32, [4]> var_20413_end_0 = const()[name = string("op_20413_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6278336)))];
            tensor<bool, [4]> var_20413_end_mask_0 = const()[name = string("op_20413_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_20413_cast_fp16 = slice_by_index(begin = var_20413_begin_0, end = var_20413_end_0, end_mask = var_20413_end_mask_0, x = x_195_cast_fp16)[name = string("op_20413_cast_fp16")];
            tensor<int32, [4]> var_20417_begin_0 = const()[name = string("op_20417_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6278464)))];
            tensor<int32, [4]> var_20417_end_0 = const()[name = string("op_20417_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6278592)))];
            tensor<bool, [4]> var_20417_end_mask_0 = const()[name = string("op_20417_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_20417_cast_fp16 = slice_by_index(begin = var_20417_begin_0, end = var_20417_end_0, end_mask = var_20417_end_mask_0, x = x_195_cast_fp16)[name = string("op_20417_cast_fp16")];
            string input_3103_pad_type_0 = const()[name = string("input_3103_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3103_strides_0 = const()[name = string("input_3103_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3103_pad_0 = const()[name = string("input_3103_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6278720)))];
            tensor<int32, [2]> input_3103_dilations_0 = const()[name = string("input_3103_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3103_groups_0 = const()[name = string("input_3103_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3105_cast_fp16 = conv(bias = const_442_to_fp16, dilations = input_3103_dilations_0, groups = input_3103_groups_0, pad = input_3103_pad_0, pad_type = input_3103_pad_type_0, strides = input_3103_strides_0, weight = const_441_to_fp16, x = var_20409_cast_fp16)[name = string("input_3105_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_3107_cast_fp16 = relu(x = input_3105_cast_fp16)[name = string("input_3107_cast_fp16")];
            string input_3109_pad_type_0 = const()[name = string("input_3109_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3109_pad_0 = const()[name = string("input_3109_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6278848)))];
            int32 input_3109_groups_0 = const()[name = string("input_3109_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_3109_strides_0 = const()[name = string("input_3109_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3109_dilations_0 = const()[name = string("input_3109_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 128, 16, 16]> input_3111_cast_fp16 = conv(bias = const_444_to_fp16, dilations = input_3109_dilations_0, groups = input_3109_groups_0, pad = input_3109_pad_0, pad_type = input_3109_pad_type_0, strides = input_3109_strides_0, weight = const_443_to_fp16, x = input_3107_cast_fp16)[name = string("input_3111_cast_fp16")];
            string input_3113_pad_type_0 = const()[name = string("input_3113_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3113_strides_0 = const()[name = string("input_3113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3113_pad_0 = const()[name = string("input_3113_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6278976)))];
            tensor<int32, [2]> input_3113_dilations_0 = const()[name = string("input_3113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3113_groups_0 = const()[name = string("input_3113_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3115_cast_fp16 = conv(bias = const_446_to_fp16, dilations = input_3113_dilations_0, groups = input_3113_groups_0, pad = input_3113_pad_0, pad_type = input_3113_pad_type_0, strides = input_3113_strides_0, weight = const_445_to_fp16, x = input_3111_cast_fp16)[name = string("input_3115_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_93_cast_fp16 = relu(x = input_3115_cast_fp16)[name = string("out1_93_cast_fp16")];
            string input_3119_pad_type_0 = const()[name = string("input_3119_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3119_strides_0 = const()[name = string("input_3119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3119_pad_0 = const()[name = string("input_3119_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6279104)))];
