program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-torch", "2.10.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})]
{
    func main<ios17>(tensor<fp32, [1, 3, 112, 112]> faceImage) {
            tensor<fp32, []> faceImage__scaled___y_0 = const()[name = tensor<string, []>("faceImage__scaled___y_0"), val = tensor<fp32, []>(0x1.010102p-7)];
            tensor<fp32, [1, 3, 112, 112]> faceImage__scaled__ = mul(x = faceImage, y = faceImage__scaled___y_0)[name = tensor<string, []>("faceImage__scaled__")];
            tensor<fp32, [1, 3, 1, 1]> faceImage__biased___y_0 = const()[name = tensor<string, []>("faceImage__biased___y_0"), val = tensor<fp32, [1, 3, 1, 1]>([[[[-0x1p+0]], [[-0x1p+0]], [[-0x1p+0]]]])];
            tensor<fp32, [1, 3, 112, 112]> faceImage__biased__ = add(x = faceImage__scaled__, y = faceImage__biased___y_0)[name = tensor<string, []>("faceImage__biased__")];
            tensor<string, []> input_tensor_1_pad_type_0 = const()[name = tensor<string, []>("input_tensor_1_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_1_pad_0 = const()[name = tensor<string, []>("input_tensor_1_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_1_strides_0 = const()[name = tensor<string, []>("input_tensor_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_1_dilations_0 = const()[name = tensor<string, []>("input_tensor_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_1_groups_0 = const()[name = tensor<string, []>("input_tensor_1_groups_0"), val = tensor<int32, []>(1)];
            tensor<string, []> faceImage_to_fp16_dtype_0 = const()[name = tensor<string, []>("faceImage_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [64, 3, 3, 3]> conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("conv1_Conv_weight_to_fp16"), val = tensor<fp16, [64, 3, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [64]> conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("conv1_Conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3584)))];
            tensor<fp16, [1, 3, 112, 112]> faceImage_to_fp16 = cast(dtype = faceImage_to_fp16_dtype_0, x = faceImage__biased__)[name = tensor<string, []>("cast_52")];
            tensor<fp16, [1, 64, 112, 112]> input_tensor_1_cast_fp16 = conv(bias = conv1_Conv_bias_to_fp16, dilations = input_tensor_1_dilations_0, groups = input_tensor_1_groups_0, pad = input_tensor_1_pad_0, pad_type = input_tensor_1_pad_type_0, strides = input_tensor_1_strides_0, weight = conv1_Conv_weight_to_fp16, x = faceImage_to_fp16)[name = tensor<string, []>("input_tensor_1_cast_fp16")];
            tensor<fp32, [64]> input_1_alpha_0 = const()[name = tensor<string, []>("input_1_alpha_0"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3776)))];
            tensor<fp16, [1, 64, 112, 112]> input_1_cast_fp16 = prelu(alpha = input_1_alpha_0, x = input_tensor_1_cast_fp16)[name = tensor<string, []>("input_1_cast_fp16")];
            tensor<fp16, [64]> layer1_layer1_0_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4096)))];
            tensor<fp16, [64]> layer1_layer1_0_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4288)))];
            tensor<fp16, [64]> layer1_layer1_0_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4480)))];
            tensor<fp16, [64]> layer1_layer1_0_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4672)))];
            tensor<fp16, []> var_273_to_fp16 = const()[name = tensor<string, []>("op_273_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 64, 112, 112]> input_3_cast_fp16 = batch_norm(beta = layer1_layer1_0_bn1_BatchNormalization_bias_to_fp16, epsilon = var_273_to_fp16, gamma = layer1_layer1_0_bn1_BatchNormalization_weight_to_fp16, mean = layer1_layer1_0_bn1_BatchNormalization_running_mean_to_fp16, variance = layer1_layer1_0_bn1_BatchNormalization_running_var_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
            tensor<string, []> input_tensor_3_pad_type_0 = const()[name = tensor<string, []>("input_tensor_3_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_3_pad_0 = const()[name = tensor<string, []>("input_tensor_3_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_3_strides_0 = const()[name = tensor<string, []>("input_tensor_3_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_3_dilations_0 = const()[name = tensor<string, []>("input_tensor_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_3_groups_0 = const()[name = tensor<string, []>("input_tensor_3_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 64, 3, 3]> layer1_layer1_0_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4864)))];
            tensor<fp16, [64]> layer1_layer1_0_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78656)))];
            tensor<fp16, [1, 64, 112, 112]> input_tensor_3_cast_fp16 = conv(bias = layer1_layer1_0_conv1_Conv_bias_to_fp16, dilations = input_tensor_3_dilations_0, groups = input_tensor_3_groups_0, pad = input_tensor_3_pad_0, pad_type = input_tensor_3_pad_type_0, strides = input_tensor_3_strides_0, weight = layer1_layer1_0_conv1_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("input_tensor_3_cast_fp16")];
            tensor<fp32, [64]> input_5_alpha_0 = const()[name = tensor<string, []>("input_5_alpha_0"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78848)))];
            tensor<fp16, [1, 64, 112, 112]> input_5_cast_fp16 = prelu(alpha = input_5_alpha_0, x = input_tensor_3_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
            tensor<string, []> first_1_pad_type_0 = const()[name = tensor<string, []>("first_1_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_1_pad_0 = const()[name = tensor<string, []>("first_1_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_1_strides_0 = const()[name = tensor<string, []>("first_1_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> first_1_dilations_0 = const()[name = tensor<string, []>("first_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_1_groups_0 = const()[name = tensor<string, []>("first_1_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 64, 3, 3]> layer1_layer1_0_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79168)))];
            tensor<fp16, [64]> layer1_layer1_0_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152960)))];
            tensor<fp16, [1, 64, 56, 56]> first_1_cast_fp16 = conv(bias = layer1_layer1_0_conv2_Conv_bias_to_fp16, dilations = first_1_dilations_0, groups = first_1_groups_0, pad = first_1_pad_0, pad_type = first_1_pad_type_0, strides = first_1_strides_0, weight = layer1_layer1_0_conv2_Conv_weight_to_fp16, x = input_5_cast_fp16)[name = tensor<string, []>("first_1_cast_fp16")];
            tensor<string, []> second_1_pad_type_0 = const()[name = tensor<string, []>("second_1_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> second_1_strides_0 = const()[name = tensor<string, []>("second_1_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> second_1_pad_0 = const()[name = tensor<string, []>("second_1_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> second_1_dilations_0 = const()[name = tensor<string, []>("second_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> second_1_groups_0 = const()[name = tensor<string, []>("second_1_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 64, 1, 1]> layer1_layer1_0_downsample_downsample_0_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_downsample_downsample_0_Conv_weight_to_fp16"), val = tensor<fp16, [64, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153152)))];
            tensor<fp16, [64]> layer1_layer1_0_downsample_downsample_0_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_0_downsample_downsample_0_Conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161408)))];
            tensor<fp16, [1, 64, 56, 56]> second_1_cast_fp16 = conv(bias = layer1_layer1_0_downsample_downsample_0_Conv_bias_to_fp16, dilations = second_1_dilations_0, groups = second_1_groups_0, pad = second_1_pad_0, pad_type = second_1_pad_type_0, strides = second_1_strides_0, weight = layer1_layer1_0_downsample_downsample_0_Conv_weight_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("second_1_cast_fp16")];
            tensor<fp16, [1, 64, 56, 56]> input_7_cast_fp16 = add(x = first_1_cast_fp16, y = second_1_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")];
            tensor<fp16, [64]> layer1_layer1_1_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_1_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161600)))];
            tensor<fp16, [64]> layer1_layer1_1_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_1_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161792)))];
            tensor<fp16, [64]> layer1_layer1_1_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_1_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161984)))];
            tensor<fp16, [64]> layer1_layer1_1_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_1_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162176)))];
            tensor<fp16, []> var_323_to_fp16 = const()[name = tensor<string, []>("op_323_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 64, 56, 56]> input_9_cast_fp16 = batch_norm(beta = layer1_layer1_1_bn1_BatchNormalization_bias_to_fp16, epsilon = var_323_to_fp16, gamma = layer1_layer1_1_bn1_BatchNormalization_weight_to_fp16, mean = layer1_layer1_1_bn1_BatchNormalization_running_mean_to_fp16, variance = layer1_layer1_1_bn1_BatchNormalization_running_var_to_fp16, x = input_7_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
            tensor<string, []> input_tensor_5_pad_type_0 = const()[name = tensor<string, []>("input_tensor_5_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_5_pad_0 = const()[name = tensor<string, []>("input_tensor_5_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_5_strides_0 = const()[name = tensor<string, []>("input_tensor_5_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_5_dilations_0 = const()[name = tensor<string, []>("input_tensor_5_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_5_groups_0 = const()[name = tensor<string, []>("input_tensor_5_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 64, 3, 3]> layer1_layer1_1_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_1_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162368)))];
            tensor<fp16, [64]> layer1_layer1_1_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_1_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(236160)))];
            tensor<fp16, [1, 64, 56, 56]> input_tensor_5_cast_fp16 = conv(bias = layer1_layer1_1_conv1_Conv_bias_to_fp16, dilations = input_tensor_5_dilations_0, groups = input_tensor_5_groups_0, pad = input_tensor_5_pad_0, pad_type = input_tensor_5_pad_type_0, strides = input_tensor_5_strides_0, weight = layer1_layer1_1_conv1_Conv_weight_to_fp16, x = input_9_cast_fp16)[name = tensor<string, []>("input_tensor_5_cast_fp16")];
            tensor<fp32, [64]> input_11_alpha_0 = const()[name = tensor<string, []>("input_11_alpha_0"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(236352)))];
            tensor<fp16, [1, 64, 56, 56]> input_11_cast_fp16 = prelu(alpha = input_11_alpha_0, x = input_tensor_5_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
            tensor<string, []> first_3_pad_type_0 = const()[name = tensor<string, []>("first_3_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_3_pad_0 = const()[name = tensor<string, []>("first_3_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_3_strides_0 = const()[name = tensor<string, []>("first_3_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_3_dilations_0 = const()[name = tensor<string, []>("first_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_3_groups_0 = const()[name = tensor<string, []>("first_3_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 64, 3, 3]> layer1_layer1_1_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_1_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(236672)))];
            tensor<fp16, [64]> layer1_layer1_1_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_1_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(310464)))];
            tensor<fp16, [1, 64, 56, 56]> first_3_cast_fp16 = conv(bias = layer1_layer1_1_conv2_Conv_bias_to_fp16, dilations = first_3_dilations_0, groups = first_3_groups_0, pad = first_3_pad_0, pad_type = first_3_pad_type_0, strides = first_3_strides_0, weight = layer1_layer1_1_conv2_Conv_weight_to_fp16, x = input_11_cast_fp16)[name = tensor<string, []>("first_3_cast_fp16")];
            tensor<fp16, [1, 64, 56, 56]> input_13_cast_fp16 = add(x = first_3_cast_fp16, y = input_7_cast_fp16)[name = tensor<string, []>("input_13_cast_fp16")];
            tensor<fp16, [64]> layer1_layer1_2_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_2_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(310656)))];
            tensor<fp16, [64]> layer1_layer1_2_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_2_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(310848)))];
            tensor<fp16, [64]> layer1_layer1_2_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_2_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(311040)))];
            tensor<fp16, [64]> layer1_layer1_2_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_2_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(311232)))];
            tensor<fp16, []> var_360_to_fp16 = const()[name = tensor<string, []>("op_360_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 64, 56, 56]> input_15_cast_fp16 = batch_norm(beta = layer1_layer1_2_bn1_BatchNormalization_bias_to_fp16, epsilon = var_360_to_fp16, gamma = layer1_layer1_2_bn1_BatchNormalization_weight_to_fp16, mean = layer1_layer1_2_bn1_BatchNormalization_running_mean_to_fp16, variance = layer1_layer1_2_bn1_BatchNormalization_running_var_to_fp16, x = input_13_cast_fp16)[name = tensor<string, []>("input_15_cast_fp16")];
            tensor<string, []> input_tensor_7_pad_type_0 = const()[name = tensor<string, []>("input_tensor_7_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_7_pad_0 = const()[name = tensor<string, []>("input_tensor_7_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_7_strides_0 = const()[name = tensor<string, []>("input_tensor_7_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_7_dilations_0 = const()[name = tensor<string, []>("input_tensor_7_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_7_groups_0 = const()[name = tensor<string, []>("input_tensor_7_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 64, 3, 3]> layer1_layer1_2_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_2_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(311424)))];
            tensor<fp16, [64]> layer1_layer1_2_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_2_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(385216)))];
            tensor<fp16, [1, 64, 56, 56]> input_tensor_7_cast_fp16 = conv(bias = layer1_layer1_2_conv1_Conv_bias_to_fp16, dilations = input_tensor_7_dilations_0, groups = input_tensor_7_groups_0, pad = input_tensor_7_pad_0, pad_type = input_tensor_7_pad_type_0, strides = input_tensor_7_strides_0, weight = layer1_layer1_2_conv1_Conv_weight_to_fp16, x = input_15_cast_fp16)[name = tensor<string, []>("input_tensor_7_cast_fp16")];
            tensor<fp32, [64]> input_17_alpha_0 = const()[name = tensor<string, []>("input_17_alpha_0"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(385408)))];
            tensor<fp16, [1, 64, 56, 56]> input_17_cast_fp16 = prelu(alpha = input_17_alpha_0, x = input_tensor_7_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")];
            tensor<string, []> first_5_pad_type_0 = const()[name = tensor<string, []>("first_5_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_5_pad_0 = const()[name = tensor<string, []>("first_5_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_5_strides_0 = const()[name = tensor<string, []>("first_5_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_5_dilations_0 = const()[name = tensor<string, []>("first_5_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_5_groups_0 = const()[name = tensor<string, []>("first_5_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 64, 3, 3]> layer1_layer1_2_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_2_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(385728)))];
            tensor<fp16, [64]> layer1_layer1_2_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer1_layer1_2_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(459520)))];
            tensor<fp16, [1, 64, 56, 56]> first_5_cast_fp16 = conv(bias = layer1_layer1_2_conv2_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = layer1_layer1_2_conv2_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = tensor<string, []>("first_5_cast_fp16")];
            tensor<fp16, [1, 64, 56, 56]> input_19_cast_fp16 = add(x = first_5_cast_fp16, y = input_13_cast_fp16)[name = tensor<string, []>("input_19_cast_fp16")];
            tensor<fp16, [64]> layer2_layer2_0_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(459712)))];
            tensor<fp16, [64]> layer2_layer2_0_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(459904)))];
            tensor<fp16, [64]> layer2_layer2_0_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(460096)))];
            tensor<fp16, [64]> layer2_layer2_0_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(460288)))];
            tensor<fp16, []> var_397_to_fp16 = const()[name = tensor<string, []>("op_397_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 64, 56, 56]> input_21_cast_fp16 = batch_norm(beta = layer2_layer2_0_bn1_BatchNormalization_bias_to_fp16, epsilon = var_397_to_fp16, gamma = layer2_layer2_0_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_0_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_0_bn1_BatchNormalization_running_var_to_fp16, x = input_19_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
            tensor<string, []> input_tensor_9_pad_type_0 = const()[name = tensor<string, []>("input_tensor_9_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_9_pad_0 = const()[name = tensor<string, []>("input_tensor_9_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_9_strides_0 = const()[name = tensor<string, []>("input_tensor_9_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_9_dilations_0 = const()[name = tensor<string, []>("input_tensor_9_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_9_groups_0 = const()[name = tensor<string, []>("input_tensor_9_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 64, 3, 3]> layer2_layer2_0_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(460480)))];
            tensor<fp16, [128]> layer2_layer2_0_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(608000)))];
            tensor<fp16, [1, 128, 56, 56]> input_tensor_9_cast_fp16 = conv(bias = layer2_layer2_0_conv1_Conv_bias_to_fp16, dilations = input_tensor_9_dilations_0, groups = input_tensor_9_groups_0, pad = input_tensor_9_pad_0, pad_type = input_tensor_9_pad_type_0, strides = input_tensor_9_strides_0, weight = layer2_layer2_0_conv1_Conv_weight_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("input_tensor_9_cast_fp16")];
            tensor<fp32, [128]> input_23_alpha_0 = const()[name = tensor<string, []>("input_23_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(608320)))];
            tensor<fp16, [1, 128, 56, 56]> input_23_cast_fp16 = prelu(alpha = input_23_alpha_0, x = input_tensor_9_cast_fp16)[name = tensor<string, []>("input_23_cast_fp16")];
            tensor<string, []> first_7_pad_type_0 = const()[name = tensor<string, []>("first_7_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_7_pad_0 = const()[name = tensor<string, []>("first_7_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_7_strides_0 = const()[name = tensor<string, []>("first_7_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> first_7_dilations_0 = const()[name = tensor<string, []>("first_7_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_7_groups_0 = const()[name = tensor<string, []>("first_7_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_0_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(608896)))];
            tensor<fp16, [128]> layer2_layer2_0_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(903872)))];
            tensor<fp16, [1, 128, 28, 28]> first_7_cast_fp16 = conv(bias = layer2_layer2_0_conv2_Conv_bias_to_fp16, dilations = first_7_dilations_0, groups = first_7_groups_0, pad = first_7_pad_0, pad_type = first_7_pad_type_0, strides = first_7_strides_0, weight = layer2_layer2_0_conv2_Conv_weight_to_fp16, x = input_23_cast_fp16)[name = tensor<string, []>("first_7_cast_fp16")];
            tensor<string, []> second_3_pad_type_0 = const()[name = tensor<string, []>("second_3_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> second_3_strides_0 = const()[name = tensor<string, []>("second_3_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> second_3_pad_0 = const()[name = tensor<string, []>("second_3_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> second_3_dilations_0 = const()[name = tensor<string, []>("second_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> second_3_groups_0 = const()[name = tensor<string, []>("second_3_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 64, 1, 1]> layer2_layer2_0_downsample_downsample_0_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_downsample_downsample_0_Conv_weight_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(904192)))];
            tensor<fp16, [128]> layer2_layer2_0_downsample_downsample_0_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_0_downsample_downsample_0_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(920640)))];
            tensor<fp16, [1, 128, 28, 28]> second_3_cast_fp16 = conv(bias = layer2_layer2_0_downsample_downsample_0_Conv_bias_to_fp16, dilations = second_3_dilations_0, groups = second_3_groups_0, pad = second_3_pad_0, pad_type = second_3_pad_type_0, strides = second_3_strides_0, weight = layer2_layer2_0_downsample_downsample_0_Conv_weight_to_fp16, x = input_19_cast_fp16)[name = tensor<string, []>("second_3_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_25_cast_fp16 = add(x = first_7_cast_fp16, y = second_3_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_1_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_1_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(920960)))];
            tensor<fp16, [128]> layer2_layer2_1_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_1_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(921280)))];
            tensor<fp16, [128]> layer2_layer2_1_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_1_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(921600)))];
            tensor<fp16, [128]> layer2_layer2_1_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_1_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(921920)))];
            tensor<fp16, []> var_447_to_fp16 = const()[name = tensor<string, []>("op_447_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_27_cast_fp16 = batch_norm(beta = layer2_layer2_1_bn1_BatchNormalization_bias_to_fp16, epsilon = var_447_to_fp16, gamma = layer2_layer2_1_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_1_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_1_bn1_BatchNormalization_running_var_to_fp16, x = input_25_cast_fp16)[name = tensor<string, []>("input_27_cast_fp16")];
            tensor<string, []> input_tensor_11_pad_type_0 = const()[name = tensor<string, []>("input_tensor_11_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_11_pad_0 = const()[name = tensor<string, []>("input_tensor_11_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_11_strides_0 = const()[name = tensor<string, []>("input_tensor_11_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_11_dilations_0 = const()[name = tensor<string, []>("input_tensor_11_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_11_groups_0 = const()[name = tensor<string, []>("input_tensor_11_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_1_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_1_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(922240)))];
            tensor<fp16, [128]> layer2_layer2_1_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_1_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1217216)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_11_cast_fp16 = conv(bias = layer2_layer2_1_conv1_Conv_bias_to_fp16, dilations = input_tensor_11_dilations_0, groups = input_tensor_11_groups_0, pad = input_tensor_11_pad_0, pad_type = input_tensor_11_pad_type_0, strides = input_tensor_11_strides_0, weight = layer2_layer2_1_conv1_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = tensor<string, []>("input_tensor_11_cast_fp16")];
            tensor<fp32, [128]> input_29_alpha_0 = const()[name = tensor<string, []>("input_29_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1217536)))];
            tensor<fp16, [1, 128, 28, 28]> input_29_cast_fp16 = prelu(alpha = input_29_alpha_0, x = input_tensor_11_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")];
            tensor<string, []> first_9_pad_type_0 = const()[name = tensor<string, []>("first_9_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_9_pad_0 = const()[name = tensor<string, []>("first_9_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_9_strides_0 = const()[name = tensor<string, []>("first_9_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_9_dilations_0 = const()[name = tensor<string, []>("first_9_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_9_groups_0 = const()[name = tensor<string, []>("first_9_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_1_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_1_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1218112)))];
            tensor<fp16, [128]> layer2_layer2_1_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_1_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1513088)))];
            tensor<fp16, [1, 128, 28, 28]> first_9_cast_fp16 = conv(bias = layer2_layer2_1_conv2_Conv_bias_to_fp16, dilations = first_9_dilations_0, groups = first_9_groups_0, pad = first_9_pad_0, pad_type = first_9_pad_type_0, strides = first_9_strides_0, weight = layer2_layer2_1_conv2_Conv_weight_to_fp16, x = input_29_cast_fp16)[name = tensor<string, []>("first_9_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_31_cast_fp16 = add(x = first_9_cast_fp16, y = input_25_cast_fp16)[name = tensor<string, []>("input_31_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_2_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_2_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1513408)))];
            tensor<fp16, [128]> layer2_layer2_2_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_2_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1513728)))];
            tensor<fp16, [128]> layer2_layer2_2_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_2_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1514048)))];
            tensor<fp16, [128]> layer2_layer2_2_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_2_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1514368)))];
            tensor<fp16, []> var_484_to_fp16 = const()[name = tensor<string, []>("op_484_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_33_cast_fp16 = batch_norm(beta = layer2_layer2_2_bn1_BatchNormalization_bias_to_fp16, epsilon = var_484_to_fp16, gamma = layer2_layer2_2_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_2_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_2_bn1_BatchNormalization_running_var_to_fp16, x = input_31_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
