text: from collections import OrderedDict
  import torch
  import torch.nn as nn
  import torch.nn.functional as F
  from torch.nn.parameter import Parameter
  
  class Flatten(nn.Module):
      def forward(self, input):
          return input.view(input.size(0), -1)
  
  
  class BNInception(nn.Module):
  
      def __init__(self, need_bn = True):
          super(BNInception, self).__init__()
          inplace = True
          self.conv1_7x7_s2 = nn.Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3))
          self.conv1_7x7_s2_bn = nn.BatchNorm2d(64, affine=True)
          self.conv1_relu_7x7 = nn.ReLU(inplace)
          self.pool1_3x3_s2 = nn.MaxPool2d((3, 3), stride=(2, 2), dilation=(1, 1), ceil_mode=True)
          self.conv2_3x3_reduce = nn.Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))
          self.conv2_3x3_reduce_bn = nn.BatchNorm2d(64, affine=True)
          self.conv2_relu_3x3_reduce = nn.ReLU(inplace)
          self.conv2_3x3 = nn.Conv2d(64, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.conv2_3x3_bn = nn.BatchNorm2d(192, affine=True)
          self.conv2_relu_3x3 = nn.ReLU(inplace)
          self.pool2_3x3_s2 = nn.MaxPool2d((3, 3), stride=(2, 2), dilation=(1, 1), ceil_mode=True)
          self.inception_3a_1x1 = nn.Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3a_1x1_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3a_relu_1x1 = nn.ReLU(inplace)
          self.inception_3a_3x3_reduce = nn.Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3a_3x3_reduce_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3a_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_3a_3x3 = nn.Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_3a_3x3_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3a_relu_3x3 = nn.ReLU(inplace)
          self.inception_3a_double_3x3_reduce = nn.Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3a_double_3x3_reduce_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3a_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_3a_double_3x3_1 = nn.Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_3a_double_3x3_1_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_3a_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_3a_double_3x3_2 = nn.Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_3a_double_3x3_2_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_3a_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_3a_pool = nn.AvgPool2d(3, stride=1, padding=1, ceil_mode=True, count_include_pad=True)
          self.inception_3a_pool_proj = nn.Conv2d(192, 32, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3a_pool_proj_bn = nn.BatchNorm2d(32, affine=True)
          self.inception_3a_relu_pool_proj = nn.ReLU(inplace)
          self.inception_3b_1x1 = nn.Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3b_1x1_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3b_relu_1x1 = nn.ReLU(inplace)
          self.inception_3b_3x3_reduce = nn.Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3b_3x3_reduce_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3b_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_3b_3x3 = nn.Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_3b_3x3_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_3b_relu_3x3 = nn.ReLU(inplace)
          self.inception_3b_double_3x3_reduce = nn.Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3b_double_3x3_reduce_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3b_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_3b_double_3x3_1 = nn.Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_3b_double_3x3_1_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_3b_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_3b_double_3x3_2 = nn.Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_3b_double_3x3_2_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_3b_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_3b_pool = nn.AvgPool2d(3, stride=1, padding=1, ceil_mode=True, count_include_pad=True)
          self.inception_3b_pool_proj = nn.Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3b_pool_proj_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3b_relu_pool_proj = nn.ReLU(inplace)
          self.inception_3c_3x3_reduce = nn.Conv2d(320, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3c_3x3_reduce_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_3c_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_3c_3x3 = nn.Conv2d(128, 160, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
          self.inception_3c_3x3_bn = nn.BatchNorm2d(160, affine=True)
          self.inception_3c_relu_3x3 = nn.ReLU(inplace)