            tensor<int32, [2]> input_3119_dilations_0 = const()[name = string("input_3119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3119_groups_0 = const()[name = string("input_3119_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3121_cast_fp16 = conv(bias = const_448_to_fp16, dilations = input_3119_dilations_0, groups = input_3119_groups_0, pad = input_3119_pad_0, pad_type = input_3119_pad_type_0, strides = input_3119_strides_0, weight = const_447_to_fp16, x = var_20413_cast_fp16)[name = string("input_3121_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_3123_cast_fp16 = relu(x = input_3121_cast_fp16)[name = string("input_3123_cast_fp16")];
            string input_3125_pad_type_0 = const()[name = string("input_3125_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3125_pad_0 = const()[name = string("input_3125_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6279232)))];
            int32 input_3125_groups_0 = const()[name = string("input_3125_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_3125_strides_0 = const()[name = string("input_3125_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3125_dilations_0 = const()[name = string("input_3125_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 128, 16, 16]> input_3127_cast_fp16 = conv(bias = const_450_to_fp16, dilations = input_3125_dilations_0, groups = input_3125_groups_0, pad = input_3125_pad_0, pad_type = input_3125_pad_type_0, strides = input_3125_strides_0, weight = const_449_to_fp16, x = input_3123_cast_fp16)[name = string("input_3127_cast_fp16")];
            string input_3129_pad_type_0 = const()[name = string("input_3129_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3129_strides_0 = const()[name = string("input_3129_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3129_pad_0 = const()[name = string("input_3129_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6279360)))];
            tensor<int32, [2]> input_3129_dilations_0 = const()[name = string("input_3129_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3129_groups_0 = const()[name = string("input_3129_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3131_cast_fp16 = conv(bias = const_452_to_fp16, dilations = input_3129_dilations_0, groups = input_3129_groups_0, pad = input_3129_pad_0, pad_type = input_3129_pad_type_0, strides = input_3129_strides_0, weight = const_451_to_fp16, x = input_3127_cast_fp16)[name = string("input_3131_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_93_cast_fp16 = relu(x = input_3131_cast_fp16)[name = string("out2_93_cast_fp16")];
            string input_3135_pad_type_0 = const()[name = string("input_3135_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3135_strides_0 = const()[name = string("input_3135_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3135_pad_0 = const()[name = string("input_3135_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6279488)))];
            tensor<int32, [2]> input_3135_dilations_0 = const()[name = string("input_3135_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3135_groups_0 = const()[name = string("input_3135_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3137_cast_fp16 = conv(bias = const_454_to_fp16, dilations = input_3135_dilations_0, groups = input_3135_groups_0, pad = input_3135_pad_0, pad_type = input_3135_pad_type_0, strides = input_3135_strides_0, weight = const_453_to_fp16, x = var_20417_cast_fp16)[name = string("input_3137_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_3139_cast_fp16 = relu(x = input_3137_cast_fp16)[name = string("input_3139_cast_fp16")];
            string input_3141_pad_type_0 = const()[name = string("input_3141_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3141_pad_0 = const()[name = string("input_3141_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6279616)))];
            int32 input_3141_groups_0 = const()[name = string("input_3141_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_3141_strides_0 = const()[name = string("input_3141_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3141_dilations_0 = const()[name = string("input_3141_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 128, 16, 16]> input_3143_cast_fp16 = conv(bias = const_456_to_fp16, dilations = input_3141_dilations_0, groups = input_3141_groups_0, pad = input_3141_pad_0, pad_type = input_3141_pad_type_0, strides = input_3141_strides_0, weight = const_455_to_fp16, x = input_3139_cast_fp16)[name = string("input_3143_cast_fp16")];
            string input_3145_pad_type_0 = const()[name = string("input_3145_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3145_strides_0 = const()[name = string("input_3145_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3145_pad_0 = const()[name = string("input_3145_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6279744)))];