            tensor<string, []> input_tensor_13_pad_type_0 = const()[name = tensor<string, []>("input_tensor_13_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_13_pad_0 = const()[name = tensor<string, []>("input_tensor_13_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_13_strides_0 = const()[name = tensor<string, []>("input_tensor_13_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_13_dilations_0 = const()[name = tensor<string, []>("input_tensor_13_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_13_groups_0 = const()[name = tensor<string, []>("input_tensor_13_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_2_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_2_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1514688)))];
            tensor<fp16, [128]> layer2_layer2_2_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_2_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1809664)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_13_cast_fp16 = conv(bias = layer2_layer2_2_conv1_Conv_bias_to_fp16, dilations = input_tensor_13_dilations_0, groups = input_tensor_13_groups_0, pad = input_tensor_13_pad_0, pad_type = input_tensor_13_pad_type_0, strides = input_tensor_13_strides_0, weight = layer2_layer2_2_conv1_Conv_weight_to_fp16, x = input_33_cast_fp16)[name = tensor<string, []>("input_tensor_13_cast_fp16")];
            tensor<fp32, [128]> input_35_alpha_0 = const()[name = tensor<string, []>("input_35_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1809984)))];
            tensor<fp16, [1, 128, 28, 28]> input_35_cast_fp16 = prelu(alpha = input_35_alpha_0, x = input_tensor_13_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")];
            tensor<string, []> first_11_pad_type_0 = const()[name = tensor<string, []>("first_11_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_11_pad_0 = const()[name = tensor<string, []>("first_11_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_11_strides_0 = const()[name = tensor<string, []>("first_11_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_11_dilations_0 = const()[name = tensor<string, []>("first_11_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_11_groups_0 = const()[name = tensor<string, []>("first_11_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_2_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_2_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1810560)))];
            tensor<fp16, [128]> layer2_layer2_2_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_2_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2105536)))];
            tensor<fp16, [1, 128, 28, 28]> first_11_cast_fp16 = conv(bias = layer2_layer2_2_conv2_Conv_bias_to_fp16, dilations = first_11_dilations_0, groups = first_11_groups_0, pad = first_11_pad_0, pad_type = first_11_pad_type_0, strides = first_11_strides_0, weight = layer2_layer2_2_conv2_Conv_weight_to_fp16, x = input_35_cast_fp16)[name = tensor<string, []>("first_11_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_37_cast_fp16 = add(x = first_11_cast_fp16, y = input_31_cast_fp16)[name = tensor<string, []>("input_37_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_3_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_3_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2105856)))];
            tensor<fp16, [128]> layer2_layer2_3_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_3_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2106176)))];
            tensor<fp16, [128]> layer2_layer2_3_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_3_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2106496)))];
            tensor<fp16, [128]> layer2_layer2_3_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_3_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2106816)))];
            tensor<fp16, []> var_521_to_fp16 = const()[name = tensor<string, []>("op_521_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_39_cast_fp16 = batch_norm(beta = layer2_layer2_3_bn1_BatchNormalization_bias_to_fp16, epsilon = var_521_to_fp16, gamma = layer2_layer2_3_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_3_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_3_bn1_BatchNormalization_running_var_to_fp16, x = input_37_cast_fp16)[name = tensor<string, []>("input_39_cast_fp16")];
            tensor<string, []> input_tensor_15_pad_type_0 = const()[name = tensor<string, []>("input_tensor_15_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_15_pad_0 = const()[name = tensor<string, []>("input_tensor_15_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_15_strides_0 = const()[name = tensor<string, []>("input_tensor_15_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_15_dilations_0 = const()[name = tensor<string, []>("input_tensor_15_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_15_groups_0 = const()[name = tensor<string, []>("input_tensor_15_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_3_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_3_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2107136)))];
            tensor<fp16, [128]> layer2_layer2_3_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_3_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2402112)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_15_cast_fp16 = conv(bias = layer2_layer2_3_conv1_Conv_bias_to_fp16, dilations = input_tensor_15_dilations_0, groups = input_tensor_15_groups_0, pad = input_tensor_15_pad_0, pad_type = input_tensor_15_pad_type_0, strides = input_tensor_15_strides_0, weight = layer2_layer2_3_conv1_Conv_weight_to_fp16, x = input_39_cast_fp16)[name = tensor<string, []>("input_tensor_15_cast_fp16")];
            tensor<fp32, [128]> input_41_alpha_0 = const()[name = tensor<string, []>("input_41_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2402432)))];
            tensor<fp16, [1, 128, 28, 28]> input_41_cast_fp16 = prelu(alpha = input_41_alpha_0, x = input_tensor_15_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")];
            tensor<string, []> first_13_pad_type_0 = const()[name = tensor<string, []>("first_13_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_13_pad_0 = const()[name = tensor<string, []>("first_13_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_13_strides_0 = const()[name = tensor<string, []>("first_13_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_13_dilations_0 = const()[name = tensor<string, []>("first_13_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_13_groups_0 = const()[name = tensor<string, []>("first_13_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_3_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_3_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2403008)))];
            tensor<fp16, [128]> layer2_layer2_3_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_3_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2697984)))];
            tensor<fp16, [1, 128, 28, 28]> first_13_cast_fp16 = conv(bias = layer2_layer2_3_conv2_Conv_bias_to_fp16, dilations = first_13_dilations_0, groups = first_13_groups_0, pad = first_13_pad_0, pad_type = first_13_pad_type_0, strides = first_13_strides_0, weight = layer2_layer2_3_conv2_Conv_weight_to_fp16, x = input_41_cast_fp16)[name = tensor<string, []>("first_13_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_43_cast_fp16 = add(x = first_13_cast_fp16, y = input_37_cast_fp16)[name = tensor<string, []>("input_43_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_4_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_4_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2698304)))];
            tensor<fp16, [128]> layer2_layer2_4_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_4_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2698624)))];
            tensor<fp16, [128]> layer2_layer2_4_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_4_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2698944)))];
            tensor<fp16, [128]> layer2_layer2_4_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_4_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2699264)))];
            tensor<fp16, []> var_558_to_fp16 = const()[name = tensor<string, []>("op_558_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_45_cast_fp16 = batch_norm(beta = layer2_layer2_4_bn1_BatchNormalization_bias_to_fp16, epsilon = var_558_to_fp16, gamma = layer2_layer2_4_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_4_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_4_bn1_BatchNormalization_running_var_to_fp16, x = input_43_cast_fp16)[name = tensor<string, []>("input_45_cast_fp16")];
            tensor<string, []> input_tensor_17_pad_type_0 = const()[name = tensor<string, []>("input_tensor_17_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_17_pad_0 = const()[name = tensor<string, []>("input_tensor_17_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_17_strides_0 = const()[name = tensor<string, []>("input_tensor_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_17_dilations_0 = const()[name = tensor<string, []>("input_tensor_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_17_groups_0 = const()[name = tensor<string, []>("input_tensor_17_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_4_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_4_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2699584)))];
            tensor<fp16, [128]> layer2_layer2_4_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_4_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2994560)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_17_cast_fp16 = conv(bias = layer2_layer2_4_conv1_Conv_bias_to_fp16, dilations = input_tensor_17_dilations_0, groups = input_tensor_17_groups_0, pad = input_tensor_17_pad_0, pad_type = input_tensor_17_pad_type_0, strides = input_tensor_17_strides_0, weight = layer2_layer2_4_conv1_Conv_weight_to_fp16, x = input_45_cast_fp16)[name = tensor<string, []>("input_tensor_17_cast_fp16")];
            tensor<fp32, [128]> input_47_alpha_0 = const()[name = tensor<string, []>("input_47_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2994880)))];
            tensor<fp16, [1, 128, 28, 28]> input_47_cast_fp16 = prelu(alpha = input_47_alpha_0, x = input_tensor_17_cast_fp16)[name = tensor<string, []>("input_47_cast_fp16")];
            tensor<string, []> first_15_pad_type_0 = const()[name = tensor<string, []>("first_15_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_15_pad_0 = const()[name = tensor<string, []>("first_15_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_15_strides_0 = const()[name = tensor<string, []>("first_15_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_15_dilations_0 = const()[name = tensor<string, []>("first_15_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_15_groups_0 = const()[name = tensor<string, []>("first_15_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_4_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_4_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2995456)))];
            tensor<fp16, [128]> layer2_layer2_4_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_4_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3290432)))];
            tensor<fp16, [1, 128, 28, 28]> first_15_cast_fp16 = conv(bias = layer2_layer2_4_conv2_Conv_bias_to_fp16, dilations = first_15_dilations_0, groups = first_15_groups_0, pad = first_15_pad_0, pad_type = first_15_pad_type_0, strides = first_15_strides_0, weight = layer2_layer2_4_conv2_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = tensor<string, []>("first_15_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_49_cast_fp16 = add(x = first_15_cast_fp16, y = input_43_cast_fp16)[name = tensor<string, []>("input_49_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_5_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_5_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3290752)))];
            tensor<fp16, [128]> layer2_layer2_5_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_5_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3291072)))];
            tensor<fp16, [128]> layer2_layer2_5_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_5_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3291392)))];
            tensor<fp16, [128]> layer2_layer2_5_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_5_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3291712)))];
            tensor<fp16, []> var_595_to_fp16 = const()[name = tensor<string, []>("op_595_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_51_cast_fp16 = batch_norm(beta = layer2_layer2_5_bn1_BatchNormalization_bias_to_fp16, epsilon = var_595_to_fp16, gamma = layer2_layer2_5_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_5_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_5_bn1_BatchNormalization_running_var_to_fp16, x = input_49_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
            tensor<string, []> input_tensor_19_pad_type_0 = const()[name = tensor<string, []>("input_tensor_19_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_19_pad_0 = const()[name = tensor<string, []>("input_tensor_19_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_19_strides_0 = const()[name = tensor<string, []>("input_tensor_19_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_19_dilations_0 = const()[name = tensor<string, []>("input_tensor_19_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_19_groups_0 = const()[name = tensor<string, []>("input_tensor_19_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_5_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_5_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3292032)))];
            tensor<fp16, [128]> layer2_layer2_5_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_5_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3587008)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_19_cast_fp16 = conv(bias = layer2_layer2_5_conv1_Conv_bias_to_fp16, dilations = input_tensor_19_dilations_0, groups = input_tensor_19_groups_0, pad = input_tensor_19_pad_0, pad_type = input_tensor_19_pad_type_0, strides = input_tensor_19_strides_0, weight = layer2_layer2_5_conv1_Conv_weight_to_fp16, x = input_51_cast_fp16)[name = tensor<string, []>("input_tensor_19_cast_fp16")];
            tensor<fp32, [128]> input_53_alpha_0 = const()[name = tensor<string, []>("input_53_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3587328)))];
            tensor<fp16, [1, 128, 28, 28]> input_53_cast_fp16 = prelu(alpha = input_53_alpha_0, x = input_tensor_19_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")];
            tensor<string, []> first_17_pad_type_0 = const()[name = tensor<string, []>("first_17_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_17_pad_0 = const()[name = tensor<string, []>("first_17_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_17_strides_0 = const()[name = tensor<string, []>("first_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_17_dilations_0 = const()[name = tensor<string, []>("first_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_17_groups_0 = const()[name = tensor<string, []>("first_17_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_5_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_5_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3587904)))];
            tensor<fp16, [128]> layer2_layer2_5_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_5_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3882880)))];
            tensor<fp16, [1, 128, 28, 28]> first_17_cast_fp16 = conv(bias = layer2_layer2_5_conv2_Conv_bias_to_fp16, dilations = first_17_dilations_0, groups = first_17_groups_0, pad = first_17_pad_0, pad_type = first_17_pad_type_0, strides = first_17_strides_0, weight = layer2_layer2_5_conv2_Conv_weight_to_fp16, x = input_53_cast_fp16)[name = tensor<string, []>("first_17_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_55_cast_fp16 = add(x = first_17_cast_fp16, y = input_49_cast_fp16)[name = tensor<string, []>("input_55_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_6_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_6_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3883200)))];
            tensor<fp16, [128]> layer2_layer2_6_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_6_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3883520)))];
            tensor<fp16, [128]> layer2_layer2_6_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_6_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3883840)))];
            tensor<fp16, [128]> layer2_layer2_6_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_6_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3884160)))];
            tensor<fp16, []> var_632_to_fp16 = const()[name = tensor<string, []>("op_632_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_57_cast_fp16 = batch_norm(beta = layer2_layer2_6_bn1_BatchNormalization_bias_to_fp16, epsilon = var_632_to_fp16, gamma = layer2_layer2_6_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_6_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_6_bn1_BatchNormalization_running_var_to_fp16, x = input_55_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")];
            tensor<string, []> input_tensor_21_pad_type_0 = const()[name = tensor<string, []>("input_tensor_21_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_21_pad_0 = const()[name = tensor<string, []>("input_tensor_21_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_21_strides_0 = const()[name = tensor<string, []>("input_tensor_21_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_21_dilations_0 = const()[name = tensor<string, []>("input_tensor_21_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_21_groups_0 = const()[name = tensor<string, []>("input_tensor_21_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_6_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_6_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3884480)))];
            tensor<fp16, [128]> layer2_layer2_6_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_6_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4179456)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_21_cast_fp16 = conv(bias = layer2_layer2_6_conv1_Conv_bias_to_fp16, dilations = input_tensor_21_dilations_0, groups = input_tensor_21_groups_0, pad = input_tensor_21_pad_0, pad_type = input_tensor_21_pad_type_0, strides = input_tensor_21_strides_0, weight = layer2_layer2_6_conv1_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = tensor<string, []>("input_tensor_21_cast_fp16")];
            tensor<fp32, [128]> input_59_alpha_0 = const()[name = tensor<string, []>("input_59_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4179776)))];
            tensor<fp16, [1, 128, 28, 28]> input_59_cast_fp16 = prelu(alpha = input_59_alpha_0, x = input_tensor_21_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
            tensor<string, []> first_19_pad_type_0 = const()[name = tensor<string, []>("first_19_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_19_pad_0 = const()[name = tensor<string, []>("first_19_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_19_strides_0 = const()[name = tensor<string, []>("first_19_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_19_dilations_0 = const()[name = tensor<string, []>("first_19_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_19_groups_0 = const()[name = tensor<string, []>("first_19_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_6_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_6_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4180352)))];
            tensor<fp16, [128]> layer2_layer2_6_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_6_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4475328)))];
            tensor<fp16, [1, 128, 28, 28]> first_19_cast_fp16 = conv(bias = layer2_layer2_6_conv2_Conv_bias_to_fp16, dilations = first_19_dilations_0, groups = first_19_groups_0, pad = first_19_pad_0, pad_type = first_19_pad_type_0, strides = first_19_strides_0, weight = layer2_layer2_6_conv2_Conv_weight_to_fp16, x = input_59_cast_fp16)[name = tensor<string, []>("first_19_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_61_cast_fp16 = add(x = first_19_cast_fp16, y = input_55_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_7_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_7_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4475648)))];
            tensor<fp16, [128]> layer2_layer2_7_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_7_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4475968)))];
            tensor<fp16, [128]> layer2_layer2_7_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_7_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4476288)))];
            tensor<fp16, [128]> layer2_layer2_7_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_7_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4476608)))];
            tensor<fp16, []> var_669_to_fp16 = const()[name = tensor<string, []>("op_669_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_63_cast_fp16 = batch_norm(beta = layer2_layer2_7_bn1_BatchNormalization_bias_to_fp16, epsilon = var_669_to_fp16, gamma = layer2_layer2_7_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_7_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_7_bn1_BatchNormalization_running_var_to_fp16, x = input_61_cast_fp16)[name = tensor<string, []>("input_63_cast_fp16")];
            tensor<string, []> input_tensor_23_pad_type_0 = const()[name = tensor<string, []>("input_tensor_23_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_23_pad_0 = const()[name = tensor<string, []>("input_tensor_23_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_23_strides_0 = const()[name = tensor<string, []>("input_tensor_23_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_23_dilations_0 = const()[name = tensor<string, []>("input_tensor_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_23_groups_0 = const()[name = tensor<string, []>("input_tensor_23_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_7_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_7_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4476928)))];
            tensor<fp16, [128]> layer2_layer2_7_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_7_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4771904)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_23_cast_fp16 = conv(bias = layer2_layer2_7_conv1_Conv_bias_to_fp16, dilations = input_tensor_23_dilations_0, groups = input_tensor_23_groups_0, pad = input_tensor_23_pad_0, pad_type = input_tensor_23_pad_type_0, strides = input_tensor_23_strides_0, weight = layer2_layer2_7_conv1_Conv_weight_to_fp16, x = input_63_cast_fp16)[name = tensor<string, []>("input_tensor_23_cast_fp16")];
            tensor<fp32, [128]> input_65_alpha_0 = const()[name = tensor<string, []>("input_65_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4772224)))];
            tensor<fp16, [1, 128, 28, 28]> input_65_cast_fp16 = prelu(alpha = input_65_alpha_0, x = input_tensor_23_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")];
            tensor<string, []> first_21_pad_type_0 = const()[name = tensor<string, []>("first_21_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_21_pad_0 = const()[name = tensor<string, []>("first_21_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_21_strides_0 = const()[name = tensor<string, []>("first_21_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_21_dilations_0 = const()[name = tensor<string, []>("first_21_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_21_groups_0 = const()[name = tensor<string, []>("first_21_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_7_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_7_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4772800)))];
            tensor<fp16, [128]> layer2_layer2_7_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_7_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5067776)))];
            tensor<fp16, [1, 128, 28, 28]> first_21_cast_fp16 = conv(bias = layer2_layer2_7_conv2_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = layer2_layer2_7_conv2_Conv_weight_to_fp16, x = input_65_cast_fp16)[name = tensor<string, []>("first_21_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_67_cast_fp16 = add(x = first_21_cast_fp16, y = input_61_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_8_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_8_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5068096)))];
            tensor<fp16, [128]> layer2_layer2_8_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_8_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5068416)))];
            tensor<fp16, [128]> layer2_layer2_8_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_8_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5068736)))];
            tensor<fp16, [128]> layer2_layer2_8_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_8_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5069056)))];
            tensor<fp16, []> var_706_to_fp16 = const()[name = tensor<string, []>("op_706_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_69_cast_fp16 = batch_norm(beta = layer2_layer2_8_bn1_BatchNormalization_bias_to_fp16, epsilon = var_706_to_fp16, gamma = layer2_layer2_8_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_8_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_8_bn1_BatchNormalization_running_var_to_fp16, x = input_67_cast_fp16)[name = tensor<string, []>("input_69_cast_fp16")];
            tensor<string, []> input_tensor_25_pad_type_0 = const()[name = tensor<string, []>("input_tensor_25_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_25_pad_0 = const()[name = tensor<string, []>("input_tensor_25_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_25_strides_0 = const()[name = tensor<string, []>("input_tensor_25_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_25_dilations_0 = const()[name = tensor<string, []>("input_tensor_25_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_25_groups_0 = const()[name = tensor<string, []>("input_tensor_25_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_8_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_8_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5069376)))];
            tensor<fp16, [128]> layer2_layer2_8_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_8_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5364352)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_25_cast_fp16 = conv(bias = layer2_layer2_8_conv1_Conv_bias_to_fp16, dilations = input_tensor_25_dilations_0, groups = input_tensor_25_groups_0, pad = input_tensor_25_pad_0, pad_type = input_tensor_25_pad_type_0, strides = input_tensor_25_strides_0, weight = layer2_layer2_8_conv1_Conv_weight_to_fp16, x = input_69_cast_fp16)[name = tensor<string, []>("input_tensor_25_cast_fp16")];
            tensor<fp32, [128]> input_71_alpha_0 = const()[name = tensor<string, []>("input_71_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5364672)))];
            tensor<fp16, [1, 128, 28, 28]> input_71_cast_fp16 = prelu(alpha = input_71_alpha_0, x = input_tensor_25_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
            tensor<string, []> first_23_pad_type_0 = const()[name = tensor<string, []>("first_23_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_23_pad_0 = const()[name = tensor<string, []>("first_23_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_23_strides_0 = const()[name = tensor<string, []>("first_23_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_23_dilations_0 = const()[name = tensor<string, []>("first_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_23_groups_0 = const()[name = tensor<string, []>("first_23_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_8_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_8_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5365248)))];
            tensor<fp16, [128]> layer2_layer2_8_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_8_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5660224)))];