          self.inception_3c_double_3x3_reduce = nn.Conv2d(320, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_3c_double_3x3_reduce_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_3c_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_3c_double_3x3_1 = nn.Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_3c_double_3x3_1_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_3c_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_3c_double_3x3_2 = nn.Conv2d(96, 96, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
          self.inception_3c_double_3x3_2_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_3c_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_3c_pool = nn.MaxPool2d((3, 3), stride=(2, 2), dilation=(1, 1), ceil_mode=True)
          self.inception_4a_1x1 = nn.Conv2d(576, 224, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4a_1x1_bn = nn.BatchNorm2d(224, affine=True)
          self.inception_4a_relu_1x1 = nn.ReLU(inplace)
          self.inception_4a_3x3_reduce = nn.Conv2d(576, 64, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4a_3x3_reduce_bn = nn.BatchNorm2d(64, affine=True)
          self.inception_4a_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_4a_3x3 = nn.Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4a_3x3_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_4a_relu_3x3 = nn.ReLU(inplace)
          self.inception_4a_double_3x3_reduce = nn.Conv2d(576, 96, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4a_double_3x3_reduce_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_4a_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_4a_double_3x3_1 = nn.Conv2d(96, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4a_double_3x3_1_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4a_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_4a_double_3x3_2 = nn.Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4a_double_3x3_2_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4a_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_4a_pool = nn.AvgPool2d(3, stride=1, padding=1, ceil_mode=True, count_include_pad=True)
          self.inception_4a_pool_proj = nn.Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4a_pool_proj_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4a_relu_pool_proj = nn.ReLU(inplace)
          self.inception_4b_1x1 = nn.Conv2d(576, 192, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4b_1x1_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_4b_relu_1x1 = nn.ReLU(inplace)
          self.inception_4b_3x3_reduce = nn.Conv2d(576, 96, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4b_3x3_reduce_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_4b_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_4b_3x3 = nn.Conv2d(96, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4b_3x3_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4b_relu_3x3 = nn.ReLU(inplace)
          self.inception_4b_double_3x3_reduce = nn.Conv2d(576, 96, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4b_double_3x3_reduce_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_4b_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_4b_double_3x3_1 = nn.Conv2d(96, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4b_double_3x3_1_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4b_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_4b_double_3x3_2 = nn.Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4b_double_3x3_2_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4b_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_4b_pool = nn.AvgPool2d(3, stride=1, padding=1, ceil_mode=True, count_include_pad=True)
          self.inception_4b_pool_proj = nn.Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4b_pool_proj_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4b_relu_pool_proj = nn.ReLU(inplace)
          self.inception_4c_1x1 = nn.Conv2d(576, 160, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4c_1x1_bn = nn.BatchNorm2d(160, affine=True)
          self.inception_4c_relu_1x1 = nn.ReLU(inplace)
          self.inception_4c_3x3_reduce = nn.Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4c_3x3_reduce_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4c_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_4c_3x3 = nn.Conv2d(128, 160, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4c_3x3_bn = nn.BatchNorm2d(160, affine=True)
          self.inception_4c_relu_3x3 = nn.ReLU(inplace)
          self.inception_4c_double_3x3_reduce = nn.Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4c_double_3x3_reduce_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4c_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_4c_double_3x3_1 = nn.Conv2d(128, 160, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4c_double_3x3_1_bn = nn.BatchNorm2d(160, affine=True)
          self.inception_4c_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_4c_double_3x3_2 = nn.Conv2d(160, 160, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4c_double_3x3_2_bn = nn.BatchNorm2d(160, affine=True)