            tensor<int32, [2]> input_3145_dilations_0 = const()[name = string("input_3145_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3145_groups_0 = const()[name = string("input_3145_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3147_cast_fp16 = conv(bias = const_458_to_fp16, dilations = input_3145_dilations_0, groups = input_3145_groups_0, pad = input_3145_pad_0, pad_type = input_3145_pad_type_0, strides = input_3145_strides_0, weight = const_457_to_fp16, x = input_3143_cast_fp16)[name = string("input_3147_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_93_cast_fp16 = relu(x = input_3147_cast_fp16)[name = string("out3_93_cast_fp16")];
            bool input_3149_interleave_0 = const()[name = string("input_3149_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_3149_cast_fp16 = concat(axis = var_16879, interleave = input_3149_interleave_0, values = (var_20405_cast_fp16, out1_93_cast_fp16, out2_93_cast_fp16, out3_93_cast_fp16))[name = string("input_3149_cast_fp16")];
            string input_3151_pad_type_0 = const()[name = string("input_3151_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3151_strides_0 = const()[name = string("input_3151_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3151_pad_0 = const()[name = string("input_3151_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6279872)))];
            tensor<int32, [2]> input_3151_dilations_0 = const()[name = string("input_3151_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3151_groups_0 = const()[name = string("input_3151_groups_0"), val = int32(1)];
            tensor<fp16, [1, 512, 16, 16]> input_3153_cast_fp16 = conv(bias = const_460_to_fp16, dilations = input_3151_dilations_0, groups = input_3151_groups_0, pad = input_3151_pad_0, pad_type = input_3151_pad_type_0, strides = input_3151_strides_0, weight = const_459_to_fp16, x = input_3149_cast_fp16)[name = string("input_3153_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_3155_cast_fp16 = relu(x = input_3153_cast_fp16)[name = string("input_3155_cast_fp16")];
            string input_3157_pad_type_0 = const()[name = string("input_3157_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3157_pad_0 = const()[name = string("input_3157_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6280000)))];
            int32 input_3157_groups_0 = const()[name = string("input_3157_groups_0"), val = int32(512)];
            tensor<int32, [2]> input_3157_strides_0 = const()[name = string("input_3157_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3157_dilations_0 = const()[name = string("input_3157_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 512, 16, 16]> input_3159_cast_fp16 = conv(bias = const_462_to_fp16, dilations = input_3157_dilations_0, groups = input_3157_groups_0, pad = input_3157_pad_0, pad_type = input_3157_pad_type_0, strides = input_3157_strides_0, weight = const_461_to_fp16, x = input_3155_cast_fp16)[name = string("input_3159_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> input_3161_cast_fp16 = relu(x = input_3159_cast_fp16)[name = string("input_3161_cast_fp16")];
            string input_3163_pad_type_0 = const()[name = string("input_3163_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3163_strides_0 = const()[name = string("input_3163_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3163_pad_0 = const()[name = string("input_3163_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6280128)))];
            tensor<int32, [2]> input_3163_dilations_0 = const()[name = string("input_3163_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3163_groups_0 = const()[name = string("input_3163_groups_0"), val = int32(1)];
            tensor<fp16, [1, 512, 16, 16]> y_119_cast_fp16 = conv(bias = const_464_to_fp16, dilations = input_3163_dilations_0, groups = input_3163_groups_0, pad = input_3163_pad_0, pad_type = input_3163_pad_type_0, strides = input_3163_strides_0, weight = const_463_to_fp16, x = input_3161_cast_fp16)[name = string("y_119_cast_fp16")];
            tensor<fp16, [1, 512, 16, 16]> x_197_cast_fp16 = add(x = input_3149_cast_fp16, y = y_119_cast_fp16)[name = string("x_197_cast_fp16")];
            tensor<int32, [4]> var_20517_begin_0 = const()[name = string("op_20517_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6280256)))];
            tensor<int32, [4]> var_20517_end_0 = const()[name = string("op_20517_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6280384)))];