            tensor<fp16, [1, 128, 28, 28]> first_23_cast_fp16 = conv(bias = layer2_layer2_8_conv2_Conv_bias_to_fp16, dilations = first_23_dilations_0, groups = first_23_groups_0, pad = first_23_pad_0, pad_type = first_23_pad_type_0, strides = first_23_strides_0, weight = layer2_layer2_8_conv2_Conv_weight_to_fp16, x = input_71_cast_fp16)[name = tensor<string, []>("first_23_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_73_cast_fp16 = add(x = first_23_cast_fp16, y = input_67_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_9_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_9_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5660544)))];
            tensor<fp16, [128]> layer2_layer2_9_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_9_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5660864)))];
            tensor<fp16, [128]> layer2_layer2_9_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_9_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5661184)))];
            tensor<fp16, [128]> layer2_layer2_9_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_9_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5661504)))];
            tensor<fp16, []> var_743_to_fp16 = const()[name = tensor<string, []>("op_743_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_75_cast_fp16 = batch_norm(beta = layer2_layer2_9_bn1_BatchNormalization_bias_to_fp16, epsilon = var_743_to_fp16, gamma = layer2_layer2_9_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_9_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_9_bn1_BatchNormalization_running_var_to_fp16, x = input_73_cast_fp16)[name = tensor<string, []>("input_75_cast_fp16")];
            tensor<string, []> input_tensor_27_pad_type_0 = const()[name = tensor<string, []>("input_tensor_27_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_27_pad_0 = const()[name = tensor<string, []>("input_tensor_27_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_27_strides_0 = const()[name = tensor<string, []>("input_tensor_27_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_27_dilations_0 = const()[name = tensor<string, []>("input_tensor_27_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_27_groups_0 = const()[name = tensor<string, []>("input_tensor_27_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_9_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_9_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5661824)))];
            tensor<fp16, [128]> layer2_layer2_9_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_9_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5956800)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_27_cast_fp16 = conv(bias = layer2_layer2_9_conv1_Conv_bias_to_fp16, dilations = input_tensor_27_dilations_0, groups = input_tensor_27_groups_0, pad = input_tensor_27_pad_0, pad_type = input_tensor_27_pad_type_0, strides = input_tensor_27_strides_0, weight = layer2_layer2_9_conv1_Conv_weight_to_fp16, x = input_75_cast_fp16)[name = tensor<string, []>("input_tensor_27_cast_fp16")];
            tensor<fp32, [128]> input_77_alpha_0 = const()[name = tensor<string, []>("input_77_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5957120)))];
            tensor<fp16, [1, 128, 28, 28]> input_77_cast_fp16 = prelu(alpha = input_77_alpha_0, x = input_tensor_27_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
            tensor<string, []> first_25_pad_type_0 = const()[name = tensor<string, []>("first_25_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_25_pad_0 = const()[name = tensor<string, []>("first_25_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_25_strides_0 = const()[name = tensor<string, []>("first_25_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_25_dilations_0 = const()[name = tensor<string, []>("first_25_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_25_groups_0 = const()[name = tensor<string, []>("first_25_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_9_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_9_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5957696)))];
            tensor<fp16, [128]> layer2_layer2_9_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_9_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6252672)))];
            tensor<fp16, [1, 128, 28, 28]> first_25_cast_fp16 = conv(bias = layer2_layer2_9_conv2_Conv_bias_to_fp16, dilations = first_25_dilations_0, groups = first_25_groups_0, pad = first_25_pad_0, pad_type = first_25_pad_type_0, strides = first_25_strides_0, weight = layer2_layer2_9_conv2_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = tensor<string, []>("first_25_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_79_cast_fp16 = add(x = first_25_cast_fp16, y = input_73_cast_fp16)[name = tensor<string, []>("input_79_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_10_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_10_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6252992)))];
            tensor<fp16, [128]> layer2_layer2_10_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_10_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6253312)))];
            tensor<fp16, [128]> layer2_layer2_10_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_10_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6253632)))];
            tensor<fp16, [128]> layer2_layer2_10_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_10_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6253952)))];
            tensor<fp16, []> var_780_to_fp16 = const()[name = tensor<string, []>("op_780_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_81_cast_fp16 = batch_norm(beta = layer2_layer2_10_bn1_BatchNormalization_bias_to_fp16, epsilon = var_780_to_fp16, gamma = layer2_layer2_10_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_10_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_10_bn1_BatchNormalization_running_var_to_fp16, x = input_79_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")];
            tensor<string, []> input_tensor_29_pad_type_0 = const()[name = tensor<string, []>("input_tensor_29_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_29_pad_0 = const()[name = tensor<string, []>("input_tensor_29_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_29_strides_0 = const()[name = tensor<string, []>("input_tensor_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_29_dilations_0 = const()[name = tensor<string, []>("input_tensor_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_29_groups_0 = const()[name = tensor<string, []>("input_tensor_29_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_10_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_10_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6254272)))];
            tensor<fp16, [128]> layer2_layer2_10_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_10_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6549248)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_29_cast_fp16 = conv(bias = layer2_layer2_10_conv1_Conv_bias_to_fp16, dilations = input_tensor_29_dilations_0, groups = input_tensor_29_groups_0, pad = input_tensor_29_pad_0, pad_type = input_tensor_29_pad_type_0, strides = input_tensor_29_strides_0, weight = layer2_layer2_10_conv1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = tensor<string, []>("input_tensor_29_cast_fp16")];
            tensor<fp32, [128]> input_83_alpha_0 = const()[name = tensor<string, []>("input_83_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6549568)))];
            tensor<fp16, [1, 128, 28, 28]> input_83_cast_fp16 = prelu(alpha = input_83_alpha_0, x = input_tensor_29_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")];
            tensor<string, []> first_27_pad_type_0 = const()[name = tensor<string, []>("first_27_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_27_pad_0 = const()[name = tensor<string, []>("first_27_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_27_strides_0 = const()[name = tensor<string, []>("first_27_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_27_dilations_0 = const()[name = tensor<string, []>("first_27_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_27_groups_0 = const()[name = tensor<string, []>("first_27_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_10_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_10_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6550144)))];
            tensor<fp16, [128]> layer2_layer2_10_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_10_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6845120)))];
            tensor<fp16, [1, 128, 28, 28]> first_27_cast_fp16 = conv(bias = layer2_layer2_10_conv2_Conv_bias_to_fp16, dilations = first_27_dilations_0, groups = first_27_groups_0, pad = first_27_pad_0, pad_type = first_27_pad_type_0, strides = first_27_strides_0, weight = layer2_layer2_10_conv2_Conv_weight_to_fp16, x = input_83_cast_fp16)[name = tensor<string, []>("first_27_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_85_cast_fp16 = add(x = first_27_cast_fp16, y = input_79_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_11_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_11_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6845440)))];
            tensor<fp16, [128]> layer2_layer2_11_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_11_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6845760)))];
            tensor<fp16, [128]> layer2_layer2_11_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_11_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6846080)))];
            tensor<fp16, [128]> layer2_layer2_11_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_11_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6846400)))];
            tensor<fp16, []> var_817_to_fp16 = const()[name = tensor<string, []>("op_817_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_87_cast_fp16 = batch_norm(beta = layer2_layer2_11_bn1_BatchNormalization_bias_to_fp16, epsilon = var_817_to_fp16, gamma = layer2_layer2_11_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_11_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_11_bn1_BatchNormalization_running_var_to_fp16, x = input_85_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")];
            tensor<string, []> input_tensor_31_pad_type_0 = const()[name = tensor<string, []>("input_tensor_31_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_31_pad_0 = const()[name = tensor<string, []>("input_tensor_31_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_31_strides_0 = const()[name = tensor<string, []>("input_tensor_31_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_31_dilations_0 = const()[name = tensor<string, []>("input_tensor_31_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_31_groups_0 = const()[name = tensor<string, []>("input_tensor_31_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_11_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_11_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6846720)))];
            tensor<fp16, [128]> layer2_layer2_11_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_11_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7141696)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_31_cast_fp16 = conv(bias = layer2_layer2_11_conv1_Conv_bias_to_fp16, dilations = input_tensor_31_dilations_0, groups = input_tensor_31_groups_0, pad = input_tensor_31_pad_0, pad_type = input_tensor_31_pad_type_0, strides = input_tensor_31_strides_0, weight = layer2_layer2_11_conv1_Conv_weight_to_fp16, x = input_87_cast_fp16)[name = tensor<string, []>("input_tensor_31_cast_fp16")];
            tensor<fp32, [128]> input_89_alpha_0 = const()[name = tensor<string, []>("input_89_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7142016)))];
            tensor<fp16, [1, 128, 28, 28]> input_89_cast_fp16 = prelu(alpha = input_89_alpha_0, x = input_tensor_31_cast_fp16)[name = tensor<string, []>("input_89_cast_fp16")];
            tensor<string, []> first_29_pad_type_0 = const()[name = tensor<string, []>("first_29_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_29_pad_0 = const()[name = tensor<string, []>("first_29_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_29_strides_0 = const()[name = tensor<string, []>("first_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_29_dilations_0 = const()[name = tensor<string, []>("first_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_29_groups_0 = const()[name = tensor<string, []>("first_29_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_11_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_11_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7142592)))];
            tensor<fp16, [128]> layer2_layer2_11_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_11_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7437568)))];
            tensor<fp16, [1, 128, 28, 28]> first_29_cast_fp16 = conv(bias = layer2_layer2_11_conv2_Conv_bias_to_fp16, dilations = first_29_dilations_0, groups = first_29_groups_0, pad = first_29_pad_0, pad_type = first_29_pad_type_0, strides = first_29_strides_0, weight = layer2_layer2_11_conv2_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = tensor<string, []>("first_29_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_91_cast_fp16 = add(x = first_29_cast_fp16, y = input_85_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")];
            tensor<fp16, [128]> layer2_layer2_12_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_12_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7437888)))];
            tensor<fp16, [128]> layer2_layer2_12_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_12_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7438208)))];
            tensor<fp16, [128]> layer2_layer2_12_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_12_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7438528)))];
            tensor<fp16, [128]> layer2_layer2_12_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_12_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7438848)))];
            tensor<fp16, []> var_854_to_fp16 = const()[name = tensor<string, []>("op_854_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_93_cast_fp16 = batch_norm(beta = layer2_layer2_12_bn1_BatchNormalization_bias_to_fp16, epsilon = var_854_to_fp16, gamma = layer2_layer2_12_bn1_BatchNormalization_weight_to_fp16, mean = layer2_layer2_12_bn1_BatchNormalization_running_mean_to_fp16, variance = layer2_layer2_12_bn1_BatchNormalization_running_var_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("input_93_cast_fp16")];
            tensor<string, []> input_tensor_33_pad_type_0 = const()[name = tensor<string, []>("input_tensor_33_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_33_pad_0 = const()[name = tensor<string, []>("input_tensor_33_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_33_strides_0 = const()[name = tensor<string, []>("input_tensor_33_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_33_dilations_0 = const()[name = tensor<string, []>("input_tensor_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_33_groups_0 = const()[name = tensor<string, []>("input_tensor_33_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_12_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_12_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7439168)))];
            tensor<fp16, [128]> layer2_layer2_12_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_12_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7734144)))];
            tensor<fp16, [1, 128, 28, 28]> input_tensor_33_cast_fp16 = conv(bias = layer2_layer2_12_conv1_Conv_bias_to_fp16, dilations = input_tensor_33_dilations_0, groups = input_tensor_33_groups_0, pad = input_tensor_33_pad_0, pad_type = input_tensor_33_pad_type_0, strides = input_tensor_33_strides_0, weight = layer2_layer2_12_conv1_Conv_weight_to_fp16, x = input_93_cast_fp16)[name = tensor<string, []>("input_tensor_33_cast_fp16")];
            tensor<fp32, [128]> input_95_alpha_0 = const()[name = tensor<string, []>("input_95_alpha_0"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7734464)))];
            tensor<fp16, [1, 128, 28, 28]> input_95_cast_fp16 = prelu(alpha = input_95_alpha_0, x = input_tensor_33_cast_fp16)[name = tensor<string, []>("input_95_cast_fp16")];
            tensor<string, []> first_31_pad_type_0 = const()[name = tensor<string, []>("first_31_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_31_pad_0 = const()[name = tensor<string, []>("first_31_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_31_strides_0 = const()[name = tensor<string, []>("first_31_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_31_dilations_0 = const()[name = tensor<string, []>("first_31_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_31_groups_0 = const()[name = tensor<string, []>("first_31_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 3, 3]> layer2_layer2_12_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_12_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7735040)))];
            tensor<fp16, [128]> layer2_layer2_12_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer2_layer2_12_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8030016)))];
            tensor<fp16, [1, 128, 28, 28]> first_31_cast_fp16 = conv(bias = layer2_layer2_12_conv2_Conv_bias_to_fp16, dilations = first_31_dilations_0, groups = first_31_groups_0, pad = first_31_pad_0, pad_type = first_31_pad_type_0, strides = first_31_strides_0, weight = layer2_layer2_12_conv2_Conv_weight_to_fp16, x = input_95_cast_fp16)[name = tensor<string, []>("first_31_cast_fp16")];
            tensor<fp16, [1, 128, 28, 28]> input_97_cast_fp16 = add(x = first_31_cast_fp16, y = input_91_cast_fp16)[name = tensor<string, []>("input_97_cast_fp16")];
            tensor<fp16, [128]> layer3_layer3_0_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8030336)))];
            tensor<fp16, [128]> layer3_layer3_0_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8030656)))];
            tensor<fp16, [128]> layer3_layer3_0_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8030976)))];
            tensor<fp16, [128]> layer3_layer3_0_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8031296)))];
            tensor<fp16, []> var_891_to_fp16 = const()[name = tensor<string, []>("op_891_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, 28, 28]> input_99_cast_fp16 = batch_norm(beta = layer3_layer3_0_bn1_BatchNormalization_bias_to_fp16, epsilon = var_891_to_fp16, gamma = layer3_layer3_0_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_0_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_0_bn1_BatchNormalization_running_var_to_fp16, x = input_97_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")];
            tensor<string, []> input_tensor_35_pad_type_0 = const()[name = tensor<string, []>("input_tensor_35_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_35_pad_0 = const()[name = tensor<string, []>("input_tensor_35_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_35_strides_0 = const()[name = tensor<string, []>("input_tensor_35_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_35_dilations_0 = const()[name = tensor<string, []>("input_tensor_35_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_35_groups_0 = const()[name = tensor<string, []>("input_tensor_35_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 128, 3, 3]> layer3_layer3_0_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8031616)))];
            tensor<fp16, [256]> layer3_layer3_0_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8621504)))];
            tensor<fp16, [1, 256, 28, 28]> input_tensor_35_cast_fp16 = conv(bias = layer3_layer3_0_conv1_Conv_bias_to_fp16, dilations = input_tensor_35_dilations_0, groups = input_tensor_35_groups_0, pad = input_tensor_35_pad_0, pad_type = input_tensor_35_pad_type_0, strides = input_tensor_35_strides_0, weight = layer3_layer3_0_conv1_Conv_weight_to_fp16, x = input_99_cast_fp16)[name = tensor<string, []>("input_tensor_35_cast_fp16")];
            tensor<fp32, [256]> input_101_alpha_0 = const()[name = tensor<string, []>("input_101_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8622080)))];
            tensor<fp16, [1, 256, 28, 28]> input_101_cast_fp16 = prelu(alpha = input_101_alpha_0, x = input_tensor_35_cast_fp16)[name = tensor<string, []>("input_101_cast_fp16")];
            tensor<string, []> first_33_pad_type_0 = const()[name = tensor<string, []>("first_33_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_33_pad_0 = const()[name = tensor<string, []>("first_33_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_33_strides_0 = const()[name = tensor<string, []>("first_33_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> first_33_dilations_0 = const()[name = tensor<string, []>("first_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_33_groups_0 = const()[name = tensor<string, []>("first_33_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_0_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8623168)))];
            tensor<fp16, [256]> layer3_layer3_0_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9802880)))];
            tensor<fp16, [1, 256, 14, 14]> first_33_cast_fp16 = conv(bias = layer3_layer3_0_conv2_Conv_bias_to_fp16, dilations = first_33_dilations_0, groups = first_33_groups_0, pad = first_33_pad_0, pad_type = first_33_pad_type_0, strides = first_33_strides_0, weight = layer3_layer3_0_conv2_Conv_weight_to_fp16, x = input_101_cast_fp16)[name = tensor<string, []>("first_33_cast_fp16")];
            tensor<string, []> second_5_pad_type_0 = const()[name = tensor<string, []>("second_5_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> second_5_strides_0 = const()[name = tensor<string, []>("second_5_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> second_5_pad_0 = const()[name = tensor<string, []>("second_5_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> second_5_dilations_0 = const()[name = tensor<string, []>("second_5_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> second_5_groups_0 = const()[name = tensor<string, []>("second_5_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 128, 1, 1]> layer3_layer3_0_downsample_downsample_0_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_downsample_downsample_0_Conv_weight_to_fp16"), val = tensor<fp16, [256, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9803456)))];
            tensor<fp16, [256]> layer3_layer3_0_downsample_downsample_0_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_0_downsample_downsample_0_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9869056)))];
            tensor<fp16, [1, 256, 14, 14]> second_5_cast_fp16 = conv(bias = layer3_layer3_0_downsample_downsample_0_Conv_bias_to_fp16, dilations = second_5_dilations_0, groups = second_5_groups_0, pad = second_5_pad_0, pad_type = second_5_pad_type_0, strides = second_5_strides_0, weight = layer3_layer3_0_downsample_downsample_0_Conv_weight_to_fp16, x = input_97_cast_fp16)[name = tensor<string, []>("second_5_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_103_cast_fp16 = add(x = first_33_cast_fp16, y = second_5_cast_fp16)[name = tensor<string, []>("input_103_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_1_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_1_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9869632)))];
            tensor<fp16, [256]> layer3_layer3_1_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_1_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9870208)))];
            tensor<fp16, [256]> layer3_layer3_1_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_1_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9870784)))];
            tensor<fp16, [256]> layer3_layer3_1_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_1_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9871360)))];
            tensor<fp16, []> var_941_to_fp16 = const()[name = tensor<string, []>("op_941_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_105_cast_fp16 = batch_norm(beta = layer3_layer3_1_bn1_BatchNormalization_bias_to_fp16, epsilon = var_941_to_fp16, gamma = layer3_layer3_1_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_1_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_1_bn1_BatchNormalization_running_var_to_fp16, x = input_103_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")];
            tensor<string, []> input_tensor_37_pad_type_0 = const()[name = tensor<string, []>("input_tensor_37_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_37_pad_0 = const()[name = tensor<string, []>("input_tensor_37_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_37_strides_0 = const()[name = tensor<string, []>("input_tensor_37_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_37_dilations_0 = const()[name = tensor<string, []>("input_tensor_37_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_37_groups_0 = const()[name = tensor<string, []>("input_tensor_37_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_1_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_1_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9871936)))];
            tensor<fp16, [256]> layer3_layer3_1_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_1_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11051648)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_37_cast_fp16 = conv(bias = layer3_layer3_1_conv1_Conv_bias_to_fp16, dilations = input_tensor_37_dilations_0, groups = input_tensor_37_groups_0, pad = input_tensor_37_pad_0, pad_type = input_tensor_37_pad_type_0, strides = input_tensor_37_strides_0, weight = layer3_layer3_1_conv1_Conv_weight_to_fp16, x = input_105_cast_fp16)[name = tensor<string, []>("input_tensor_37_cast_fp16")];
            tensor<fp32, [256]> input_107_alpha_0 = const()[name = tensor<string, []>("input_107_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11052224)))];
            tensor<fp16, [1, 256, 14, 14]> input_107_cast_fp16 = prelu(alpha = input_107_alpha_0, x = input_tensor_37_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")];
            tensor<string, []> first_35_pad_type_0 = const()[name = tensor<string, []>("first_35_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_35_pad_0 = const()[name = tensor<string, []>("first_35_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_35_strides_0 = const()[name = tensor<string, []>("first_35_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_35_dilations_0 = const()[name = tensor<string, []>("first_35_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_35_groups_0 = const()[name = tensor<string, []>("first_35_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_1_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_1_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11053312)))];
            tensor<fp16, [256]> layer3_layer3_1_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_1_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12233024)))];
            tensor<fp16, [1, 256, 14, 14]> first_35_cast_fp16 = conv(bias = layer3_layer3_1_conv2_Conv_bias_to_fp16, dilations = first_35_dilations_0, groups = first_35_groups_0, pad = first_35_pad_0, pad_type = first_35_pad_type_0, strides = first_35_strides_0, weight = layer3_layer3_1_conv2_Conv_weight_to_fp16, x = input_107_cast_fp16)[name = tensor<string, []>("first_35_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_109_cast_fp16 = add(x = first_35_cast_fp16, y = input_103_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_2_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_2_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12233600)))];
            tensor<fp16, [256]> layer3_layer3_2_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_2_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12234176)))];
            tensor<fp16, [256]> layer3_layer3_2_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_2_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12234752)))];