          self.inception_4c_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_4c_pool = nn.AvgPool2d(3, stride=1, padding=1, ceil_mode=True, count_include_pad=True)
          self.inception_4c_pool_proj = nn.Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4c_pool_proj_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4c_relu_pool_proj = nn.ReLU(inplace)
          self.inception_4d_1x1 = nn.Conv2d(608, 96, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4d_1x1_bn = nn.BatchNorm2d(96, affine=True)
          self.inception_4d_relu_1x1 = nn.ReLU(inplace)
          self.inception_4d_3x3_reduce = nn.Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4d_3x3_reduce_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4d_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_4d_3x3 = nn.Conv2d(128, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4d_3x3_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_4d_relu_3x3 = nn.ReLU(inplace)
          self.inception_4d_double_3x3_reduce = nn.Conv2d(608, 160, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4d_double_3x3_reduce_bn = nn.BatchNorm2d(160, affine=True)
          self.inception_4d_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_4d_double_3x3_1 = nn.Conv2d(160, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4d_double_3x3_1_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_4d_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_4d_double_3x3_2 = nn.Conv2d(192, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4d_double_3x3_2_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_4d_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_4d_pool = nn.AvgPool2d(3, stride=1, padding=1, ceil_mode=True, count_include_pad=True)
          self.inception_4d_pool_proj = nn.Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4d_pool_proj_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4d_relu_pool_proj = nn.ReLU(inplace)
          self.inception_4e_3x3_reduce = nn.Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4e_3x3_reduce_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_4e_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_4e_3x3 = nn.Conv2d(128, 192, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
          self.inception_4e_3x3_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_4e_relu_3x3 = nn.ReLU(inplace)
          self.inception_4e_double_3x3_reduce = nn.Conv2d(608, 192, kernel_size=(1, 1), stride=(1, 1))
          self.inception_4e_double_3x3_reduce_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_4e_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_4e_double_3x3_1 = nn.Conv2d(192, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_4e_double_3x3_1_bn = nn.BatchNorm2d(256, affine=True)
          self.inception_4e_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_4e_double_3x3_2 = nn.Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
          self.inception_4e_double_3x3_2_bn = nn.BatchNorm2d(256, affine=True)
          self.inception_4e_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_4e_pool = nn.MaxPool2d((3, 3), stride=(2, 2), dilation=(1, 1), ceil_mode=True)
          self.inception_5a_1x1 = nn.Conv2d(1056, 352, kernel_size=(1, 1), stride=(1, 1))
          self.inception_5a_1x1_bn = nn.BatchNorm2d(352, affine=True)
          self.inception_5a_relu_1x1 = nn.ReLU(inplace)
          self.inception_5a_3x3_reduce = nn.Conv2d(1056, 192, kernel_size=(1, 1), stride=(1, 1))
          self.inception_5a_3x3_reduce_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_5a_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_5a_3x3 = nn.Conv2d(192, 320, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_5a_3x3_bn = nn.BatchNorm2d(320, affine=True)
          self.inception_5a_relu_3x3 = nn.ReLU(inplace)
          self.inception_5a_double_3x3_reduce = nn.Conv2d(1056, 160, kernel_size=(1, 1), stride=(1, 1))
          self.inception_5a_double_3x3_reduce_bn = nn.BatchNorm2d(160, affine=True)
          self.inception_5a_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_5a_double_3x3_1 = nn.Conv2d(160, 224, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_5a_double_3x3_1_bn = nn.BatchNorm2d(224, affine=True)
          self.inception_5a_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_5a_double_3x3_2 = nn.Conv2d(224, 224, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_5a_double_3x3_2_bn = nn.BatchNorm2d(224, affine=True)
          self.inception_5a_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_5a_pool = nn.AvgPool2d(3, stride=1, padding=1, ceil_mode=True, count_include_pad=True)
          self.inception_5a_pool_proj = nn.Conv2d(1056, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_5a_pool_proj_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_5a_relu_pool_proj = nn.ReLU(inplace)