            tensor<bool, [4]> var_20517_end_mask_0 = const()[name = string("op_20517_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_20517_cast_fp16 = slice_by_index(begin = var_20517_begin_0, end = var_20517_end_0, end_mask = var_20517_end_mask_0, x = x_197_cast_fp16)[name = string("op_20517_cast_fp16")];
            tensor<int32, [4]> var_20521_begin_0 = const()[name = string("op_20521_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6280512)))];
            tensor<int32, [4]> var_20521_end_0 = const()[name = string("op_20521_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6280640)))];
            tensor<bool, [4]> var_20521_end_mask_0 = const()[name = string("op_20521_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_20521_cast_fp16 = slice_by_index(begin = var_20521_begin_0, end = var_20521_end_0, end_mask = var_20521_end_mask_0, x = x_197_cast_fp16)[name = string("op_20521_cast_fp16")];
            tensor<int32, [4]> var_20525_begin_0 = const()[name = string("op_20525_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6280768)))];
            tensor<int32, [4]> var_20525_end_0 = const()[name = string("op_20525_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6280896)))];
            tensor<bool, [4]> var_20525_end_mask_0 = const()[name = string("op_20525_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_20525_cast_fp16 = slice_by_index(begin = var_20525_begin_0, end = var_20525_end_0, end_mask = var_20525_end_mask_0, x = x_197_cast_fp16)[name = string("op_20525_cast_fp16")];
            tensor<int32, [4]> var_20529_begin_0 = const()[name = string("op_20529_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6281024)))];
            tensor<int32, [4]> var_20529_end_0 = const()[name = string("op_20529_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6281152)))];
            tensor<bool, [4]> var_20529_end_mask_0 = const()[name = string("op_20529_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 128, 16, 16]> var_20529_cast_fp16 = slice_by_index(begin = var_20529_begin_0, end = var_20529_end_0, end_mask = var_20529_end_mask_0, x = x_197_cast_fp16)[name = string("op_20529_cast_fp16")];
            string input_3167_pad_type_0 = const()[name = string("input_3167_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3167_strides_0 = const()[name = string("input_3167_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3167_pad_0 = const()[name = string("input_3167_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6281280)))];
            tensor<int32, [2]> input_3167_dilations_0 = const()[name = string("input_3167_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3167_groups_0 = const()[name = string("input_3167_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3169_cast_fp16 = conv(bias = const_466_to_fp16, dilations = input_3167_dilations_0, groups = input_3167_groups_0, pad = input_3167_pad_0, pad_type = input_3167_pad_type_0, strides = input_3167_strides_0, weight = const_465_to_fp16, x = var_20521_cast_fp16)[name = string("input_3169_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_3171_cast_fp16 = relu(x = input_3169_cast_fp16)[name = string("input_3171_cast_fp16")];
            string input_3173_pad_type_0 = const()[name = string("input_3173_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3173_pad_0 = const()[name = string("input_3173_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6281408)))];
            int32 input_3173_groups_0 = const()[name = string("input_3173_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_3173_strides_0 = const()[name = string("input_3173_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3173_dilations_0 = const()[name = string("input_3173_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 128, 16, 16]> input_3175_cast_fp16 = conv(bias = const_468_to_fp16, dilations = input_3173_dilations_0, groups = input_3173_groups_0, pad = input_3173_pad_0, pad_type = input_3173_pad_type_0, strides = input_3173_strides_0, weight = const_467_to_fp16, x = input_3171_cast_fp16)[name = string("input_3175_cast_fp16")];
            string input_3177_pad_type_0 = const()[name = string("input_3177_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3177_strides_0 = const()[name = string("input_3177_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3177_pad_0 = const()[name = string("input_3177_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6281536)))];