            tensor<fp16, [256]> layer3_layer3_2_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_2_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12235328)))];
            tensor<fp16, []> var_978_to_fp16 = const()[name = tensor<string, []>("op_978_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_111_cast_fp16 = batch_norm(beta = layer3_layer3_2_bn1_BatchNormalization_bias_to_fp16, epsilon = var_978_to_fp16, gamma = layer3_layer3_2_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_2_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_2_bn1_BatchNormalization_running_var_to_fp16, x = input_109_cast_fp16)[name = tensor<string, []>("input_111_cast_fp16")];
            tensor<string, []> input_tensor_39_pad_type_0 = const()[name = tensor<string, []>("input_tensor_39_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_39_pad_0 = const()[name = tensor<string, []>("input_tensor_39_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_39_strides_0 = const()[name = tensor<string, []>("input_tensor_39_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_39_dilations_0 = const()[name = tensor<string, []>("input_tensor_39_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_39_groups_0 = const()[name = tensor<string, []>("input_tensor_39_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_2_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_2_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12235904)))];
            tensor<fp16, [256]> layer3_layer3_2_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_2_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13415616)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_39_cast_fp16 = conv(bias = layer3_layer3_2_conv1_Conv_bias_to_fp16, dilations = input_tensor_39_dilations_0, groups = input_tensor_39_groups_0, pad = input_tensor_39_pad_0, pad_type = input_tensor_39_pad_type_0, strides = input_tensor_39_strides_0, weight = layer3_layer3_2_conv1_Conv_weight_to_fp16, x = input_111_cast_fp16)[name = tensor<string, []>("input_tensor_39_cast_fp16")];
            tensor<fp32, [256]> input_113_alpha_0 = const()[name = tensor<string, []>("input_113_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13416192)))];
            tensor<fp16, [1, 256, 14, 14]> input_113_cast_fp16 = prelu(alpha = input_113_alpha_0, x = input_tensor_39_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")];
            tensor<string, []> first_37_pad_type_0 = const()[name = tensor<string, []>("first_37_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_37_pad_0 = const()[name = tensor<string, []>("first_37_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_37_strides_0 = const()[name = tensor<string, []>("first_37_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_37_dilations_0 = const()[name = tensor<string, []>("first_37_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_37_groups_0 = const()[name = tensor<string, []>("first_37_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_2_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_2_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13417280)))];
            tensor<fp16, [256]> layer3_layer3_2_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_2_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14596992)))];
            tensor<fp16, [1, 256, 14, 14]> first_37_cast_fp16 = conv(bias = layer3_layer3_2_conv2_Conv_bias_to_fp16, dilations = first_37_dilations_0, groups = first_37_groups_0, pad = first_37_pad_0, pad_type = first_37_pad_type_0, strides = first_37_strides_0, weight = layer3_layer3_2_conv2_Conv_weight_to_fp16, x = input_113_cast_fp16)[name = tensor<string, []>("first_37_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_115_cast_fp16 = add(x = first_37_cast_fp16, y = input_109_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_3_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_3_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14597568)))];
            tensor<fp16, [256]> layer3_layer3_3_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_3_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14598144)))];
            tensor<fp16, [256]> layer3_layer3_3_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_3_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14598720)))];
            tensor<fp16, [256]> layer3_layer3_3_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_3_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14599296)))];
            tensor<fp16, []> var_1015_to_fp16 = const()[name = tensor<string, []>("op_1015_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_117_cast_fp16 = batch_norm(beta = layer3_layer3_3_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1015_to_fp16, gamma = layer3_layer3_3_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_3_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_3_bn1_BatchNormalization_running_var_to_fp16, x = input_115_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")];
            tensor<string, []> input_tensor_41_pad_type_0 = const()[name = tensor<string, []>("input_tensor_41_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_41_pad_0 = const()[name = tensor<string, []>("input_tensor_41_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_41_strides_0 = const()[name = tensor<string, []>("input_tensor_41_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_41_dilations_0 = const()[name = tensor<string, []>("input_tensor_41_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_41_groups_0 = const()[name = tensor<string, []>("input_tensor_41_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_3_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_3_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14599872)))];
            tensor<fp16, [256]> layer3_layer3_3_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_3_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15779584)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_41_cast_fp16 = conv(bias = layer3_layer3_3_conv1_Conv_bias_to_fp16, dilations = input_tensor_41_dilations_0, groups = input_tensor_41_groups_0, pad = input_tensor_41_pad_0, pad_type = input_tensor_41_pad_type_0, strides = input_tensor_41_strides_0, weight = layer3_layer3_3_conv1_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = tensor<string, []>("input_tensor_41_cast_fp16")];
            tensor<fp32, [256]> input_119_alpha_0 = const()[name = tensor<string, []>("input_119_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15780160)))];
            tensor<fp16, [1, 256, 14, 14]> input_119_cast_fp16 = prelu(alpha = input_119_alpha_0, x = input_tensor_41_cast_fp16)[name = tensor<string, []>("input_119_cast_fp16")];
            tensor<string, []> first_39_pad_type_0 = const()[name = tensor<string, []>("first_39_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_39_pad_0 = const()[name = tensor<string, []>("first_39_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_39_strides_0 = const()[name = tensor<string, []>("first_39_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_39_dilations_0 = const()[name = tensor<string, []>("first_39_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_39_groups_0 = const()[name = tensor<string, []>("first_39_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_3_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_3_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15781248)))];
            tensor<fp16, [256]> layer3_layer3_3_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_3_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16960960)))];
            tensor<fp16, [1, 256, 14, 14]> first_39_cast_fp16 = conv(bias = layer3_layer3_3_conv2_Conv_bias_to_fp16, dilations = first_39_dilations_0, groups = first_39_groups_0, pad = first_39_pad_0, pad_type = first_39_pad_type_0, strides = first_39_strides_0, weight = layer3_layer3_3_conv2_Conv_weight_to_fp16, x = input_119_cast_fp16)[name = tensor<string, []>("first_39_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_121_cast_fp16 = add(x = first_39_cast_fp16, y = input_115_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_4_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_4_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16961536)))];
            tensor<fp16, [256]> layer3_layer3_4_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_4_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16962112)))];
            tensor<fp16, [256]> layer3_layer3_4_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_4_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16962688)))];
            tensor<fp16, [256]> layer3_layer3_4_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_4_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16963264)))];
            tensor<fp16, []> var_1052_to_fp16 = const()[name = tensor<string, []>("op_1052_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_123_cast_fp16 = batch_norm(beta = layer3_layer3_4_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1052_to_fp16, gamma = layer3_layer3_4_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_4_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_4_bn1_BatchNormalization_running_var_to_fp16, x = input_121_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")];
            tensor<string, []> input_tensor_43_pad_type_0 = const()[name = tensor<string, []>("input_tensor_43_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_43_pad_0 = const()[name = tensor<string, []>("input_tensor_43_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_43_strides_0 = const()[name = tensor<string, []>("input_tensor_43_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_43_dilations_0 = const()[name = tensor<string, []>("input_tensor_43_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_43_groups_0 = const()[name = tensor<string, []>("input_tensor_43_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_4_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_4_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16963840)))];
            tensor<fp16, [256]> layer3_layer3_4_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_4_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18143552)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_43_cast_fp16 = conv(bias = layer3_layer3_4_conv1_Conv_bias_to_fp16, dilations = input_tensor_43_dilations_0, groups = input_tensor_43_groups_0, pad = input_tensor_43_pad_0, pad_type = input_tensor_43_pad_type_0, strides = input_tensor_43_strides_0, weight = layer3_layer3_4_conv1_Conv_weight_to_fp16, x = input_123_cast_fp16)[name = tensor<string, []>("input_tensor_43_cast_fp16")];
            tensor<fp32, [256]> input_125_alpha_0 = const()[name = tensor<string, []>("input_125_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18144128)))];
            tensor<fp16, [1, 256, 14, 14]> input_125_cast_fp16 = prelu(alpha = input_125_alpha_0, x = input_tensor_43_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")];
            tensor<string, []> first_41_pad_type_0 = const()[name = tensor<string, []>("first_41_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_41_pad_0 = const()[name = tensor<string, []>("first_41_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_41_strides_0 = const()[name = tensor<string, []>("first_41_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_41_dilations_0 = const()[name = tensor<string, []>("first_41_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_41_groups_0 = const()[name = tensor<string, []>("first_41_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_4_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_4_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18145216)))];
            tensor<fp16, [256]> layer3_layer3_4_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_4_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19324928)))];
            tensor<fp16, [1, 256, 14, 14]> first_41_cast_fp16 = conv(bias = layer3_layer3_4_conv2_Conv_bias_to_fp16, dilations = first_41_dilations_0, groups = first_41_groups_0, pad = first_41_pad_0, pad_type = first_41_pad_type_0, strides = first_41_strides_0, weight = layer3_layer3_4_conv2_Conv_weight_to_fp16, x = input_125_cast_fp16)[name = tensor<string, []>("first_41_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_127_cast_fp16 = add(x = first_41_cast_fp16, y = input_121_cast_fp16)[name = tensor<string, []>("input_127_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_5_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_5_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19325504)))];
            tensor<fp16, [256]> layer3_layer3_5_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_5_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19326080)))];
            tensor<fp16, [256]> layer3_layer3_5_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_5_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19326656)))];
            tensor<fp16, [256]> layer3_layer3_5_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_5_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19327232)))];
            tensor<fp16, []> var_1089_to_fp16 = const()[name = tensor<string, []>("op_1089_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_129_cast_fp16 = batch_norm(beta = layer3_layer3_5_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1089_to_fp16, gamma = layer3_layer3_5_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_5_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_5_bn1_BatchNormalization_running_var_to_fp16, x = input_127_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")];
            tensor<string, []> input_tensor_45_pad_type_0 = const()[name = tensor<string, []>("input_tensor_45_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_45_pad_0 = const()[name = tensor<string, []>("input_tensor_45_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_45_strides_0 = const()[name = tensor<string, []>("input_tensor_45_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_45_dilations_0 = const()[name = tensor<string, []>("input_tensor_45_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_45_groups_0 = const()[name = tensor<string, []>("input_tensor_45_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_5_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_5_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19327808)))];
            tensor<fp16, [256]> layer3_layer3_5_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_5_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20507520)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_45_cast_fp16 = conv(bias = layer3_layer3_5_conv1_Conv_bias_to_fp16, dilations = input_tensor_45_dilations_0, groups = input_tensor_45_groups_0, pad = input_tensor_45_pad_0, pad_type = input_tensor_45_pad_type_0, strides = input_tensor_45_strides_0, weight = layer3_layer3_5_conv1_Conv_weight_to_fp16, x = input_129_cast_fp16)[name = tensor<string, []>("input_tensor_45_cast_fp16")];
            tensor<fp32, [256]> input_131_alpha_0 = const()[name = tensor<string, []>("input_131_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20508096)))];
            tensor<fp16, [1, 256, 14, 14]> input_131_cast_fp16 = prelu(alpha = input_131_alpha_0, x = input_tensor_45_cast_fp16)[name = tensor<string, []>("input_131_cast_fp16")];
            tensor<string, []> first_43_pad_type_0 = const()[name = tensor<string, []>("first_43_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_43_pad_0 = const()[name = tensor<string, []>("first_43_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_43_strides_0 = const()[name = tensor<string, []>("first_43_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_43_dilations_0 = const()[name = tensor<string, []>("first_43_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_43_groups_0 = const()[name = tensor<string, []>("first_43_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_5_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_5_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20509184)))];
            tensor<fp16, [256]> layer3_layer3_5_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_5_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21688896)))];
            tensor<fp16, [1, 256, 14, 14]> first_43_cast_fp16 = conv(bias = layer3_layer3_5_conv2_Conv_bias_to_fp16, dilations = first_43_dilations_0, groups = first_43_groups_0, pad = first_43_pad_0, pad_type = first_43_pad_type_0, strides = first_43_strides_0, weight = layer3_layer3_5_conv2_Conv_weight_to_fp16, x = input_131_cast_fp16)[name = tensor<string, []>("first_43_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_133_cast_fp16 = add(x = first_43_cast_fp16, y = input_127_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_6_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_6_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21689472)))];
            tensor<fp16, [256]> layer3_layer3_6_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_6_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21690048)))];
            tensor<fp16, [256]> layer3_layer3_6_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_6_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21690624)))];
            tensor<fp16, [256]> layer3_layer3_6_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_6_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21691200)))];
            tensor<fp16, []> var_1126_to_fp16 = const()[name = tensor<string, []>("op_1126_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_135_cast_fp16 = batch_norm(beta = layer3_layer3_6_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1126_to_fp16, gamma = layer3_layer3_6_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_6_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_6_bn1_BatchNormalization_running_var_to_fp16, x = input_133_cast_fp16)[name = tensor<string, []>("input_135_cast_fp16")];
            tensor<string, []> input_tensor_47_pad_type_0 = const()[name = tensor<string, []>("input_tensor_47_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_47_pad_0 = const()[name = tensor<string, []>("input_tensor_47_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_47_strides_0 = const()[name = tensor<string, []>("input_tensor_47_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_47_dilations_0 = const()[name = tensor<string, []>("input_tensor_47_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_47_groups_0 = const()[name = tensor<string, []>("input_tensor_47_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_6_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_6_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21691776)))];
            tensor<fp16, [256]> layer3_layer3_6_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_6_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22871488)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_47_cast_fp16 = conv(bias = layer3_layer3_6_conv1_Conv_bias_to_fp16, dilations = input_tensor_47_dilations_0, groups = input_tensor_47_groups_0, pad = input_tensor_47_pad_0, pad_type = input_tensor_47_pad_type_0, strides = input_tensor_47_strides_0, weight = layer3_layer3_6_conv1_Conv_weight_to_fp16, x = input_135_cast_fp16)[name = tensor<string, []>("input_tensor_47_cast_fp16")];
            tensor<fp32, [256]> input_137_alpha_0 = const()[name = tensor<string, []>("input_137_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22872064)))];
            tensor<fp16, [1, 256, 14, 14]> input_137_cast_fp16 = prelu(alpha = input_137_alpha_0, x = input_tensor_47_cast_fp16)[name = tensor<string, []>("input_137_cast_fp16")];
            tensor<string, []> first_45_pad_type_0 = const()[name = tensor<string, []>("first_45_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_45_pad_0 = const()[name = tensor<string, []>("first_45_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_45_strides_0 = const()[name = tensor<string, []>("first_45_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_45_dilations_0 = const()[name = tensor<string, []>("first_45_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_45_groups_0 = const()[name = tensor<string, []>("first_45_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_6_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_6_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22873152)))];
            tensor<fp16, [256]> layer3_layer3_6_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_6_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24052864)))];
            tensor<fp16, [1, 256, 14, 14]> first_45_cast_fp16 = conv(bias = layer3_layer3_6_conv2_Conv_bias_to_fp16, dilations = first_45_dilations_0, groups = first_45_groups_0, pad = first_45_pad_0, pad_type = first_45_pad_type_0, strides = first_45_strides_0, weight = layer3_layer3_6_conv2_Conv_weight_to_fp16, x = input_137_cast_fp16)[name = tensor<string, []>("first_45_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_139_cast_fp16 = add(x = first_45_cast_fp16, y = input_133_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_7_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_7_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24053440)))];
            tensor<fp16, [256]> layer3_layer3_7_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_7_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24054016)))];
            tensor<fp16, [256]> layer3_layer3_7_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_7_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24054592)))];
            tensor<fp16, [256]> layer3_layer3_7_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_7_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24055168)))];
            tensor<fp16, []> var_1163_to_fp16 = const()[name = tensor<string, []>("op_1163_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_141_cast_fp16 = batch_norm(beta = layer3_layer3_7_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1163_to_fp16, gamma = layer3_layer3_7_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_7_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_7_bn1_BatchNormalization_running_var_to_fp16, x = input_139_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")];
            tensor<string, []> input_tensor_49_pad_type_0 = const()[name = tensor<string, []>("input_tensor_49_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_49_pad_0 = const()[name = tensor<string, []>("input_tensor_49_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_49_strides_0 = const()[name = tensor<string, []>("input_tensor_49_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_49_dilations_0 = const()[name = tensor<string, []>("input_tensor_49_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_49_groups_0 = const()[name = tensor<string, []>("input_tensor_49_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_7_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_7_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24055744)))];
            tensor<fp16, [256]> layer3_layer3_7_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_7_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25235456)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_49_cast_fp16 = conv(bias = layer3_layer3_7_conv1_Conv_bias_to_fp16, dilations = input_tensor_49_dilations_0, groups = input_tensor_49_groups_0, pad = input_tensor_49_pad_0, pad_type = input_tensor_49_pad_type_0, strides = input_tensor_49_strides_0, weight = layer3_layer3_7_conv1_Conv_weight_to_fp16, x = input_141_cast_fp16)[name = tensor<string, []>("input_tensor_49_cast_fp16")];
            tensor<fp32, [256]> input_143_alpha_0 = const()[name = tensor<string, []>("input_143_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25236032)))];
            tensor<fp16, [1, 256, 14, 14]> input_143_cast_fp16 = prelu(alpha = input_143_alpha_0, x = input_tensor_49_cast_fp16)[name = tensor<string, []>("input_143_cast_fp16")];
            tensor<string, []> first_47_pad_type_0 = const()[name = tensor<string, []>("first_47_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_47_pad_0 = const()[name = tensor<string, []>("first_47_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_47_strides_0 = const()[name = tensor<string, []>("first_47_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_47_dilations_0 = const()[name = tensor<string, []>("first_47_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_47_groups_0 = const()[name = tensor<string, []>("first_47_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_7_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_7_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25237120)))];
            tensor<fp16, [256]> layer3_layer3_7_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_7_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26416832)))];
            tensor<fp16, [1, 256, 14, 14]> first_47_cast_fp16 = conv(bias = layer3_layer3_7_conv2_Conv_bias_to_fp16, dilations = first_47_dilations_0, groups = first_47_groups_0, pad = first_47_pad_0, pad_type = first_47_pad_type_0, strides = first_47_strides_0, weight = layer3_layer3_7_conv2_Conv_weight_to_fp16, x = input_143_cast_fp16)[name = tensor<string, []>("first_47_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_145_cast_fp16 = add(x = first_47_cast_fp16, y = input_139_cast_fp16)[name = tensor<string, []>("input_145_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_8_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_8_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26417408)))];
            tensor<fp16, [256]> layer3_layer3_8_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_8_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26417984)))];
            tensor<fp16, [256]> layer3_layer3_8_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_8_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26418560)))];
            tensor<fp16, [256]> layer3_layer3_8_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_8_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26419136)))];
            tensor<fp16, []> var_1200_to_fp16 = const()[name = tensor<string, []>("op_1200_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_147_cast_fp16 = batch_norm(beta = layer3_layer3_8_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1200_to_fp16, gamma = layer3_layer3_8_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_8_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_8_bn1_BatchNormalization_running_var_to_fp16, x = input_145_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")];
            tensor<string, []> input_tensor_51_pad_type_0 = const()[name = tensor<string, []>("input_tensor_51_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_51_pad_0 = const()[name = tensor<string, []>("input_tensor_51_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_51_strides_0 = const()[name = tensor<string, []>("input_tensor_51_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_51_dilations_0 = const()[name = tensor<string, []>("input_tensor_51_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_51_groups_0 = const()[name = tensor<string, []>("input_tensor_51_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_8_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_8_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26419712)))];
            tensor<fp16, [256]> layer3_layer3_8_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_8_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27599424)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_51_cast_fp16 = conv(bias = layer3_layer3_8_conv1_Conv_bias_to_fp16, dilations = input_tensor_51_dilations_0, groups = input_tensor_51_groups_0, pad = input_tensor_51_pad_0, pad_type = input_tensor_51_pad_type_0, strides = input_tensor_51_strides_0, weight = layer3_layer3_8_conv1_Conv_weight_to_fp16, x = input_147_cast_fp16)[name = tensor<string, []>("input_tensor_51_cast_fp16")];