          self.inception_5b_1x1 = nn.Conv2d(1024, 352, kernel_size=(1, 1), stride=(1, 1))
          self.inception_5b_1x1_bn = nn.BatchNorm2d(352, affine=True)
          self.inception_5b_relu_1x1 = nn.ReLU(inplace)
          self.inception_5b_3x3_reduce = nn.Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1))
          self.inception_5b_3x3_reduce_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_5b_relu_3x3_reduce = nn.ReLU(inplace)
          self.inception_5b_3x3 = nn.Conv2d(192, 320, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_5b_3x3_bn = nn.BatchNorm2d(320, affine=True)
          self.inception_5b_relu_3x3 = nn.ReLU(inplace)
          self.inception_5b_double_3x3_reduce = nn.Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1))
          self.inception_5b_double_3x3_reduce_bn = nn.BatchNorm2d(192, affine=True)
          self.inception_5b_relu_double_3x3_reduce = nn.ReLU(inplace)
          self.inception_5b_double_3x3_1 = nn.Conv2d(192, 224, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_5b_double_3x3_1_bn = nn.BatchNorm2d(224, affine=True)
          self.inception_5b_relu_double_3x3_1 = nn.ReLU(inplace)
          self.inception_5b_double_3x3_2 = nn.Conv2d(224, 224, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.inception_5b_double_3x3_2_bn = nn.BatchNorm2d(224, affine=True)
          self.inception_5b_relu_double_3x3_2 = nn.ReLU(inplace)
          self.inception_5b_pool = nn.MaxPool2d((3, 3), stride=(1, 1), padding=(1, 1), dilation=(1, 1), ceil_mode=True)
          self.inception_5b_pool_proj = nn.Conv2d(1024, 128, kernel_size=(1, 1), stride=(1, 1))
          self.inception_5b_pool_proj_bn = nn.BatchNorm2d(128, affine=True)
          self.inception_5b_relu_pool_proj = nn.ReLU(inplace)
  
          if need_bn:
              self.head = nn.Sequential(OrderedDict([
                  ('avgpool', nn.AdaptiveAvgPool2d(1)),
                  ('bn', nn.BatchNorm2d(1024, eps=1e-5)),
                  ('flatten', Flatten()),
                  ('fc', nn.Linear(in_features=1024, out_features=512)),
              ]))
          else:
              self.head = nn.Sequential(OrderedDict([
                  ('avgpool', nn.AdaptiveAvgPool2d(1)),
                  ('flatten', Flatten()),
                  ('fc', nn.Linear(in_features=1024, out_features=512)),
              ]))
  
      def features(self, input):
          conv1_7x7_s2_out = self.conv1_7x7_s2(input)
          conv1_7x7_s2_bn_out = self.conv1_7x7_s2_bn(conv1_7x7_s2_out)
          conv1_relu_7x7_out = self.conv1_relu_7x7(conv1_7x7_s2_bn_out)
          pool1_3x3_s2_out = self.pool1_3x3_s2(conv1_relu_7x7_out)
          conv2_3x3_reduce_out = self.conv2_3x3_reduce(pool1_3x3_s2_out)
          conv2_3x3_reduce_bn_out = self.conv2_3x3_reduce_bn(conv2_3x3_reduce_out)
          conv2_relu_3x3_reduce_out = self.conv2_relu_3x3_reduce(conv2_3x3_reduce_bn_out)
          conv2_3x3_out = self.conv2_3x3(conv2_relu_3x3_reduce_out)
          conv2_3x3_bn_out = self.conv2_3x3_bn(conv2_3x3_out)
          conv2_relu_3x3_out = self.conv2_relu_3x3(conv2_3x3_bn_out)
          pool2_3x3_s2_out = self.pool2_3x3_s2(conv2_relu_3x3_out)
  
          inception_3a_1x1_out = self.inception_3a_1x1(pool2_3x3_s2_out)
          inception_3a_1x1_bn_out = self.inception_3a_1x1_bn(inception_3a_1x1_out)
          inception_3a_relu_1x1_out = self.inception_3a_relu_1x1(inception_3a_1x1_bn_out)
          inception_3a_3x3_reduce_out = self.inception_3a_3x3_reduce(pool2_3x3_s2_out)
          inception_3a_3x3_reduce_bn_out = self.inception_3a_3x3_reduce_bn(inception_3a_3x3_reduce_out)
          inception_3a_relu_3x3_reduce_out = self.inception_3a_relu_3x3_reduce(inception_3a_3x3_reduce_bn_out)
          inception_3a_3x3_out = self.inception_3a_3x3(inception_3a_relu_3x3_reduce_out)
          inception_3a_3x3_bn_out = self.inception_3a_3x3_bn(inception_3a_3x3_out)
          inception_3a_relu_3x3_out = self.inception_3a_relu_3x3(inception_3a_3x3_bn_out)
          inception_3a_double_3x3_reduce_out = self.inception_3a_double_3x3_reduce(pool2_3x3_s2_out)
          inception_3a_double_3x3_reduce_bn_out = self.inception_3a_double_3x3_reduce_bn(
              inception_3a_double_3x3_reduce_out)
          inception_3a_relu_double_3x3_reduce_out = self.inception_3a_relu_double_3x3_reduce(
              inception_3a_double_3x3_reduce_bn_out)
          inception_3a_double_3x3_1_out = self.inception_3a_double_3x3_1(inception_3a_relu_double_3x3_reduce_out)
          inception_3a_double_3x3_1_bn_out = self.inception_3a_double_3x3_1_bn(inception_3a_double_3x3_1_out)
          inception_3a_relu_double_3x3_1_out = self.inception_3a_relu_double_3x3_1(inception_3a_double_3x3_1_bn_out)