            tensor<int32, [2]> input_3177_dilations_0 = const()[name = string("input_3177_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3177_groups_0 = const()[name = string("input_3177_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3179_cast_fp16 = conv(bias = const_470_to_fp16, dilations = input_3177_dilations_0, groups = input_3177_groups_0, pad = input_3177_pad_0, pad_type = input_3177_pad_type_0, strides = input_3177_strides_0, weight = const_469_to_fp16, x = input_3175_cast_fp16)[name = string("input_3179_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out1_95_cast_fp16 = relu(x = input_3179_cast_fp16)[name = string("out1_95_cast_fp16")];
            string input_3183_pad_type_0 = const()[name = string("input_3183_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3183_strides_0 = const()[name = string("input_3183_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3183_pad_0 = const()[name = string("input_3183_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6281664)))];
            tensor<int32, [2]> input_3183_dilations_0 = const()[name = string("input_3183_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3183_groups_0 = const()[name = string("input_3183_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3185_cast_fp16 = conv(bias = const_472_to_fp16, dilations = input_3183_dilations_0, groups = input_3183_groups_0, pad = input_3183_pad_0, pad_type = input_3183_pad_type_0, strides = input_3183_strides_0, weight = const_471_to_fp16, x = var_20525_cast_fp16)[name = string("input_3185_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_3187_cast_fp16 = relu(x = input_3185_cast_fp16)[name = string("input_3187_cast_fp16")];
            string input_3189_pad_type_0 = const()[name = string("input_3189_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3189_pad_0 = const()[name = string("input_3189_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6281792)))];
            int32 input_3189_groups_0 = const()[name = string("input_3189_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_3189_strides_0 = const()[name = string("input_3189_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3189_dilations_0 = const()[name = string("input_3189_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 128, 16, 16]> input_3191_cast_fp16 = conv(bias = const_474_to_fp16, dilations = input_3189_dilations_0, groups = input_3189_groups_0, pad = input_3189_pad_0, pad_type = input_3189_pad_type_0, strides = input_3189_strides_0, weight = const_473_to_fp16, x = input_3187_cast_fp16)[name = string("input_3191_cast_fp16")];
            string input_3193_pad_type_0 = const()[name = string("input_3193_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3193_strides_0 = const()[name = string("input_3193_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3193_pad_0 = const()[name = string("input_3193_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6281920)))];
            tensor<int32, [2]> input_3193_dilations_0 = const()[name = string("input_3193_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3193_groups_0 = const()[name = string("input_3193_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3195_cast_fp16 = conv(bias = const_476_to_fp16, dilations = input_3193_dilations_0, groups = input_3193_groups_0, pad = input_3193_pad_0, pad_type = input_3193_pad_type_0, strides = input_3193_strides_0, weight = const_475_to_fp16, x = input_3191_cast_fp16)[name = string("input_3195_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out2_95_cast_fp16 = relu(x = input_3195_cast_fp16)[name = string("out2_95_cast_fp16")];
            string input_3199_pad_type_0 = const()[name = string("input_3199_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3199_strides_0 = const()[name = string("input_3199_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3199_pad_0 = const()[name = string("input_3199_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6282048)))];
            tensor<int32, [2]> input_3199_dilations_0 = const()[name = string("input_3199_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3199_groups_0 = const()[name = string("input_3199_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3201_cast_fp16 = conv(bias = const_478_to_fp16, dilations = input_3199_dilations_0, groups = input_3199_groups_0, pad = input_3199_pad_0, pad_type = input_3199_pad_type_0, strides = input_3199_strides_0, weight = const_477_to_fp16, x = var_20529_cast_fp16)[name = string("input_3201_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> input_3203_cast_fp16 = relu(x = input_3201_cast_fp16)[name = string("input_3203_cast_fp16")];