            tensor<fp32, [256]> input_149_alpha_0 = const()[name = tensor<string, []>("input_149_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27600000)))];
            tensor<fp16, [1, 256, 14, 14]> input_149_cast_fp16 = prelu(alpha = input_149_alpha_0, x = input_tensor_51_cast_fp16)[name = tensor<string, []>("input_149_cast_fp16")];
            tensor<string, []> first_49_pad_type_0 = const()[name = tensor<string, []>("first_49_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_49_pad_0 = const()[name = tensor<string, []>("first_49_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_49_strides_0 = const()[name = tensor<string, []>("first_49_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_49_dilations_0 = const()[name = tensor<string, []>("first_49_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_49_groups_0 = const()[name = tensor<string, []>("first_49_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_8_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_8_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27601088)))];
            tensor<fp16, [256]> layer3_layer3_8_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_8_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28780800)))];
            tensor<fp16, [1, 256, 14, 14]> first_49_cast_fp16 = conv(bias = layer3_layer3_8_conv2_Conv_bias_to_fp16, dilations = first_49_dilations_0, groups = first_49_groups_0, pad = first_49_pad_0, pad_type = first_49_pad_type_0, strides = first_49_strides_0, weight = layer3_layer3_8_conv2_Conv_weight_to_fp16, x = input_149_cast_fp16)[name = tensor<string, []>("first_49_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_151_cast_fp16 = add(x = first_49_cast_fp16, y = input_145_cast_fp16)[name = tensor<string, []>("input_151_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_9_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_9_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28781376)))];
            tensor<fp16, [256]> layer3_layer3_9_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_9_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28781952)))];
            tensor<fp16, [256]> layer3_layer3_9_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_9_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28782528)))];
            tensor<fp16, [256]> layer3_layer3_9_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_9_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28783104)))];
            tensor<fp16, []> var_1237_to_fp16 = const()[name = tensor<string, []>("op_1237_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_153_cast_fp16 = batch_norm(beta = layer3_layer3_9_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1237_to_fp16, gamma = layer3_layer3_9_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_9_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_9_bn1_BatchNormalization_running_var_to_fp16, x = input_151_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")];
            tensor<string, []> input_tensor_53_pad_type_0 = const()[name = tensor<string, []>("input_tensor_53_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_53_pad_0 = const()[name = tensor<string, []>("input_tensor_53_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_53_strides_0 = const()[name = tensor<string, []>("input_tensor_53_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_53_dilations_0 = const()[name = tensor<string, []>("input_tensor_53_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_53_groups_0 = const()[name = tensor<string, []>("input_tensor_53_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_9_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_9_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28783680)))];
            tensor<fp16, [256]> layer3_layer3_9_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_9_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29963392)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_53_cast_fp16 = conv(bias = layer3_layer3_9_conv1_Conv_bias_to_fp16, dilations = input_tensor_53_dilations_0, groups = input_tensor_53_groups_0, pad = input_tensor_53_pad_0, pad_type = input_tensor_53_pad_type_0, strides = input_tensor_53_strides_0, weight = layer3_layer3_9_conv1_Conv_weight_to_fp16, x = input_153_cast_fp16)[name = tensor<string, []>("input_tensor_53_cast_fp16")];
            tensor<fp32, [256]> input_155_alpha_0 = const()[name = tensor<string, []>("input_155_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29963968)))];
            tensor<fp16, [1, 256, 14, 14]> input_155_cast_fp16 = prelu(alpha = input_155_alpha_0, x = input_tensor_53_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")];
            tensor<string, []> first_51_pad_type_0 = const()[name = tensor<string, []>("first_51_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_51_pad_0 = const()[name = tensor<string, []>("first_51_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_51_strides_0 = const()[name = tensor<string, []>("first_51_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_51_dilations_0 = const()[name = tensor<string, []>("first_51_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_51_groups_0 = const()[name = tensor<string, []>("first_51_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_9_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_9_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29965056)))];
            tensor<fp16, [256]> layer3_layer3_9_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_9_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31144768)))];
            tensor<fp16, [1, 256, 14, 14]> first_51_cast_fp16 = conv(bias = layer3_layer3_9_conv2_Conv_bias_to_fp16, dilations = first_51_dilations_0, groups = first_51_groups_0, pad = first_51_pad_0, pad_type = first_51_pad_type_0, strides = first_51_strides_0, weight = layer3_layer3_9_conv2_Conv_weight_to_fp16, x = input_155_cast_fp16)[name = tensor<string, []>("first_51_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_157_cast_fp16 = add(x = first_51_cast_fp16, y = input_151_cast_fp16)[name = tensor<string, []>("input_157_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_10_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_10_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31145344)))];
            tensor<fp16, [256]> layer3_layer3_10_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_10_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31145920)))];
            tensor<fp16, [256]> layer3_layer3_10_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_10_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31146496)))];
            tensor<fp16, [256]> layer3_layer3_10_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_10_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31147072)))];
            tensor<fp16, []> var_1274_to_fp16 = const()[name = tensor<string, []>("op_1274_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_159_cast_fp16 = batch_norm(beta = layer3_layer3_10_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1274_to_fp16, gamma = layer3_layer3_10_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_10_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_10_bn1_BatchNormalization_running_var_to_fp16, x = input_157_cast_fp16)[name = tensor<string, []>("input_159_cast_fp16")];
            tensor<string, []> input_tensor_55_pad_type_0 = const()[name = tensor<string, []>("input_tensor_55_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_55_pad_0 = const()[name = tensor<string, []>("input_tensor_55_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_55_strides_0 = const()[name = tensor<string, []>("input_tensor_55_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_55_dilations_0 = const()[name = tensor<string, []>("input_tensor_55_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_55_groups_0 = const()[name = tensor<string, []>("input_tensor_55_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_10_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_10_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31147648)))];
            tensor<fp16, [256]> layer3_layer3_10_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_10_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32327360)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_55_cast_fp16 = conv(bias = layer3_layer3_10_conv1_Conv_bias_to_fp16, dilations = input_tensor_55_dilations_0, groups = input_tensor_55_groups_0, pad = input_tensor_55_pad_0, pad_type = input_tensor_55_pad_type_0, strides = input_tensor_55_strides_0, weight = layer3_layer3_10_conv1_Conv_weight_to_fp16, x = input_159_cast_fp16)[name = tensor<string, []>("input_tensor_55_cast_fp16")];
            tensor<fp32, [256]> input_161_alpha_0 = const()[name = tensor<string, []>("input_161_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32327936)))];
            tensor<fp16, [1, 256, 14, 14]> input_161_cast_fp16 = prelu(alpha = input_161_alpha_0, x = input_tensor_55_cast_fp16)[name = tensor<string, []>("input_161_cast_fp16")];
            tensor<string, []> first_53_pad_type_0 = const()[name = tensor<string, []>("first_53_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_53_pad_0 = const()[name = tensor<string, []>("first_53_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_53_strides_0 = const()[name = tensor<string, []>("first_53_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_53_dilations_0 = const()[name = tensor<string, []>("first_53_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_53_groups_0 = const()[name = tensor<string, []>("first_53_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_10_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_10_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32329024)))];
            tensor<fp16, [256]> layer3_layer3_10_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_10_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33508736)))];
            tensor<fp16, [1, 256, 14, 14]> first_53_cast_fp16 = conv(bias = layer3_layer3_10_conv2_Conv_bias_to_fp16, dilations = first_53_dilations_0, groups = first_53_groups_0, pad = first_53_pad_0, pad_type = first_53_pad_type_0, strides = first_53_strides_0, weight = layer3_layer3_10_conv2_Conv_weight_to_fp16, x = input_161_cast_fp16)[name = tensor<string, []>("first_53_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_163_cast_fp16 = add(x = first_53_cast_fp16, y = input_157_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_11_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_11_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33509312)))];
            tensor<fp16, [256]> layer3_layer3_11_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_11_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33509888)))];
            tensor<fp16, [256]> layer3_layer3_11_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_11_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33510464)))];
            tensor<fp16, [256]> layer3_layer3_11_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_11_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33511040)))];
            tensor<fp16, []> var_1311_to_fp16 = const()[name = tensor<string, []>("op_1311_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_165_cast_fp16 = batch_norm(beta = layer3_layer3_11_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1311_to_fp16, gamma = layer3_layer3_11_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_11_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_11_bn1_BatchNormalization_running_var_to_fp16, x = input_163_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")];
            tensor<string, []> input_tensor_57_pad_type_0 = const()[name = tensor<string, []>("input_tensor_57_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_57_pad_0 = const()[name = tensor<string, []>("input_tensor_57_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_57_strides_0 = const()[name = tensor<string, []>("input_tensor_57_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_57_dilations_0 = const()[name = tensor<string, []>("input_tensor_57_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_57_groups_0 = const()[name = tensor<string, []>("input_tensor_57_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_11_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_11_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33511616)))];
            tensor<fp16, [256]> layer3_layer3_11_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_11_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34691328)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_57_cast_fp16 = conv(bias = layer3_layer3_11_conv1_Conv_bias_to_fp16, dilations = input_tensor_57_dilations_0, groups = input_tensor_57_groups_0, pad = input_tensor_57_pad_0, pad_type = input_tensor_57_pad_type_0, strides = input_tensor_57_strides_0, weight = layer3_layer3_11_conv1_Conv_weight_to_fp16, x = input_165_cast_fp16)[name = tensor<string, []>("input_tensor_57_cast_fp16")];
            tensor<fp32, [256]> input_167_alpha_0 = const()[name = tensor<string, []>("input_167_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34691904)))];
            tensor<fp16, [1, 256, 14, 14]> input_167_cast_fp16 = prelu(alpha = input_167_alpha_0, x = input_tensor_57_cast_fp16)[name = tensor<string, []>("input_167_cast_fp16")];
            tensor<string, []> first_55_pad_type_0 = const()[name = tensor<string, []>("first_55_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_55_pad_0 = const()[name = tensor<string, []>("first_55_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_55_strides_0 = const()[name = tensor<string, []>("first_55_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_55_dilations_0 = const()[name = tensor<string, []>("first_55_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_55_groups_0 = const()[name = tensor<string, []>("first_55_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_11_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_11_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34692992)))];
            tensor<fp16, [256]> layer3_layer3_11_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_11_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35872704)))];
            tensor<fp16, [1, 256, 14, 14]> first_55_cast_fp16 = conv(bias = layer3_layer3_11_conv2_Conv_bias_to_fp16, dilations = first_55_dilations_0, groups = first_55_groups_0, pad = first_55_pad_0, pad_type = first_55_pad_type_0, strides = first_55_strides_0, weight = layer3_layer3_11_conv2_Conv_weight_to_fp16, x = input_167_cast_fp16)[name = tensor<string, []>("first_55_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_169_cast_fp16 = add(x = first_55_cast_fp16, y = input_163_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_12_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_12_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35873280)))];
            tensor<fp16, [256]> layer3_layer3_12_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_12_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35873856)))];
            tensor<fp16, [256]> layer3_layer3_12_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_12_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35874432)))];
            tensor<fp16, [256]> layer3_layer3_12_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_12_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35875008)))];
            tensor<fp16, []> var_1348_to_fp16 = const()[name = tensor<string, []>("op_1348_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_171_cast_fp16 = batch_norm(beta = layer3_layer3_12_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1348_to_fp16, gamma = layer3_layer3_12_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_12_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_12_bn1_BatchNormalization_running_var_to_fp16, x = input_169_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")];
            tensor<string, []> input_tensor_59_pad_type_0 = const()[name = tensor<string, []>("input_tensor_59_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_59_pad_0 = const()[name = tensor<string, []>("input_tensor_59_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_59_strides_0 = const()[name = tensor<string, []>("input_tensor_59_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_59_dilations_0 = const()[name = tensor<string, []>("input_tensor_59_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_59_groups_0 = const()[name = tensor<string, []>("input_tensor_59_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_12_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_12_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35875584)))];
            tensor<fp16, [256]> layer3_layer3_12_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_12_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37055296)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_59_cast_fp16 = conv(bias = layer3_layer3_12_conv1_Conv_bias_to_fp16, dilations = input_tensor_59_dilations_0, groups = input_tensor_59_groups_0, pad = input_tensor_59_pad_0, pad_type = input_tensor_59_pad_type_0, strides = input_tensor_59_strides_0, weight = layer3_layer3_12_conv1_Conv_weight_to_fp16, x = input_171_cast_fp16)[name = tensor<string, []>("input_tensor_59_cast_fp16")];
            tensor<fp32, [256]> input_173_alpha_0 = const()[name = tensor<string, []>("input_173_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37055872)))];
            tensor<fp16, [1, 256, 14, 14]> input_173_cast_fp16 = prelu(alpha = input_173_alpha_0, x = input_tensor_59_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")];
            tensor<string, []> first_57_pad_type_0 = const()[name = tensor<string, []>("first_57_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_57_pad_0 = const()[name = tensor<string, []>("first_57_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_57_strides_0 = const()[name = tensor<string, []>("first_57_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_57_dilations_0 = const()[name = tensor<string, []>("first_57_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_57_groups_0 = const()[name = tensor<string, []>("first_57_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_12_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_12_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37056960)))];
            tensor<fp16, [256]> layer3_layer3_12_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_12_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38236672)))];
            tensor<fp16, [1, 256, 14, 14]> first_57_cast_fp16 = conv(bias = layer3_layer3_12_conv2_Conv_bias_to_fp16, dilations = first_57_dilations_0, groups = first_57_groups_0, pad = first_57_pad_0, pad_type = first_57_pad_type_0, strides = first_57_strides_0, weight = layer3_layer3_12_conv2_Conv_weight_to_fp16, x = input_173_cast_fp16)[name = tensor<string, []>("first_57_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_175_cast_fp16 = add(x = first_57_cast_fp16, y = input_169_cast_fp16)[name = tensor<string, []>("input_175_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_13_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_13_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38237248)))];
            tensor<fp16, [256]> layer3_layer3_13_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_13_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38237824)))];
            tensor<fp16, [256]> layer3_layer3_13_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_13_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38238400)))];
            tensor<fp16, [256]> layer3_layer3_13_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_13_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38238976)))];
            tensor<fp16, []> var_1385_to_fp16 = const()[name = tensor<string, []>("op_1385_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_177_cast_fp16 = batch_norm(beta = layer3_layer3_13_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1385_to_fp16, gamma = layer3_layer3_13_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_13_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_13_bn1_BatchNormalization_running_var_to_fp16, x = input_175_cast_fp16)[name = tensor<string, []>("input_177_cast_fp16")];
            tensor<string, []> input_tensor_61_pad_type_0 = const()[name = tensor<string, []>("input_tensor_61_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_61_pad_0 = const()[name = tensor<string, []>("input_tensor_61_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_61_strides_0 = const()[name = tensor<string, []>("input_tensor_61_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_61_dilations_0 = const()[name = tensor<string, []>("input_tensor_61_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_61_groups_0 = const()[name = tensor<string, []>("input_tensor_61_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_13_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_13_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38239552)))];
            tensor<fp16, [256]> layer3_layer3_13_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_13_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39419264)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_61_cast_fp16 = conv(bias = layer3_layer3_13_conv1_Conv_bias_to_fp16, dilations = input_tensor_61_dilations_0, groups = input_tensor_61_groups_0, pad = input_tensor_61_pad_0, pad_type = input_tensor_61_pad_type_0, strides = input_tensor_61_strides_0, weight = layer3_layer3_13_conv1_Conv_weight_to_fp16, x = input_177_cast_fp16)[name = tensor<string, []>("input_tensor_61_cast_fp16")];
            tensor<fp32, [256]> input_179_alpha_0 = const()[name = tensor<string, []>("input_179_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39419840)))];
            tensor<fp16, [1, 256, 14, 14]> input_179_cast_fp16 = prelu(alpha = input_179_alpha_0, x = input_tensor_61_cast_fp16)[name = tensor<string, []>("input_179_cast_fp16")];
            tensor<string, []> first_59_pad_type_0 = const()[name = tensor<string, []>("first_59_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_59_pad_0 = const()[name = tensor<string, []>("first_59_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_59_strides_0 = const()[name = tensor<string, []>("first_59_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_59_dilations_0 = const()[name = tensor<string, []>("first_59_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_59_groups_0 = const()[name = tensor<string, []>("first_59_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_13_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_13_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39420928)))];
            tensor<fp16, [256]> layer3_layer3_13_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_13_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40600640)))];
            tensor<fp16, [1, 256, 14, 14]> first_59_cast_fp16 = conv(bias = layer3_layer3_13_conv2_Conv_bias_to_fp16, dilations = first_59_dilations_0, groups = first_59_groups_0, pad = first_59_pad_0, pad_type = first_59_pad_type_0, strides = first_59_strides_0, weight = layer3_layer3_13_conv2_Conv_weight_to_fp16, x = input_179_cast_fp16)[name = tensor<string, []>("first_59_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_181_cast_fp16 = add(x = first_59_cast_fp16, y = input_175_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_14_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_14_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40601216)))];
            tensor<fp16, [256]> layer3_layer3_14_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_14_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40601792)))];
            tensor<fp16, [256]> layer3_layer3_14_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_14_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40602368)))];
            tensor<fp16, [256]> layer3_layer3_14_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_14_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40602944)))];
            tensor<fp16, []> var_1422_to_fp16 = const()[name = tensor<string, []>("op_1422_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_183_cast_fp16 = batch_norm(beta = layer3_layer3_14_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1422_to_fp16, gamma = layer3_layer3_14_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_14_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_14_bn1_BatchNormalization_running_var_to_fp16, x = input_181_cast_fp16)[name = tensor<string, []>("input_183_cast_fp16")];
            tensor<string, []> input_tensor_63_pad_type_0 = const()[name = tensor<string, []>("input_tensor_63_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_63_pad_0 = const()[name = tensor<string, []>("input_tensor_63_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_63_strides_0 = const()[name = tensor<string, []>("input_tensor_63_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_63_dilations_0 = const()[name = tensor<string, []>("input_tensor_63_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_63_groups_0 = const()[name = tensor<string, []>("input_tensor_63_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_14_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_14_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40603520)))];
            tensor<fp16, [256]> layer3_layer3_14_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_14_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41783232)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_63_cast_fp16 = conv(bias = layer3_layer3_14_conv1_Conv_bias_to_fp16, dilations = input_tensor_63_dilations_0, groups = input_tensor_63_groups_0, pad = input_tensor_63_pad_0, pad_type = input_tensor_63_pad_type_0, strides = input_tensor_63_strides_0, weight = layer3_layer3_14_conv1_Conv_weight_to_fp16, x = input_183_cast_fp16)[name = tensor<string, []>("input_tensor_63_cast_fp16")];
            tensor<fp32, [256]> input_185_alpha_0 = const()[name = tensor<string, []>("input_185_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41783808)))];
            tensor<fp16, [1, 256, 14, 14]> input_185_cast_fp16 = prelu(alpha = input_185_alpha_0, x = input_tensor_63_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")];
            tensor<string, []> first_61_pad_type_0 = const()[name = tensor<string, []>("first_61_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_61_pad_0 = const()[name = tensor<string, []>("first_61_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_61_strides_0 = const()[name = tensor<string, []>("first_61_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_61_dilations_0 = const()[name = tensor<string, []>("first_61_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_61_groups_0 = const()[name = tensor<string, []>("first_61_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_14_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_14_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41784896)))];
            tensor<fp16, [256]> layer3_layer3_14_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_14_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42964608)))];
            tensor<fp16, [1, 256, 14, 14]> first_61_cast_fp16 = conv(bias = layer3_layer3_14_conv2_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = layer3_layer3_14_conv2_Conv_weight_to_fp16, x = input_185_cast_fp16)[name = tensor<string, []>("first_61_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_187_cast_fp16 = add(x = first_61_cast_fp16, y = input_181_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_15_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_15_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42965184)))];
            tensor<fp16, [256]> layer3_layer3_15_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_15_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42965760)))];
            tensor<fp16, [256]> layer3_layer3_15_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_15_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42966336)))];
            tensor<fp16, [256]> layer3_layer3_15_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_15_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42966912)))];
            tensor<fp16, []> var_1459_to_fp16 = const()[name = tensor<string, []>("op_1459_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_189_cast_fp16 = batch_norm(beta = layer3_layer3_15_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1459_to_fp16, gamma = layer3_layer3_15_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_15_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_15_bn1_BatchNormalization_running_var_to_fp16, x = input_187_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")];
            tensor<string, []> input_tensor_65_pad_type_0 = const()[name = tensor<string, []>("input_tensor_65_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_65_pad_0 = const()[name = tensor<string, []>("input_tensor_65_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_65_strides_0 = const()[name = tensor<string, []>("input_tensor_65_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_65_dilations_0 = const()[name = tensor<string, []>("input_tensor_65_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_65_groups_0 = const()[name = tensor<string, []>("input_tensor_65_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_15_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_15_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42967488)))];
            tensor<fp16, [256]> layer3_layer3_15_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_15_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44147200)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_65_cast_fp16 = conv(bias = layer3_layer3_15_conv1_Conv_bias_to_fp16, dilations = input_tensor_65_dilations_0, groups = input_tensor_65_groups_0, pad = input_tensor_65_pad_0, pad_type = input_tensor_65_pad_type_0, strides = input_tensor_65_strides_0, weight = layer3_layer3_15_conv1_Conv_weight_to_fp16, x = input_189_cast_fp16)[name = tensor<string, []>("input_tensor_65_cast_fp16")];
            tensor<fp32, [256]> input_191_alpha_0 = const()[name = tensor<string, []>("input_191_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44147776)))];
            tensor<fp16, [1, 256, 14, 14]> input_191_cast_fp16 = prelu(alpha = input_191_alpha_0, x = input_tensor_65_cast_fp16)[name = tensor<string, []>("input_191_cast_fp16")];
            tensor<string, []> first_63_pad_type_0 = const()[name = tensor<string, []>("first_63_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_63_pad_0 = const()[name = tensor<string, []>("first_63_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_63_strides_0 = const()[name = tensor<string, []>("first_63_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_63_dilations_0 = const()[name = tensor<string, []>("first_63_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_63_groups_0 = const()[name = tensor<string, []>("first_63_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_15_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_15_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44148864)))];
            tensor<fp16, [256]> layer3_layer3_15_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_15_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45328576)))];
            tensor<fp16, [1, 256, 14, 14]> first_63_cast_fp16 = conv(bias = layer3_layer3_15_conv2_Conv_bias_to_fp16, dilations = first_63_dilations_0, groups = first_63_groups_0, pad = first_63_pad_0, pad_type = first_63_pad_type_0, strides = first_63_strides_0, weight = layer3_layer3_15_conv2_Conv_weight_to_fp16, x = input_191_cast_fp16)[name = tensor<string, []>("first_63_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_193_cast_fp16 = add(x = first_63_cast_fp16, y = input_187_cast_fp16)[name = tensor<string, []>("input_193_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_16_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_16_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45329152)))];
            tensor<fp16, [256]> layer3_layer3_16_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_16_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45329728)))];
            tensor<fp16, [256]> layer3_layer3_16_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_16_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45330304)))];
            tensor<fp16, [256]> layer3_layer3_16_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_16_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45330880)))];
            tensor<fp16, []> var_1496_to_fp16 = const()[name = tensor<string, []>("op_1496_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_195_cast_fp16 = batch_norm(beta = layer3_layer3_16_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1496_to_fp16, gamma = layer3_layer3_16_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_16_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_16_bn1_BatchNormalization_running_var_to_fp16, x = input_193_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
            tensor<string, []> input_tensor_67_pad_type_0 = const()[name = tensor<string, []>("input_tensor_67_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_67_pad_0 = const()[name = tensor<string, []>("input_tensor_67_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_67_strides_0 = const()[name = tensor<string, []>("input_tensor_67_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_67_dilations_0 = const()[name = tensor<string, []>("input_tensor_67_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_67_groups_0 = const()[name = tensor<string, []>("input_tensor_67_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_16_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_16_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45331456)))];
            tensor<fp16, [256]> layer3_layer3_16_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_16_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46511168)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_67_cast_fp16 = conv(bias = layer3_layer3_16_conv1_Conv_bias_to_fp16, dilations = input_tensor_67_dilations_0, groups = input_tensor_67_groups_0, pad = input_tensor_67_pad_0, pad_type = input_tensor_67_pad_type_0, strides = input_tensor_67_strides_0, weight = layer3_layer3_16_conv1_Conv_weight_to_fp16, x = input_195_cast_fp16)[name = tensor<string, []>("input_tensor_67_cast_fp16")];
            tensor<fp32, [256]> input_197_alpha_0 = const()[name = tensor<string, []>("input_197_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46511744)))];
            tensor<fp16, [1, 256, 14, 14]> input_197_cast_fp16 = prelu(alpha = input_197_alpha_0, x = input_tensor_67_cast_fp16)[name = tensor<string, []>("input_197_cast_fp16")];
            tensor<string, []> first_65_pad_type_0 = const()[name = tensor<string, []>("first_65_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_65_pad_0 = const()[name = tensor<string, []>("first_65_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_65_strides_0 = const()[name = tensor<string, []>("first_65_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_65_dilations_0 = const()[name = tensor<string, []>("first_65_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_65_groups_0 = const()[name = tensor<string, []>("first_65_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_16_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_16_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46512832)))];
            tensor<fp16, [256]> layer3_layer3_16_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_16_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47692544)))];
            tensor<fp16, [1, 256, 14, 14]> first_65_cast_fp16 = conv(bias = layer3_layer3_16_conv2_Conv_bias_to_fp16, dilations = first_65_dilations_0, groups = first_65_groups_0, pad = first_65_pad_0, pad_type = first_65_pad_type_0, strides = first_65_strides_0, weight = layer3_layer3_16_conv2_Conv_weight_to_fp16, x = input_197_cast_fp16)[name = tensor<string, []>("first_65_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_199_cast_fp16 = add(x = first_65_cast_fp16, y = input_193_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_17_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_17_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47693120)))];
            tensor<fp16, [256]> layer3_layer3_17_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_17_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47693696)))];
            tensor<fp16, [256]> layer3_layer3_17_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_17_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47694272)))];
            tensor<fp16, [256]> layer3_layer3_17_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_17_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47694848)))];
            tensor<fp16, []> var_1533_to_fp16 = const()[name = tensor<string, []>("op_1533_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_201_cast_fp16 = batch_norm(beta = layer3_layer3_17_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1533_to_fp16, gamma = layer3_layer3_17_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_17_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_17_bn1_BatchNormalization_running_var_to_fp16, x = input_199_cast_fp16)[name = tensor<string, []>("input_201_cast_fp16")];
            tensor<string, []> input_tensor_69_pad_type_0 = const()[name = tensor<string, []>("input_tensor_69_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_69_pad_0 = const()[name = tensor<string, []>("input_tensor_69_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_69_strides_0 = const()[name = tensor<string, []>("input_tensor_69_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_69_dilations_0 = const()[name = tensor<string, []>("input_tensor_69_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_69_groups_0 = const()[name = tensor<string, []>("input_tensor_69_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_17_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_17_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47695424)))];
            tensor<fp16, [256]> layer3_layer3_17_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_17_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48875136)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_69_cast_fp16 = conv(bias = layer3_layer3_17_conv1_Conv_bias_to_fp16, dilations = input_tensor_69_dilations_0, groups = input_tensor_69_groups_0, pad = input_tensor_69_pad_0, pad_type = input_tensor_69_pad_type_0, strides = input_tensor_69_strides_0, weight = layer3_layer3_17_conv1_Conv_weight_to_fp16, x = input_201_cast_fp16)[name = tensor<string, []>("input_tensor_69_cast_fp16")];
            tensor<fp32, [256]> input_203_alpha_0 = const()[name = tensor<string, []>("input_203_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48875712)))];
            tensor<fp16, [1, 256, 14, 14]> input_203_cast_fp16 = prelu(alpha = input_203_alpha_0, x = input_tensor_69_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
            tensor<string, []> first_67_pad_type_0 = const()[name = tensor<string, []>("first_67_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_67_pad_0 = const()[name = tensor<string, []>("first_67_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_67_strides_0 = const()[name = tensor<string, []>("first_67_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_67_dilations_0 = const()[name = tensor<string, []>("first_67_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_67_groups_0 = const()[name = tensor<string, []>("first_67_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_17_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_17_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48876800)))];
            tensor<fp16, [256]> layer3_layer3_17_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_17_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50056512)))];
            tensor<fp16, [1, 256, 14, 14]> first_67_cast_fp16 = conv(bias = layer3_layer3_17_conv2_Conv_bias_to_fp16, dilations = first_67_dilations_0, groups = first_67_groups_0, pad = first_67_pad_0, pad_type = first_67_pad_type_0, strides = first_67_strides_0, weight = layer3_layer3_17_conv2_Conv_weight_to_fp16, x = input_203_cast_fp16)[name = tensor<string, []>("first_67_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_205_cast_fp16 = add(x = first_67_cast_fp16, y = input_199_cast_fp16)[name = tensor<string, []>("input_205_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_18_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_18_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50057088)))];
            tensor<fp16, [256]> layer3_layer3_18_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_18_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50057664)))];
            tensor<fp16, [256]> layer3_layer3_18_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_18_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50058240)))];
            tensor<fp16, [256]> layer3_layer3_18_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_18_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50058816)))];
            tensor<fp16, []> var_1570_to_fp16 = const()[name = tensor<string, []>("op_1570_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_207_cast_fp16 = batch_norm(beta = layer3_layer3_18_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1570_to_fp16, gamma = layer3_layer3_18_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_18_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_18_bn1_BatchNormalization_running_var_to_fp16, x = input_205_cast_fp16)[name = tensor<string, []>("input_207_cast_fp16")];
            tensor<string, []> input_tensor_71_pad_type_0 = const()[name = tensor<string, []>("input_tensor_71_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_71_pad_0 = const()[name = tensor<string, []>("input_tensor_71_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_71_strides_0 = const()[name = tensor<string, []>("input_tensor_71_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_71_dilations_0 = const()[name = tensor<string, []>("input_tensor_71_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_71_groups_0 = const()[name = tensor<string, []>("input_tensor_71_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_18_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_18_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50059392)))];
            tensor<fp16, [256]> layer3_layer3_18_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_18_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51239104)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_71_cast_fp16 = conv(bias = layer3_layer3_18_conv1_Conv_bias_to_fp16, dilations = input_tensor_71_dilations_0, groups = input_tensor_71_groups_0, pad = input_tensor_71_pad_0, pad_type = input_tensor_71_pad_type_0, strides = input_tensor_71_strides_0, weight = layer3_layer3_18_conv1_Conv_weight_to_fp16, x = input_207_cast_fp16)[name = tensor<string, []>("input_tensor_71_cast_fp16")];
            tensor<fp32, [256]> input_209_alpha_0 = const()[name = tensor<string, []>("input_209_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51239680)))];
            tensor<fp16, [1, 256, 14, 14]> input_209_cast_fp16 = prelu(alpha = input_209_alpha_0, x = input_tensor_71_cast_fp16)[name = tensor<string, []>("input_209_cast_fp16")];
            tensor<string, []> first_69_pad_type_0 = const()[name = tensor<string, []>("first_69_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_69_pad_0 = const()[name = tensor<string, []>("first_69_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_69_strides_0 = const()[name = tensor<string, []>("first_69_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_69_dilations_0 = const()[name = tensor<string, []>("first_69_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_69_groups_0 = const()[name = tensor<string, []>("first_69_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_18_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_18_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51240768)))];
            tensor<fp16, [256]> layer3_layer3_18_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_18_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52420480)))];
            tensor<fp16, [1, 256, 14, 14]> first_69_cast_fp16 = conv(bias = layer3_layer3_18_conv2_Conv_bias_to_fp16, dilations = first_69_dilations_0, groups = first_69_groups_0, pad = first_69_pad_0, pad_type = first_69_pad_type_0, strides = first_69_strides_0, weight = layer3_layer3_18_conv2_Conv_weight_to_fp16, x = input_209_cast_fp16)[name = tensor<string, []>("first_69_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_211_cast_fp16 = add(x = first_69_cast_fp16, y = input_205_cast_fp16)[name = tensor<string, []>("input_211_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_19_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_19_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52421056)))];
            tensor<fp16, [256]> layer3_layer3_19_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_19_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52421632)))];
            tensor<fp16, [256]> layer3_layer3_19_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_19_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52422208)))];
            tensor<fp16, [256]> layer3_layer3_19_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_19_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52422784)))];
            tensor<fp16, []> var_1607_to_fp16 = const()[name = tensor<string, []>("op_1607_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_213_cast_fp16 = batch_norm(beta = layer3_layer3_19_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1607_to_fp16, gamma = layer3_layer3_19_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_19_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_19_bn1_BatchNormalization_running_var_to_fp16, x = input_211_cast_fp16)[name = tensor<string, []>("input_213_cast_fp16")];
            tensor<string, []> input_tensor_73_pad_type_0 = const()[name = tensor<string, []>("input_tensor_73_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_73_pad_0 = const()[name = tensor<string, []>("input_tensor_73_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_73_strides_0 = const()[name = tensor<string, []>("input_tensor_73_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_73_dilations_0 = const()[name = tensor<string, []>("input_tensor_73_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_73_groups_0 = const()[name = tensor<string, []>("input_tensor_73_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_19_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_19_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52423360)))];
            tensor<fp16, [256]> layer3_layer3_19_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_19_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53603072)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_73_cast_fp16 = conv(bias = layer3_layer3_19_conv1_Conv_bias_to_fp16, dilations = input_tensor_73_dilations_0, groups = input_tensor_73_groups_0, pad = input_tensor_73_pad_0, pad_type = input_tensor_73_pad_type_0, strides = input_tensor_73_strides_0, weight = layer3_layer3_19_conv1_Conv_weight_to_fp16, x = input_213_cast_fp16)[name = tensor<string, []>("input_tensor_73_cast_fp16")];
            tensor<fp32, [256]> input_215_alpha_0 = const()[name = tensor<string, []>("input_215_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53603648)))];
            tensor<fp16, [1, 256, 14, 14]> input_215_cast_fp16 = prelu(alpha = input_215_alpha_0, x = input_tensor_73_cast_fp16)[name = tensor<string, []>("input_215_cast_fp16")];
            tensor<string, []> first_71_pad_type_0 = const()[name = tensor<string, []>("first_71_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_71_pad_0 = const()[name = tensor<string, []>("first_71_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_71_strides_0 = const()[name = tensor<string, []>("first_71_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_71_dilations_0 = const()[name = tensor<string, []>("first_71_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_71_groups_0 = const()[name = tensor<string, []>("first_71_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_19_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_19_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53604736)))];
            tensor<fp16, [256]> layer3_layer3_19_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_19_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54784448)))];
            tensor<fp16, [1, 256, 14, 14]> first_71_cast_fp16 = conv(bias = layer3_layer3_19_conv2_Conv_bias_to_fp16, dilations = first_71_dilations_0, groups = first_71_groups_0, pad = first_71_pad_0, pad_type = first_71_pad_type_0, strides = first_71_strides_0, weight = layer3_layer3_19_conv2_Conv_weight_to_fp16, x = input_215_cast_fp16)[name = tensor<string, []>("first_71_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_217_cast_fp16 = add(x = first_71_cast_fp16, y = input_211_cast_fp16)[name = tensor<string, []>("input_217_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_20_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_20_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54785024)))];
            tensor<fp16, [256]> layer3_layer3_20_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_20_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54785600)))];
            tensor<fp16, [256]> layer3_layer3_20_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_20_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54786176)))];
            tensor<fp16, [256]> layer3_layer3_20_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_20_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54786752)))];
            tensor<fp16, []> var_1644_to_fp16 = const()[name = tensor<string, []>("op_1644_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_219_cast_fp16 = batch_norm(beta = layer3_layer3_20_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1644_to_fp16, gamma = layer3_layer3_20_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_20_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_20_bn1_BatchNormalization_running_var_to_fp16, x = input_217_cast_fp16)[name = tensor<string, []>("input_219_cast_fp16")];
            tensor<string, []> input_tensor_75_pad_type_0 = const()[name = tensor<string, []>("input_tensor_75_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_75_pad_0 = const()[name = tensor<string, []>("input_tensor_75_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_75_strides_0 = const()[name = tensor<string, []>("input_tensor_75_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_75_dilations_0 = const()[name = tensor<string, []>("input_tensor_75_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_75_groups_0 = const()[name = tensor<string, []>("input_tensor_75_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_20_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_20_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54787328)))];
            tensor<fp16, [256]> layer3_layer3_20_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_20_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(55967040)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_75_cast_fp16 = conv(bias = layer3_layer3_20_conv1_Conv_bias_to_fp16, dilations = input_tensor_75_dilations_0, groups = input_tensor_75_groups_0, pad = input_tensor_75_pad_0, pad_type = input_tensor_75_pad_type_0, strides = input_tensor_75_strides_0, weight = layer3_layer3_20_conv1_Conv_weight_to_fp16, x = input_219_cast_fp16)[name = tensor<string, []>("input_tensor_75_cast_fp16")];
            tensor<fp32, [256]> input_221_alpha_0 = const()[name = tensor<string, []>("input_221_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(55967616)))];
            tensor<fp16, [1, 256, 14, 14]> input_221_cast_fp16 = prelu(alpha = input_221_alpha_0, x = input_tensor_75_cast_fp16)[name = tensor<string, []>("input_221_cast_fp16")];
            tensor<string, []> first_73_pad_type_0 = const()[name = tensor<string, []>("first_73_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_73_pad_0 = const()[name = tensor<string, []>("first_73_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_73_strides_0 = const()[name = tensor<string, []>("first_73_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_73_dilations_0 = const()[name = tensor<string, []>("first_73_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_73_groups_0 = const()[name = tensor<string, []>("first_73_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_20_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_20_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(55968704)))];
            tensor<fp16, [256]> layer3_layer3_20_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_20_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57148416)))];
            tensor<fp16, [1, 256, 14, 14]> first_73_cast_fp16 = conv(bias = layer3_layer3_20_conv2_Conv_bias_to_fp16, dilations = first_73_dilations_0, groups = first_73_groups_0, pad = first_73_pad_0, pad_type = first_73_pad_type_0, strides = first_73_strides_0, weight = layer3_layer3_20_conv2_Conv_weight_to_fp16, x = input_221_cast_fp16)[name = tensor<string, []>("first_73_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_223_cast_fp16 = add(x = first_73_cast_fp16, y = input_217_cast_fp16)[name = tensor<string, []>("input_223_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_21_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_21_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57148992)))];
            tensor<fp16, [256]> layer3_layer3_21_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_21_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57149568)))];
            tensor<fp16, [256]> layer3_layer3_21_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_21_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57150144)))];
            tensor<fp16, [256]> layer3_layer3_21_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_21_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57150720)))];
            tensor<fp16, []> var_1681_to_fp16 = const()[name = tensor<string, []>("op_1681_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_225_cast_fp16 = batch_norm(beta = layer3_layer3_21_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1681_to_fp16, gamma = layer3_layer3_21_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_21_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_21_bn1_BatchNormalization_running_var_to_fp16, x = input_223_cast_fp16)[name = tensor<string, []>("input_225_cast_fp16")];
            tensor<string, []> input_tensor_77_pad_type_0 = const()[name = tensor<string, []>("input_tensor_77_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_77_pad_0 = const()[name = tensor<string, []>("input_tensor_77_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_77_strides_0 = const()[name = tensor<string, []>("input_tensor_77_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_77_dilations_0 = const()[name = tensor<string, []>("input_tensor_77_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_77_groups_0 = const()[name = tensor<string, []>("input_tensor_77_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_21_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_21_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57151296)))];