            string input_3205_pad_type_0 = const()[name = string("input_3205_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3205_pad_0 = const()[name = string("input_3205_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6282176)))];
            int32 input_3205_groups_0 = const()[name = string("input_3205_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_3205_strides_0 = const()[name = string("input_3205_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3205_dilations_0 = const()[name = string("input_3205_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 128, 16, 16]> input_3207_cast_fp16 = conv(bias = const_480_to_fp16, dilations = input_3205_dilations_0, groups = input_3205_groups_0, pad = input_3205_pad_0, pad_type = input_3205_pad_type_0, strides = input_3205_strides_0, weight = const_479_to_fp16, x = input_3203_cast_fp16)[name = string("input_3207_cast_fp16")];
            string input_3209_pad_type_0 = const()[name = string("input_3209_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3209_strides_0 = const()[name = string("input_3209_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3209_pad_0 = const()[name = string("input_3209_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6282304)))];
            tensor<int32, [2]> input_3209_dilations_0 = const()[name = string("input_3209_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3209_groups_0 = const()[name = string("input_3209_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3211_cast_fp16 = conv(bias = const_482_to_fp16, dilations = input_3209_dilations_0, groups = input_3209_groups_0, pad = input_3209_pad_0, pad_type = input_3209_pad_type_0, strides = input_3209_strides_0, weight = const_481_to_fp16, x = input_3207_cast_fp16)[name = string("input_3211_cast_fp16")];
            tensor<fp16, [1, 128, 16, 16]> out3_95_cast_fp16 = relu(x = input_3211_cast_fp16)[name = string("out3_95_cast_fp16")];
            bool input_3213_interleave_0 = const()[name = string("input_3213_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 16, 16]> input_3213_cast_fp16 = concat(axis = var_16879, interleave = input_3213_interleave_0, values = (var_20517_cast_fp16, out1_95_cast_fp16, out2_95_cast_fp16, out3_95_cast_fp16))[name = string("input_3213_cast_fp16")];
            string input_3215_pad_type_0 = const()[name = string("input_3215_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3215_strides_0 = const()[name = string("input_3215_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_3215_pad_0 = const()[name = string("input_3215_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6282432)))];
            tensor<int32, [2]> input_3215_dilations_0 = const()[name = string("input_3215_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3215_groups_0 = const()[name = string("input_3215_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 16, 16]> input_3215_cast_fp16 = conv(dilations = input_3215_dilations_0, groups = input_3215_groups_0, pad = input_3215_pad_0, pad_type = input_3215_pad_type_0, strides = input_3215_strides_0, weight = model_value_encoder_backbone_xfpn_p5_1x1_weight_to_fp16, x = input_3213_cast_fp16)[name = string("input_3215_cast_fp16")];
            fp32 y_121_scale_factor_height_0 = const()[name = string("y_121_scale_factor_height_0"), val = fp32(2)];
            fp32 y_121_scale_factor_width_0 = const()[name = string("y_121_scale_factor_width_0"), val = fp32(2)];
            tensor<fp16, [1, 128, 32, 32]> y_121_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = y_121_scale_factor_height_0, scale_factor_width = y_121_scale_factor_width_0, x = input_3215_cast_fp16)[name = string("y_121_cast_fp16")];
            string x_199_pad_type_0 = const()[name = string("x_199_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_199_strides_0 = const()[name = string("x_199_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_199_pad_0 = const()[name = string("x_199_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6282560)))];
            tensor<int32, [2]> x_199_dilations_0 = const()[name = string("x_199_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_199_groups_0 = const()[name = string("x_199_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 32, 32]> x_199_cast_fp16 = conv(dilations = x_199_dilations_0, groups = x_199_groups_0, pad = x_199_pad_0, pad_type = x_199_pad_type_0, strides = x_199_strides_0, weight = model_value_encoder_backbone_xfpn_p4_1x1_weight_to_fp16, x = input_3085_cast_fp16)[name = string("x_199_cast_fp16")];
            tensor<fp16, [1, 128, 32, 32]> input_3217_cast_fp16 = add(x = x_199_cast_fp16, y = y_121_cast_fp16)[name = string("input_3217_cast_fp16")];
            string input_3317_pad_type_0 = const()[name = string("input_3317_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3317_pad_0 = const()[name = string("input_3317_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6282688)))];
            int32 input_3317_groups_0 = const()[name = string("input_3317_groups_0"), val = int32(128)];
            tensor<int32, [2]> input_3317_strides_0 = const()[name = string("input_3317_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3317_dilations_0 = const()[name = string("input_3317_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [1, 128, 32, 32]> input_3317_cast_fp16 = conv(dilations = input_3317_dilations_0, groups = input_3317_groups_0, pad = input_3317_pad_0, pad_type = input_3317_pad_type_0, strides = input_3317_strides_0, weight = model_value_encoder_backbone_xfpn_fpn_output4_weight_to_fp16, x = input_3217_cast_fp16)[name = string("input_3317_cast_fp16")];
            string input_pad_type_0 = const()[name = string("input_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_strides_0 = const()[name = string("input_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_pad_0 = const()[name = string("input_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6282816)))];
            tensor<int32, [2]> input_dilations_0 = const()[name = string("input_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_groups_0 = const()[name = string("input_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 32, 32]> input_cast_fp16 = conv(bias = model_value_encoder_fuser_bias_to_fp16, dilations = input_dilations_0, groups = input_groups_0, pad = input_pad_0, pad_type = input_pad_type_0, strides = input_strides_0, weight = model_value_encoder_fuser_weight_to_fp16, x = input_3317_cast_fp16)[name = string("input_cast_fp16")];
            string var_20653_pad_type_0 = const()[name = string("op_20653_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> var_20653_pad_0 = const()[name = string("op_20653_pad_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6282944)))];
            tensor<int32, [2]> var_20653_strides_0 = const()[name = string("op_20653_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_20653_dilations_0 = const()[name = string("op_20653_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_20653_groups_0 = const()[name = string("op_20653_groups_0"), val = int32(1)];
            tensor<fp16, [1, 192, 32, 32]> var_20653_cast_fp16 = conv(bias = model_value_encoder_hidden_reinforce_transform1_bias_to_fp16, dilations = var_20653_dilations_0, groups = var_20653_groups_0, pad = var_20653_pad_0, pad_type = var_20653_pad_type_0, strides = var_20653_strides_0, weight = model_value_encoder_hidden_reinforce_transform1_weight_to_fp16, x = input_cast_fp16)[name = string("op_20653_cast_fp16")];
            tensor<fp16, [1, 192, 32, 32]> values_cast_fp16 = add(x = var_20653_cast_fp16, y = var_7657_cast_fp16)[name = string("values_cast_fp16")];
            tensor<int32, [4]> var_20662_begin_0 = const()[name = string("op_20662_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6283072)))];
            tensor<int32, [4]> var_20662_end_0 = const()[name = string("op_20662_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6283200)))];
            tensor<bool, [4]> var_20662_end_mask_0 = const()[name = string("op_20662_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20662_cast_fp16 = slice_by_index(begin = var_20662_begin_0, end = var_20662_end_0, end_mask = var_20662_end_mask_0, x = values_cast_fp16)[name = string("op_20662_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> forget_gate_cast_fp16 = sigmoid(x = var_20662_cast_fp16)[name = string("forget_gate_cast_fp16")];
            tensor<int32, [4]> var_20665_begin_0 = const()[name = string("op_20665_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6283328)))];
            tensor<int32, [4]> var_20665_end_0 = const()[name = string("op_20665_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6283456)))];
            tensor<bool, [4]> var_20665_end_mask_0 = const()[name = string("op_20665_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20665_cast_fp16 = slice_by_index(begin = var_20665_begin_0, end = var_20665_end_0, end_mask = var_20665_end_mask_0, x = values_cast_fp16)[name = string("op_20665_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> update_gate_cast_fp16 = sigmoid(x = var_20665_cast_fp16)[name = string("update_gate_cast_fp16")];