            tensor<fp16, [256]> layer3_layer3_21_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_21_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58331008)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_77_cast_fp16 = conv(bias = layer3_layer3_21_conv1_Conv_bias_to_fp16, dilations = input_tensor_77_dilations_0, groups = input_tensor_77_groups_0, pad = input_tensor_77_pad_0, pad_type = input_tensor_77_pad_type_0, strides = input_tensor_77_strides_0, weight = layer3_layer3_21_conv1_Conv_weight_to_fp16, x = input_225_cast_fp16)[name = tensor<string, []>("input_tensor_77_cast_fp16")];
            tensor<fp32, [256]> input_227_alpha_0 = const()[name = tensor<string, []>("input_227_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58331584)))];
            tensor<fp16, [1, 256, 14, 14]> input_227_cast_fp16 = prelu(alpha = input_227_alpha_0, x = input_tensor_77_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")];
            tensor<string, []> first_75_pad_type_0 = const()[name = tensor<string, []>("first_75_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_75_pad_0 = const()[name = tensor<string, []>("first_75_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_75_strides_0 = const()[name = tensor<string, []>("first_75_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_75_dilations_0 = const()[name = tensor<string, []>("first_75_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_75_groups_0 = const()[name = tensor<string, []>("first_75_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_21_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_21_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58332672)))];
            tensor<fp16, [256]> layer3_layer3_21_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_21_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59512384)))];
            tensor<fp16, [1, 256, 14, 14]> first_75_cast_fp16 = conv(bias = layer3_layer3_21_conv2_Conv_bias_to_fp16, dilations = first_75_dilations_0, groups = first_75_groups_0, pad = first_75_pad_0, pad_type = first_75_pad_type_0, strides = first_75_strides_0, weight = layer3_layer3_21_conv2_Conv_weight_to_fp16, x = input_227_cast_fp16)[name = tensor<string, []>("first_75_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_229_cast_fp16 = add(x = first_75_cast_fp16, y = input_223_cast_fp16)[name = tensor<string, []>("input_229_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_22_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_22_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59512960)))];
            tensor<fp16, [256]> layer3_layer3_22_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_22_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59513536)))];
            tensor<fp16, [256]> layer3_layer3_22_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_22_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59514112)))];
            tensor<fp16, [256]> layer3_layer3_22_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_22_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59514688)))];
            tensor<fp16, []> var_1718_to_fp16 = const()[name = tensor<string, []>("op_1718_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_231_cast_fp16 = batch_norm(beta = layer3_layer3_22_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1718_to_fp16, gamma = layer3_layer3_22_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_22_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_22_bn1_BatchNormalization_running_var_to_fp16, x = input_229_cast_fp16)[name = tensor<string, []>("input_231_cast_fp16")];
            tensor<string, []> input_tensor_79_pad_type_0 = const()[name = tensor<string, []>("input_tensor_79_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_79_pad_0 = const()[name = tensor<string, []>("input_tensor_79_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_79_strides_0 = const()[name = tensor<string, []>("input_tensor_79_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_79_dilations_0 = const()[name = tensor<string, []>("input_tensor_79_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_79_groups_0 = const()[name = tensor<string, []>("input_tensor_79_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_22_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_22_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59515264)))];
            tensor<fp16, [256]> layer3_layer3_22_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_22_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60694976)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_79_cast_fp16 = conv(bias = layer3_layer3_22_conv1_Conv_bias_to_fp16, dilations = input_tensor_79_dilations_0, groups = input_tensor_79_groups_0, pad = input_tensor_79_pad_0, pad_type = input_tensor_79_pad_type_0, strides = input_tensor_79_strides_0, weight = layer3_layer3_22_conv1_Conv_weight_to_fp16, x = input_231_cast_fp16)[name = tensor<string, []>("input_tensor_79_cast_fp16")];
            tensor<fp32, [256]> input_233_alpha_0 = const()[name = tensor<string, []>("input_233_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60695552)))];
            tensor<fp16, [1, 256, 14, 14]> input_233_cast_fp16 = prelu(alpha = input_233_alpha_0, x = input_tensor_79_cast_fp16)[name = tensor<string, []>("input_233_cast_fp16")];
            tensor<string, []> first_77_pad_type_0 = const()[name = tensor<string, []>("first_77_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_77_pad_0 = const()[name = tensor<string, []>("first_77_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_77_strides_0 = const()[name = tensor<string, []>("first_77_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_77_dilations_0 = const()[name = tensor<string, []>("first_77_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_77_groups_0 = const()[name = tensor<string, []>("first_77_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_22_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_22_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60696640)))];
            tensor<fp16, [256]> layer3_layer3_22_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_22_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61876352)))];
            tensor<fp16, [1, 256, 14, 14]> first_77_cast_fp16 = conv(bias = layer3_layer3_22_conv2_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = layer3_layer3_22_conv2_Conv_weight_to_fp16, x = input_233_cast_fp16)[name = tensor<string, []>("first_77_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_235_cast_fp16 = add(x = first_77_cast_fp16, y = input_229_cast_fp16)[name = tensor<string, []>("input_235_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_23_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_23_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61876928)))];
            tensor<fp16, [256]> layer3_layer3_23_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_23_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61877504)))];
            tensor<fp16, [256]> layer3_layer3_23_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_23_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61878080)))];
            tensor<fp16, [256]> layer3_layer3_23_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_23_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61878656)))];
            tensor<fp16, []> var_1755_to_fp16 = const()[name = tensor<string, []>("op_1755_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_237_cast_fp16 = batch_norm(beta = layer3_layer3_23_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1755_to_fp16, gamma = layer3_layer3_23_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_23_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_23_bn1_BatchNormalization_running_var_to_fp16, x = input_235_cast_fp16)[name = tensor<string, []>("input_237_cast_fp16")];
            tensor<string, []> input_tensor_81_pad_type_0 = const()[name = tensor<string, []>("input_tensor_81_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_81_pad_0 = const()[name = tensor<string, []>("input_tensor_81_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_81_strides_0 = const()[name = tensor<string, []>("input_tensor_81_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_81_dilations_0 = const()[name = tensor<string, []>("input_tensor_81_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_81_groups_0 = const()[name = tensor<string, []>("input_tensor_81_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_23_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_23_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61879232)))];
            tensor<fp16, [256]> layer3_layer3_23_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_23_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63058944)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_81_cast_fp16 = conv(bias = layer3_layer3_23_conv1_Conv_bias_to_fp16, dilations = input_tensor_81_dilations_0, groups = input_tensor_81_groups_0, pad = input_tensor_81_pad_0, pad_type = input_tensor_81_pad_type_0, strides = input_tensor_81_strides_0, weight = layer3_layer3_23_conv1_Conv_weight_to_fp16, x = input_237_cast_fp16)[name = tensor<string, []>("input_tensor_81_cast_fp16")];
            tensor<fp32, [256]> input_239_alpha_0 = const()[name = tensor<string, []>("input_239_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63059520)))];
            tensor<fp16, [1, 256, 14, 14]> input_239_cast_fp16 = prelu(alpha = input_239_alpha_0, x = input_tensor_81_cast_fp16)[name = tensor<string, []>("input_239_cast_fp16")];
            tensor<string, []> first_79_pad_type_0 = const()[name = tensor<string, []>("first_79_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_79_pad_0 = const()[name = tensor<string, []>("first_79_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_79_strides_0 = const()[name = tensor<string, []>("first_79_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_79_dilations_0 = const()[name = tensor<string, []>("first_79_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_79_groups_0 = const()[name = tensor<string, []>("first_79_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_23_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_23_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63060608)))];
            tensor<fp16, [256]> layer3_layer3_23_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_23_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64240320)))];
            tensor<fp16, [1, 256, 14, 14]> first_79_cast_fp16 = conv(bias = layer3_layer3_23_conv2_Conv_bias_to_fp16, dilations = first_79_dilations_0, groups = first_79_groups_0, pad = first_79_pad_0, pad_type = first_79_pad_type_0, strides = first_79_strides_0, weight = layer3_layer3_23_conv2_Conv_weight_to_fp16, x = input_239_cast_fp16)[name = tensor<string, []>("first_79_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_241_cast_fp16 = add(x = first_79_cast_fp16, y = input_235_cast_fp16)[name = tensor<string, []>("input_241_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_24_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_24_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64240896)))];
            tensor<fp16, [256]> layer3_layer3_24_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_24_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64241472)))];
            tensor<fp16, [256]> layer3_layer3_24_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_24_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64242048)))];
            tensor<fp16, [256]> layer3_layer3_24_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_24_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64242624)))];
            tensor<fp16, []> var_1792_to_fp16 = const()[name = tensor<string, []>("op_1792_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_243_cast_fp16 = batch_norm(beta = layer3_layer3_24_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1792_to_fp16, gamma = layer3_layer3_24_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_24_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_24_bn1_BatchNormalization_running_var_to_fp16, x = input_241_cast_fp16)[name = tensor<string, []>("input_243_cast_fp16")];
            tensor<string, []> input_tensor_83_pad_type_0 = const()[name = tensor<string, []>("input_tensor_83_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_83_pad_0 = const()[name = tensor<string, []>("input_tensor_83_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_83_strides_0 = const()[name = tensor<string, []>("input_tensor_83_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_83_dilations_0 = const()[name = tensor<string, []>("input_tensor_83_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_83_groups_0 = const()[name = tensor<string, []>("input_tensor_83_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_24_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_24_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64243200)))];
            tensor<fp16, [256]> layer3_layer3_24_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_24_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(65422912)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_83_cast_fp16 = conv(bias = layer3_layer3_24_conv1_Conv_bias_to_fp16, dilations = input_tensor_83_dilations_0, groups = input_tensor_83_groups_0, pad = input_tensor_83_pad_0, pad_type = input_tensor_83_pad_type_0, strides = input_tensor_83_strides_0, weight = layer3_layer3_24_conv1_Conv_weight_to_fp16, x = input_243_cast_fp16)[name = tensor<string, []>("input_tensor_83_cast_fp16")];
            tensor<fp32, [256]> input_245_alpha_0 = const()[name = tensor<string, []>("input_245_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(65423488)))];
            tensor<fp16, [1, 256, 14, 14]> input_245_cast_fp16 = prelu(alpha = input_245_alpha_0, x = input_tensor_83_cast_fp16)[name = tensor<string, []>("input_245_cast_fp16")];
            tensor<string, []> first_81_pad_type_0 = const()[name = tensor<string, []>("first_81_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_81_pad_0 = const()[name = tensor<string, []>("first_81_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_81_strides_0 = const()[name = tensor<string, []>("first_81_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_81_dilations_0 = const()[name = tensor<string, []>("first_81_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_81_groups_0 = const()[name = tensor<string, []>("first_81_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_24_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_24_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(65424576)))];
            tensor<fp16, [256]> layer3_layer3_24_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_24_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66604288)))];
            tensor<fp16, [1, 256, 14, 14]> first_81_cast_fp16 = conv(bias = layer3_layer3_24_conv2_Conv_bias_to_fp16, dilations = first_81_dilations_0, groups = first_81_groups_0, pad = first_81_pad_0, pad_type = first_81_pad_type_0, strides = first_81_strides_0, weight = layer3_layer3_24_conv2_Conv_weight_to_fp16, x = input_245_cast_fp16)[name = tensor<string, []>("first_81_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_247_cast_fp16 = add(x = first_81_cast_fp16, y = input_241_cast_fp16)[name = tensor<string, []>("input_247_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_25_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_25_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66604864)))];
            tensor<fp16, [256]> layer3_layer3_25_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_25_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66605440)))];
            tensor<fp16, [256]> layer3_layer3_25_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_25_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66606016)))];
            tensor<fp16, [256]> layer3_layer3_25_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_25_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66606592)))];
            tensor<fp16, []> var_1829_to_fp16 = const()[name = tensor<string, []>("op_1829_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_249_cast_fp16 = batch_norm(beta = layer3_layer3_25_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1829_to_fp16, gamma = layer3_layer3_25_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_25_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_25_bn1_BatchNormalization_running_var_to_fp16, x = input_247_cast_fp16)[name = tensor<string, []>("input_249_cast_fp16")];
            tensor<string, []> input_tensor_85_pad_type_0 = const()[name = tensor<string, []>("input_tensor_85_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_85_pad_0 = const()[name = tensor<string, []>("input_tensor_85_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_85_strides_0 = const()[name = tensor<string, []>("input_tensor_85_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_85_dilations_0 = const()[name = tensor<string, []>("input_tensor_85_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_85_groups_0 = const()[name = tensor<string, []>("input_tensor_85_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_25_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_25_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66607168)))];
            tensor<fp16, [256]> layer3_layer3_25_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_25_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67786880)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_85_cast_fp16 = conv(bias = layer3_layer3_25_conv1_Conv_bias_to_fp16, dilations = input_tensor_85_dilations_0, groups = input_tensor_85_groups_0, pad = input_tensor_85_pad_0, pad_type = input_tensor_85_pad_type_0, strides = input_tensor_85_strides_0, weight = layer3_layer3_25_conv1_Conv_weight_to_fp16, x = input_249_cast_fp16)[name = tensor<string, []>("input_tensor_85_cast_fp16")];
            tensor<fp32, [256]> input_251_alpha_0 = const()[name = tensor<string, []>("input_251_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67787456)))];
            tensor<fp16, [1, 256, 14, 14]> input_251_cast_fp16 = prelu(alpha = input_251_alpha_0, x = input_tensor_85_cast_fp16)[name = tensor<string, []>("input_251_cast_fp16")];
            tensor<string, []> first_83_pad_type_0 = const()[name = tensor<string, []>("first_83_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_83_pad_0 = const()[name = tensor<string, []>("first_83_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_83_strides_0 = const()[name = tensor<string, []>("first_83_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_83_dilations_0 = const()[name = tensor<string, []>("first_83_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_83_groups_0 = const()[name = tensor<string, []>("first_83_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_25_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_25_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67788544)))];
            tensor<fp16, [256]> layer3_layer3_25_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_25_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68968256)))];
            tensor<fp16, [1, 256, 14, 14]> first_83_cast_fp16 = conv(bias = layer3_layer3_25_conv2_Conv_bias_to_fp16, dilations = first_83_dilations_0, groups = first_83_groups_0, pad = first_83_pad_0, pad_type = first_83_pad_type_0, strides = first_83_strides_0, weight = layer3_layer3_25_conv2_Conv_weight_to_fp16, x = input_251_cast_fp16)[name = tensor<string, []>("first_83_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_253_cast_fp16 = add(x = first_83_cast_fp16, y = input_247_cast_fp16)[name = tensor<string, []>("input_253_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_26_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_26_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68968832)))];
            tensor<fp16, [256]> layer3_layer3_26_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_26_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68969408)))];
            tensor<fp16, [256]> layer3_layer3_26_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_26_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68969984)))];
            tensor<fp16, [256]> layer3_layer3_26_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_26_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68970560)))];
            tensor<fp16, []> var_1866_to_fp16 = const()[name = tensor<string, []>("op_1866_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_255_cast_fp16 = batch_norm(beta = layer3_layer3_26_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1866_to_fp16, gamma = layer3_layer3_26_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_26_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_26_bn1_BatchNormalization_running_var_to_fp16, x = input_253_cast_fp16)[name = tensor<string, []>("input_255_cast_fp16")];
            tensor<string, []> input_tensor_87_pad_type_0 = const()[name = tensor<string, []>("input_tensor_87_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_87_pad_0 = const()[name = tensor<string, []>("input_tensor_87_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_87_strides_0 = const()[name = tensor<string, []>("input_tensor_87_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_87_dilations_0 = const()[name = tensor<string, []>("input_tensor_87_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_87_groups_0 = const()[name = tensor<string, []>("input_tensor_87_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_26_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_26_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68971136)))];
            tensor<fp16, [256]> layer3_layer3_26_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_26_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70150848)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_87_cast_fp16 = conv(bias = layer3_layer3_26_conv1_Conv_bias_to_fp16, dilations = input_tensor_87_dilations_0, groups = input_tensor_87_groups_0, pad = input_tensor_87_pad_0, pad_type = input_tensor_87_pad_type_0, strides = input_tensor_87_strides_0, weight = layer3_layer3_26_conv1_Conv_weight_to_fp16, x = input_255_cast_fp16)[name = tensor<string, []>("input_tensor_87_cast_fp16")];
            tensor<fp32, [256]> input_257_alpha_0 = const()[name = tensor<string, []>("input_257_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70151424)))];
            tensor<fp16, [1, 256, 14, 14]> input_257_cast_fp16 = prelu(alpha = input_257_alpha_0, x = input_tensor_87_cast_fp16)[name = tensor<string, []>("input_257_cast_fp16")];
            tensor<string, []> first_85_pad_type_0 = const()[name = tensor<string, []>("first_85_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_85_pad_0 = const()[name = tensor<string, []>("first_85_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_85_strides_0 = const()[name = tensor<string, []>("first_85_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_85_dilations_0 = const()[name = tensor<string, []>("first_85_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_85_groups_0 = const()[name = tensor<string, []>("first_85_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_26_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_26_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70152512)))];
            tensor<fp16, [256]> layer3_layer3_26_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_26_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71332224)))];
            tensor<fp16, [1, 256, 14, 14]> first_85_cast_fp16 = conv(bias = layer3_layer3_26_conv2_Conv_bias_to_fp16, dilations = first_85_dilations_0, groups = first_85_groups_0, pad = first_85_pad_0, pad_type = first_85_pad_type_0, strides = first_85_strides_0, weight = layer3_layer3_26_conv2_Conv_weight_to_fp16, x = input_257_cast_fp16)[name = tensor<string, []>("first_85_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_259_cast_fp16 = add(x = first_85_cast_fp16, y = input_253_cast_fp16)[name = tensor<string, []>("input_259_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_27_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_27_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71332800)))];
            tensor<fp16, [256]> layer3_layer3_27_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_27_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71333376)))];
            tensor<fp16, [256]> layer3_layer3_27_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_27_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71333952)))];
            tensor<fp16, [256]> layer3_layer3_27_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_27_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71334528)))];
            tensor<fp16, []> var_1903_to_fp16 = const()[name = tensor<string, []>("op_1903_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_261_cast_fp16 = batch_norm(beta = layer3_layer3_27_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1903_to_fp16, gamma = layer3_layer3_27_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_27_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_27_bn1_BatchNormalization_running_var_to_fp16, x = input_259_cast_fp16)[name = tensor<string, []>("input_261_cast_fp16")];
            tensor<string, []> input_tensor_89_pad_type_0 = const()[name = tensor<string, []>("input_tensor_89_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_89_pad_0 = const()[name = tensor<string, []>("input_tensor_89_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_89_strides_0 = const()[name = tensor<string, []>("input_tensor_89_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_89_dilations_0 = const()[name = tensor<string, []>("input_tensor_89_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_89_groups_0 = const()[name = tensor<string, []>("input_tensor_89_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_27_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_27_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71335104)))];
            tensor<fp16, [256]> layer3_layer3_27_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_27_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72514816)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_89_cast_fp16 = conv(bias = layer3_layer3_27_conv1_Conv_bias_to_fp16, dilations = input_tensor_89_dilations_0, groups = input_tensor_89_groups_0, pad = input_tensor_89_pad_0, pad_type = input_tensor_89_pad_type_0, strides = input_tensor_89_strides_0, weight = layer3_layer3_27_conv1_Conv_weight_to_fp16, x = input_261_cast_fp16)[name = tensor<string, []>("input_tensor_89_cast_fp16")];
            tensor<fp32, [256]> input_263_alpha_0 = const()[name = tensor<string, []>("input_263_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72515392)))];
            tensor<fp16, [1, 256, 14, 14]> input_263_cast_fp16 = prelu(alpha = input_263_alpha_0, x = input_tensor_89_cast_fp16)[name = tensor<string, []>("input_263_cast_fp16")];
            tensor<string, []> first_87_pad_type_0 = const()[name = tensor<string, []>("first_87_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_87_pad_0 = const()[name = tensor<string, []>("first_87_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_87_strides_0 = const()[name = tensor<string, []>("first_87_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_87_dilations_0 = const()[name = tensor<string, []>("first_87_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_87_groups_0 = const()[name = tensor<string, []>("first_87_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_27_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_27_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72516480)))];
            tensor<fp16, [256]> layer3_layer3_27_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_27_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73696192)))];