            tensor<int32, [4]> var_20668_begin_0 = const()[name = string("op_20668_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6283584)))];
            tensor<int32, [4]> var_20668_end_0 = const()[name = string("op_20668_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6283712)))];
            tensor<bool, [4]> var_20668_end_mask_0 = const()[name = string("op_20668_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 64, 32, 32]> var_20668_cast_fp16 = slice_by_index(begin = var_20668_begin_0, end = var_20668_end_0, end_mask = var_20668_end_mask_0, x = values_cast_fp16)[name = string("op_20668_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> new_value_cast_fp16 = tanh(x = var_20668_cast_fp16)[name = string("new_value_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> var_20670_cast_fp16 = mul(x = forget_gate_cast_fp16, y = hidden_state)[name = string("op_20670_cast_fp16")];
            fp16 var_16879_promoted_to_fp16 = const()[name = string("op_16879_promoted_to_fp16"), val = fp16(1)];
            tensor<fp16, [1, 64, 32, 32]> var_20671_cast_fp16 = sub(x = var_16879_promoted_to_fp16, y = update_gate_cast_fp16)[name = string("op_20671_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> var_20672_cast_fp16 = mul(x = var_20670_cast_fp16, y = var_20671_cast_fp16)[name = string("op_20672_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> var_20673_cast_fp16 = mul(x = update_gate_cast_fp16, y = new_value_cast_fp16)[name = string("op_20673_cast_fp16")];
            tensor<fp16, [1, 64, 32, 32]> update_h = add(x = var_20672_cast_fp16, y = var_20673_cast_fp16)[name = string("op_20674_cast_fp16")];
            tensor<int32, [4]> k_perm_0 = const()[name = string("k_perm_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6283840)))];
            tensor<int32, [4]> var_20711 = const()[name = string("op_20711"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6283968)))];
            tensor<fp16, [1, 128, 1, 1024]> v_cast_fp16 = reshape(shape = var_20711, x = input_cast_fp16)[name = string("v_cast_fp16")];
            tensor<int32, [4]> var_20725_begin_0 = const()[name = string("op_20725_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6284096)))];
            tensor<int32, [4]> var_20725_end_0 = const()[name = string("op_20725_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6284224)))];
            tensor<bool, [4]> var_20725_end_mask_0 = const()[name = string("op_20725_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 1024, 1, 64]> var_20725_cast_fp16 = slice_by_index(begin = var_20725_begin_0, end = var_20725_end_0, end_mask = var_20725_end_mask_0, x = prev_key)[name = string("op_20725_cast_fp16")];
            int32 var_20727 = const()[name = string("op_20727"), val = int32(1)];
            bool var_20728_interleave_0 = const()[name = string("op_20728_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1024, 1, 64]> k_cast_fp16 = transpose(perm = k_perm_0, x = var_11917_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 2048, 1, 64]> update_k = concat(axis = var_20727, interleave = var_20728_interleave_0, values = (var_20725_cast_fp16, k_cast_fp16))[name = string("op_20728_cast_fp16")];
            tensor<int32, [4]> var_20751_begin_0 = const()[name = string("op_20751_begin_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6284352)))];
            tensor<int32, [4]> var_20751_end_0 = const()[name = string("op_20751_end_0"), val = tensor<int32, [4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6284480)))];
            tensor<bool, [4]> var_20751_end_mask_0 = const()[name = string("op_20751_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 128, 1, 1024]> var_20751_cast_fp16 = slice_by_index(begin = var_20751_begin_0, end = var_20751_end_0, end_mask = var_20751_end_mask_0, x = prev_value)[name = string("op_20751_cast_fp16")];
            int32 var_20753 = const()[name = string("op_20753"), val = int32(3)];
            bool var_20754_interleave_0 = const()[name = string("op_20754_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 1, 2048]> update_v = concat(axis = var_20753, interleave = var_20754_interleave_0, values = (var_20751_cast_fp16, v_cast_fp16))[name = string("op_20754_cast_fp16")];
            tensor<fp16, [1, 1, 512, 512]> update_prob = sigmoid(x = var_12307_cast_fp16)[name = string("op_20757_cast_fp16")];
        } -> (update_h, update_k, update_v, update_prob, update_q);
}