            tensor<fp16, [1, 256, 14, 14]> first_87_cast_fp16 = conv(bias = layer3_layer3_27_conv2_Conv_bias_to_fp16, dilations = first_87_dilations_0, groups = first_87_groups_0, pad = first_87_pad_0, pad_type = first_87_pad_type_0, strides = first_87_strides_0, weight = layer3_layer3_27_conv2_Conv_weight_to_fp16, x = input_263_cast_fp16)[name = tensor<string, []>("first_87_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_265_cast_fp16 = add(x = first_87_cast_fp16, y = input_259_cast_fp16)[name = tensor<string, []>("input_265_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_28_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_28_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73696768)))];
            tensor<fp16, [256]> layer3_layer3_28_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_28_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73697344)))];
            tensor<fp16, [256]> layer3_layer3_28_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_28_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73697920)))];
            tensor<fp16, [256]> layer3_layer3_28_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_28_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73698496)))];
            tensor<fp16, []> var_1940_to_fp16 = const()[name = tensor<string, []>("op_1940_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_267_cast_fp16 = batch_norm(beta = layer3_layer3_28_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1940_to_fp16, gamma = layer3_layer3_28_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_28_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_28_bn1_BatchNormalization_running_var_to_fp16, x = input_265_cast_fp16)[name = tensor<string, []>("input_267_cast_fp16")];
            tensor<string, []> input_tensor_91_pad_type_0 = const()[name = tensor<string, []>("input_tensor_91_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_91_pad_0 = const()[name = tensor<string, []>("input_tensor_91_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_91_strides_0 = const()[name = tensor<string, []>("input_tensor_91_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_91_dilations_0 = const()[name = tensor<string, []>("input_tensor_91_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_91_groups_0 = const()[name = tensor<string, []>("input_tensor_91_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_28_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_28_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73699072)))];
            tensor<fp16, [256]> layer3_layer3_28_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_28_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74878784)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_91_cast_fp16 = conv(bias = layer3_layer3_28_conv1_Conv_bias_to_fp16, dilations = input_tensor_91_dilations_0, groups = input_tensor_91_groups_0, pad = input_tensor_91_pad_0, pad_type = input_tensor_91_pad_type_0, strides = input_tensor_91_strides_0, weight = layer3_layer3_28_conv1_Conv_weight_to_fp16, x = input_267_cast_fp16)[name = tensor<string, []>("input_tensor_91_cast_fp16")];
            tensor<fp32, [256]> input_269_alpha_0 = const()[name = tensor<string, []>("input_269_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74879360)))];
            tensor<fp16, [1, 256, 14, 14]> input_269_cast_fp16 = prelu(alpha = input_269_alpha_0, x = input_tensor_91_cast_fp16)[name = tensor<string, []>("input_269_cast_fp16")];
            tensor<string, []> first_89_pad_type_0 = const()[name = tensor<string, []>("first_89_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_89_pad_0 = const()[name = tensor<string, []>("first_89_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_89_strides_0 = const()[name = tensor<string, []>("first_89_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_89_dilations_0 = const()[name = tensor<string, []>("first_89_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_89_groups_0 = const()[name = tensor<string, []>("first_89_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_28_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_28_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74880448)))];
            tensor<fp16, [256]> layer3_layer3_28_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_28_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76060160)))];
            tensor<fp16, [1, 256, 14, 14]> first_89_cast_fp16 = conv(bias = layer3_layer3_28_conv2_Conv_bias_to_fp16, dilations = first_89_dilations_0, groups = first_89_groups_0, pad = first_89_pad_0, pad_type = first_89_pad_type_0, strides = first_89_strides_0, weight = layer3_layer3_28_conv2_Conv_weight_to_fp16, x = input_269_cast_fp16)[name = tensor<string, []>("first_89_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_271_cast_fp16 = add(x = first_89_cast_fp16, y = input_265_cast_fp16)[name = tensor<string, []>("input_271_cast_fp16")];
            tensor<fp16, [256]> layer3_layer3_29_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_29_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76060736)))];
            tensor<fp16, [256]> layer3_layer3_29_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_29_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76061312)))];
            tensor<fp16, [256]> layer3_layer3_29_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_29_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76061888)))];
            tensor<fp16, [256]> layer3_layer3_29_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_29_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76062464)))];
            tensor<fp16, []> var_1977_to_fp16 = const()[name = tensor<string, []>("op_1977_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_273_cast_fp16 = batch_norm(beta = layer3_layer3_29_bn1_BatchNormalization_bias_to_fp16, epsilon = var_1977_to_fp16, gamma = layer3_layer3_29_bn1_BatchNormalization_weight_to_fp16, mean = layer3_layer3_29_bn1_BatchNormalization_running_mean_to_fp16, variance = layer3_layer3_29_bn1_BatchNormalization_running_var_to_fp16, x = input_271_cast_fp16)[name = tensor<string, []>("input_273_cast_fp16")];
            tensor<string, []> input_tensor_93_pad_type_0 = const()[name = tensor<string, []>("input_tensor_93_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_93_pad_0 = const()[name = tensor<string, []>("input_tensor_93_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_93_strides_0 = const()[name = tensor<string, []>("input_tensor_93_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_93_dilations_0 = const()[name = tensor<string, []>("input_tensor_93_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_93_groups_0 = const()[name = tensor<string, []>("input_tensor_93_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_29_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_29_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76063040)))];
            tensor<fp16, [256]> layer3_layer3_29_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_29_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77242752)))];
            tensor<fp16, [1, 256, 14, 14]> input_tensor_93_cast_fp16 = conv(bias = layer3_layer3_29_conv1_Conv_bias_to_fp16, dilations = input_tensor_93_dilations_0, groups = input_tensor_93_groups_0, pad = input_tensor_93_pad_0, pad_type = input_tensor_93_pad_type_0, strides = input_tensor_93_strides_0, weight = layer3_layer3_29_conv1_Conv_weight_to_fp16, x = input_273_cast_fp16)[name = tensor<string, []>("input_tensor_93_cast_fp16")];
            tensor<fp32, [256]> input_275_alpha_0 = const()[name = tensor<string, []>("input_275_alpha_0"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77243328)))];
            tensor<fp16, [1, 256, 14, 14]> input_275_cast_fp16 = prelu(alpha = input_275_alpha_0, x = input_tensor_93_cast_fp16)[name = tensor<string, []>("input_275_cast_fp16")];
            tensor<string, []> first_91_pad_type_0 = const()[name = tensor<string, []>("first_91_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_91_pad_0 = const()[name = tensor<string, []>("first_91_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_91_strides_0 = const()[name = tensor<string, []>("first_91_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_91_dilations_0 = const()[name = tensor<string, []>("first_91_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_91_groups_0 = const()[name = tensor<string, []>("first_91_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 3, 3]> layer3_layer3_29_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_29_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77244416)))];
            tensor<fp16, [256]> layer3_layer3_29_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer3_layer3_29_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78424128)))];
            tensor<fp16, [1, 256, 14, 14]> first_91_cast_fp16 = conv(bias = layer3_layer3_29_conv2_Conv_bias_to_fp16, dilations = first_91_dilations_0, groups = first_91_groups_0, pad = first_91_pad_0, pad_type = first_91_pad_type_0, strides = first_91_strides_0, weight = layer3_layer3_29_conv2_Conv_weight_to_fp16, x = input_275_cast_fp16)[name = tensor<string, []>("first_91_cast_fp16")];
            tensor<fp16, [1, 256, 14, 14]> input_277_cast_fp16 = add(x = first_91_cast_fp16, y = input_271_cast_fp16)[name = tensor<string, []>("input_277_cast_fp16")];
            tensor<fp16, [256]> layer4_layer4_0_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78424704)))];
            tensor<fp16, [256]> layer4_layer4_0_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78425280)))];
            tensor<fp16, [256]> layer4_layer4_0_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78425856)))];
            tensor<fp16, [256]> layer4_layer4_0_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78426432)))];
            tensor<fp16, []> var_2014_to_fp16 = const()[name = tensor<string, []>("op_2014_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 256, 14, 14]> input_279_cast_fp16 = batch_norm(beta = layer4_layer4_0_bn1_BatchNormalization_bias_to_fp16, epsilon = var_2014_to_fp16, gamma = layer4_layer4_0_bn1_BatchNormalization_weight_to_fp16, mean = layer4_layer4_0_bn1_BatchNormalization_running_mean_to_fp16, variance = layer4_layer4_0_bn1_BatchNormalization_running_var_to_fp16, x = input_277_cast_fp16)[name = tensor<string, []>("input_279_cast_fp16")];
            tensor<string, []> input_tensor_95_pad_type_0 = const()[name = tensor<string, []>("input_tensor_95_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_95_pad_0 = const()[name = tensor<string, []>("input_tensor_95_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_95_strides_0 = const()[name = tensor<string, []>("input_tensor_95_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_95_dilations_0 = const()[name = tensor<string, []>("input_tensor_95_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_95_groups_0 = const()[name = tensor<string, []>("input_tensor_95_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 256, 3, 3]> layer4_layer4_0_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [512, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78427008)))];
            tensor<fp16, [512]> layer4_layer4_0_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80786368)))];
            tensor<fp16, [1, 512, 14, 14]> input_tensor_95_cast_fp16 = conv(bias = layer4_layer4_0_conv1_Conv_bias_to_fp16, dilations = input_tensor_95_dilations_0, groups = input_tensor_95_groups_0, pad = input_tensor_95_pad_0, pad_type = input_tensor_95_pad_type_0, strides = input_tensor_95_strides_0, weight = layer4_layer4_0_conv1_Conv_weight_to_fp16, x = input_279_cast_fp16)[name = tensor<string, []>("input_tensor_95_cast_fp16")];
            tensor<fp32, [512]> input_281_alpha_0 = const()[name = tensor<string, []>("input_281_alpha_0"), val = tensor<fp32, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80787456)))];
            tensor<fp16, [1, 512, 14, 14]> input_281_cast_fp16 = prelu(alpha = input_281_alpha_0, x = input_tensor_95_cast_fp16)[name = tensor<string, []>("input_281_cast_fp16")];
            tensor<string, []> first_93_pad_type_0 = const()[name = tensor<string, []>("first_93_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_93_pad_0 = const()[name = tensor<string, []>("first_93_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_93_strides_0 = const()[name = tensor<string, []>("first_93_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> first_93_dilations_0 = const()[name = tensor<string, []>("first_93_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_93_groups_0 = const()[name = tensor<string, []>("first_93_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 3, 3]> layer4_layer4_0_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 512, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80789568)))];
            tensor<fp16, [512]> layer4_layer4_0_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85508224)))];
            tensor<fp16, [1, 512, 7, 7]> first_93_cast_fp16 = conv(bias = layer4_layer4_0_conv2_Conv_bias_to_fp16, dilations = first_93_dilations_0, groups = first_93_groups_0, pad = first_93_pad_0, pad_type = first_93_pad_type_0, strides = first_93_strides_0, weight = layer4_layer4_0_conv2_Conv_weight_to_fp16, x = input_281_cast_fp16)[name = tensor<string, []>("first_93_cast_fp16")];
            tensor<string, []> second_pad_type_0 = const()[name = tensor<string, []>("second_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> second_strides_0 = const()[name = tensor<string, []>("second_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> second_pad_0 = const()[name = tensor<string, []>("second_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> second_dilations_0 = const()[name = tensor<string, []>("second_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> second_groups_0 = const()[name = tensor<string, []>("second_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 256, 1, 1]> layer4_layer4_0_downsample_downsample_0_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_downsample_downsample_0_Conv_weight_to_fp16"), val = tensor<fp16, [512, 256, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85509312)))];
            tensor<fp16, [512]> layer4_layer4_0_downsample_downsample_0_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_0_downsample_downsample_0_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85771520)))];
            tensor<fp16, [1, 512, 7, 7]> second_cast_fp16 = conv(bias = layer4_layer4_0_downsample_downsample_0_Conv_bias_to_fp16, dilations = second_dilations_0, groups = second_groups_0, pad = second_pad_0, pad_type = second_pad_type_0, strides = second_strides_0, weight = layer4_layer4_0_downsample_downsample_0_Conv_weight_to_fp16, x = input_277_cast_fp16)[name = tensor<string, []>("second_cast_fp16")];
            tensor<fp16, [1, 512, 7, 7]> input_283_cast_fp16 = add(x = first_93_cast_fp16, y = second_cast_fp16)[name = tensor<string, []>("input_283_cast_fp16")];
            tensor<fp16, [512]> layer4_layer4_1_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_1_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85772608)))];
            tensor<fp16, [512]> layer4_layer4_1_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_1_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85773696)))];
            tensor<fp16, [512]> layer4_layer4_1_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_1_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85774784)))];
            tensor<fp16, [512]> layer4_layer4_1_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_1_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85775872)))];
            tensor<fp16, []> var_2064_to_fp16 = const()[name = tensor<string, []>("op_2064_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 512, 7, 7]> input_285_cast_fp16 = batch_norm(beta = layer4_layer4_1_bn1_BatchNormalization_bias_to_fp16, epsilon = var_2064_to_fp16, gamma = layer4_layer4_1_bn1_BatchNormalization_weight_to_fp16, mean = layer4_layer4_1_bn1_BatchNormalization_running_mean_to_fp16, variance = layer4_layer4_1_bn1_BatchNormalization_running_var_to_fp16, x = input_283_cast_fp16)[name = tensor<string, []>("input_285_cast_fp16")];
            tensor<string, []> input_tensor_97_pad_type_0 = const()[name = tensor<string, []>("input_tensor_97_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_97_pad_0 = const()[name = tensor<string, []>("input_tensor_97_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_97_strides_0 = const()[name = tensor<string, []>("input_tensor_97_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_97_dilations_0 = const()[name = tensor<string, []>("input_tensor_97_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_97_groups_0 = const()[name = tensor<string, []>("input_tensor_97_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 3, 3]> layer4_layer4_1_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_1_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [512, 512, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85776960)))];
            tensor<fp16, [512]> layer4_layer4_1_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_1_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90495616)))];
            tensor<fp16, [1, 512, 7, 7]> input_tensor_97_cast_fp16 = conv(bias = layer4_layer4_1_conv1_Conv_bias_to_fp16, dilations = input_tensor_97_dilations_0, groups = input_tensor_97_groups_0, pad = input_tensor_97_pad_0, pad_type = input_tensor_97_pad_type_0, strides = input_tensor_97_strides_0, weight = layer4_layer4_1_conv1_Conv_weight_to_fp16, x = input_285_cast_fp16)[name = tensor<string, []>("input_tensor_97_cast_fp16")];
            tensor<fp32, [512]> input_287_alpha_0 = const()[name = tensor<string, []>("input_287_alpha_0"), val = tensor<fp32, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90496704)))];
            tensor<fp16, [1, 512, 7, 7]> input_287_cast_fp16 = prelu(alpha = input_287_alpha_0, x = input_tensor_97_cast_fp16)[name = tensor<string, []>("input_287_cast_fp16")];
            tensor<string, []> first_95_pad_type_0 = const()[name = tensor<string, []>("first_95_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_95_pad_0 = const()[name = tensor<string, []>("first_95_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_95_strides_0 = const()[name = tensor<string, []>("first_95_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_95_dilations_0 = const()[name = tensor<string, []>("first_95_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_95_groups_0 = const()[name = tensor<string, []>("first_95_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 3, 3]> layer4_layer4_1_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_1_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 512, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90498816)))];
            tensor<fp16, [512]> layer4_layer4_1_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_1_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95217472)))];
            tensor<fp16, [1, 512, 7, 7]> first_95_cast_fp16 = conv(bias = layer4_layer4_1_conv2_Conv_bias_to_fp16, dilations = first_95_dilations_0, groups = first_95_groups_0, pad = first_95_pad_0, pad_type = first_95_pad_type_0, strides = first_95_strides_0, weight = layer4_layer4_1_conv2_Conv_weight_to_fp16, x = input_287_cast_fp16)[name = tensor<string, []>("first_95_cast_fp16")];
            tensor<fp16, [1, 512, 7, 7]> input_289_cast_fp16 = add(x = first_95_cast_fp16, y = input_283_cast_fp16)[name = tensor<string, []>("input_289_cast_fp16")];
            tensor<fp16, [512]> layer4_layer4_2_bn1_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_2_bn1_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95218560)))];
            tensor<fp16, [512]> layer4_layer4_2_bn1_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_2_bn1_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95219648)))];
            tensor<fp16, [512]> layer4_layer4_2_bn1_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_2_bn1_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95220736)))];
            tensor<fp16, [512]> layer4_layer4_2_bn1_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_2_bn1_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95221824)))];
            tensor<fp16, []> var_2101_to_fp16 = const()[name = tensor<string, []>("op_2101_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 512, 7, 7]> input_291_cast_fp16 = batch_norm(beta = layer4_layer4_2_bn1_BatchNormalization_bias_to_fp16, epsilon = var_2101_to_fp16, gamma = layer4_layer4_2_bn1_BatchNormalization_weight_to_fp16, mean = layer4_layer4_2_bn1_BatchNormalization_running_mean_to_fp16, variance = layer4_layer4_2_bn1_BatchNormalization_running_var_to_fp16, x = input_289_cast_fp16)[name = tensor<string, []>("input_291_cast_fp16")];
            tensor<string, []> input_tensor_pad_type_0 = const()[name = tensor<string, []>("input_tensor_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_tensor_pad_0 = const()[name = tensor<string, []>("input_tensor_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_tensor_strides_0 = const()[name = tensor<string, []>("input_tensor_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_tensor_dilations_0 = const()[name = tensor<string, []>("input_tensor_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_tensor_groups_0 = const()[name = tensor<string, []>("input_tensor_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 3, 3]> layer4_layer4_2_conv1_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_2_conv1_Conv_weight_to_fp16"), val = tensor<fp16, [512, 512, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95222912)))];
            tensor<fp16, [512]> layer4_layer4_2_conv1_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_2_conv1_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(99941568)))];
            tensor<fp16, [1, 512, 7, 7]> input_tensor_cast_fp16 = conv(bias = layer4_layer4_2_conv1_Conv_bias_to_fp16, dilations = input_tensor_dilations_0, groups = input_tensor_groups_0, pad = input_tensor_pad_0, pad_type = input_tensor_pad_type_0, strides = input_tensor_strides_0, weight = layer4_layer4_2_conv1_Conv_weight_to_fp16, x = input_291_cast_fp16)[name = tensor<string, []>("input_tensor_cast_fp16")];
            tensor<fp32, [512]> input_293_alpha_0 = const()[name = tensor<string, []>("input_293_alpha_0"), val = tensor<fp32, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(99942656)))];
            tensor<fp16, [1, 512, 7, 7]> input_293_cast_fp16 = prelu(alpha = input_293_alpha_0, x = input_tensor_cast_fp16)[name = tensor<string, []>("input_293_cast_fp16")];
            tensor<string, []> first_pad_type_0 = const()[name = tensor<string, []>("first_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> first_pad_0 = const()[name = tensor<string, []>("first_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> first_strides_0 = const()[name = tensor<string, []>("first_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> first_dilations_0 = const()[name = tensor<string, []>("first_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> first_groups_0 = const()[name = tensor<string, []>("first_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 3, 3]> layer4_layer4_2_conv2_Conv_weight_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_2_conv2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 512, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(99944768)))];
            tensor<fp16, [512]> layer4_layer4_2_conv2_Conv_bias_to_fp16 = const()[name = tensor<string, []>("layer4_layer4_2_conv2_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104663424)))];
            tensor<fp16, [1, 512, 7, 7]> first_cast_fp16 = conv(bias = layer4_layer4_2_conv2_Conv_bias_to_fp16, dilations = first_dilations_0, groups = first_groups_0, pad = first_pad_0, pad_type = first_pad_type_0, strides = first_strides_0, weight = layer4_layer4_2_conv2_Conv_weight_to_fp16, x = input_293_cast_fp16)[name = tensor<string, []>("first_cast_fp16")];
            tensor<fp16, [1, 512, 7, 7]> input_295_cast_fp16 = add(x = first_cast_fp16, y = input_289_cast_fp16)[name = tensor<string, []>("input_295_cast_fp16")];
            tensor<fp16, [512]> bn2_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("bn2_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104664512)))];
            tensor<fp16, [512]> bn2_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("bn2_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104665600)))];
            tensor<fp16, [512]> bn2_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("bn2_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104666688)))];
            tensor<fp16, [512]> bn2_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("bn2_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104667776)))];
            tensor<fp16, []> var_2138_to_fp16 = const()[name = tensor<string, []>("op_2138_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 512, 7, 7]> input_297_cast_fp16 = batch_norm(beta = bn2_BatchNormalization_bias_to_fp16, epsilon = var_2138_to_fp16, gamma = bn2_BatchNormalization_weight_to_fp16, mean = bn2_BatchNormalization_running_mean_to_fp16, variance = bn2_BatchNormalization_running_var_to_fp16, x = input_295_cast_fp16)[name = tensor<string, []>("input_297_cast_fp16")];
            tensor<int32, [2]> concat_0 = const()[name = tensor<string, []>("concat_0"), val = tensor<int32, [2]>([1, 25088])];
            tensor<fp16, [1, 25088]> input_299_cast_fp16 = reshape(shape = concat_0, x = input_297_cast_fp16)[name = tensor<string, []>("input_299_cast_fp16")];
            tensor<fp16, [512, 25088]> fc_Gemm_weight_to_fp16 = const()[name = tensor<string, []>("fc_Gemm_weight_to_fp16"), val = tensor<fp16, [512, 25088]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104668864)))];
            tensor<fp16, [512]> fc_Gemm_bias_to_fp16 = const()[name = tensor<string, []>("fc_Gemm_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130359040)))];
            tensor<fp16, [1, 512]> linear_0_cast_fp16 = linear(bias = fc_Gemm_bias_to_fp16, weight = fc_Gemm_weight_to_fp16, x = input_299_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
            tensor<int32, [1]> var_2160_rank2_expansion_axes_0 = const()[name = tensor<string, []>("op_2160_rank2_expansion_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 512, 1]> var_2160_rank2_expansion_cast_fp16 = expand_dims(axes = var_2160_rank2_expansion_axes_0, x = linear_0_cast_fp16)[name = tensor<string, []>("op_2160_rank2_expansion_cast_fp16")];
            tensor<fp16, [512]> features_BatchNormalization_running_mean_to_fp16 = const()[name = tensor<string, []>("features_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130360128)))];
            tensor<fp16, [512]> features_BatchNormalization_running_var_to_fp16 = const()[name = tensor<string, []>("features_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130361216)))];
            tensor<fp16, [512]> features_BatchNormalization_weight_to_fp16 = const()[name = tensor<string, []>("features_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130362304)))];
            tensor<fp16, [512]> features_BatchNormalization_bias_to_fp16 = const()[name = tensor<string, []>("features_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130363392)))];
            tensor<fp16, []> var_2153_to_fp16 = const()[name = tensor<string, []>("op_2153_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 512, 1]> var_2160_batch_norm_1d_cast_fp16 = batch_norm(beta = features_BatchNormalization_bias_to_fp16, epsilon = var_2153_to_fp16, gamma = features_BatchNormalization_weight_to_fp16, mean = features_BatchNormalization_running_mean_to_fp16, variance = features_BatchNormalization_running_var_to_fp16, x = var_2160_rank2_expansion_cast_fp16)[name = tensor<string, []>("op_2160_batch_norm_1d_cast_fp16")];
            tensor<int32, [1]> var_2160_axes_0 = const()[name = tensor<string, []>("op_2160_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 512]> embedding = squeeze(axes = var_2160_axes_0, x = var_2160_batch_norm_1d_cast_fp16)[name = tensor<string, []>("op_2160_cast_fp16")];
        } -> (embedding);
}