          inception_3a_double_3x3_2_out = self.inception_3a_double_3x3_2(inception_3a_relu_double_3x3_1_out)
          inception_3a_double_3x3_2_bn_out = self.inception_3a_double_3x3_2_bn(inception_3a_double_3x3_2_out)
          inception_3a_relu_double_3x3_2_out = self.inception_3a_relu_double_3x3_2(inception_3a_double_3x3_2_bn_out)
          inception_3a_pool_out = self.inception_3a_pool(pool2_3x3_s2_out)
          inception_3a_pool_proj_out = self.inception_3a_pool_proj(inception_3a_pool_out)
          inception_3a_pool_proj_bn_out = self.inception_3a_pool_proj_bn(inception_3a_pool_proj_out)
          inception_3a_relu_pool_proj_out = self.inception_3a_relu_pool_proj(inception_3a_pool_proj_bn_out)
          inception_3a_output_out = torch.cat(
              [inception_3a_relu_1x1_out, inception_3a_relu_3x3_out, inception_3a_relu_double_3x3_2_out,
               inception_3a_relu_pool_proj_out], 1)
  
          inception_3b_1x1_out = self.inception_3b_1x1(inception_3a_output_out)
          inception_3b_1x1_bn_out = self.inception_3b_1x1_bn(inception_3b_1x1_out)
          inception_3b_relu_1x1_out = self.inception_3b_relu_1x1(inception_3b_1x1_bn_out)
          inception_3b_3x3_reduce_out = self.inception_3b_3x3_reduce(inception_3a_output_out)
          inception_3b_3x3_reduce_bn_out = self.inception_3b_3x3_reduce_bn(inception_3b_3x3_reduce_out)
          inception_3b_relu_3x3_reduce_out = self.inception_3b_relu_3x3_reduce(inception_3b_3x3_reduce_bn_out)
          inception_3b_3x3_out = self.inception_3b_3x3(inception_3b_relu_3x3_reduce_out)
          inception_3b_3x3_bn_out = self.inception_3b_3x3_bn(inception_3b_3x3_out)
          inception_3b_relu_3x3_out = self.inception_3b_relu_3x3(inception_3b_3x3_bn_out)
          inception_3b_double_3x3_reduce_out = self.inception_3b_double_3x3_reduce(inception_3a_output_out)
          inception_3b_double_3x3_reduce_bn_out = self.inception_3b_double_3x3_reduce_bn(
              inception_3b_double_3x3_reduce_out)
          inception_3b_relu_double_3x3_reduce_out = self.inception_3b_relu_double_3x3_reduce(
              inception_3b_double_3x3_reduce_bn_out)
          inception_3b_double_3x3_1_out = self.inception_3b_double_3x3_1(inception_3b_relu_double_3x3_reduce_out)
          inception_3b_double_3x3_1_bn_out = self.inception_3b_double_3x3_1_bn(inception_3b_double_3x3_1_out)
          inception_3b_relu_double_3x3_1_out = self.inception_3b_relu_double_3x3_1(inception_3b_double_3x3_1_bn_out)
          inception_3b_double_3x3_2_out = self.inception_3b_double_3x3_2(inception_3b_relu_double_3x3_1_out)
          inception_3b_double_3x3_2_bn_out = self.inception_3b_double_3x3_2_bn(inception_3b_double_3x3_2_out)
          inception_3b_relu_double_3x3_2_out = self.inception_3b_relu_double_3x3_2(inception_3b_double_3x3_2_bn_out)
          inception_3b_pool_out = self.inception_3b_pool(inception_3a_output_out)
          inception_3b_pool_proj_out = self.inception_3b_pool_proj(inception_3b_pool_out)
          inception_3b_pool_proj_bn_out = self.inception_3b_pool_proj_bn(inception_3b_pool_proj_out)
          inception_3b_relu_pool_proj_out = self.inception_3b_relu_pool_proj(inception_3b_pool_proj_bn_out)
          inception_3b_output_out = torch.cat(
              [inception_3b_relu_1x1_out, inception_3b_relu_3x3_out, inception_3b_relu_double_3x3_2_out,
               inception_3b_relu_pool_proj_out], 1)
  
          inception_3c_3x3_reduce_out = self.inception_3c_3x3_reduce(inception_3b_output_out)
          inception_3c_3x3_reduce_bn_out = self.inception_3c_3x3_reduce_bn(inception_3c_3x3_reduce_out)
          inception_3c_relu_3x3_reduce_out = self.inception_3c_relu_3x3_reduce(inception_3c_3x3_reduce_bn_out)
          inception_3c_3x3_out = self.inception_3c_3x3(inception_3c_relu_3x3_reduce_out)
          inception_3c_3x3_bn_out = self.inception_3c_3x3_bn(inception_3c_3x3_out)
          inception_3c_relu_3x3_out = self.inception_3c_relu_3x3(inception_3c_3x3_bn_out)
          inception_3c_double_3x3_reduce_out = self.inception_3c_double_3x3_reduce(inception_3b_output_out)
          inception_3c_double_3x3_reduce_bn_out = self.inception_3c_double_3x3_reduce_bn(
              inception_3c_double_3x3_reduce_out)
          inception_3c_relu_double_3x3_reduce_out = self.inception_3c_relu_double_3x3_reduce(
              inception_3c_double_3x3_reduce_bn_out)
          inception_3c_double_3x3_1_out = self.inception_3c_double_3x3_1(inception_3c_relu_double_3x3_reduce_out)
          inception_3c_double_3x3_1_bn_out = self.inception_3c_double_3x3_1_bn(inception_3c_double_3x3_1_out)
          inception_3c_relu_double_3x3_1_out = self.inception_3c_relu_double_3x3_1(inception_3c_double_3x3_1_bn_out)
          inception_3c_double_3x3_2_out = self.inception_3c_double_3x3_2(inception_3c_relu_double_3x3_1_out)
          inception_3c_double_3x3_2_bn_out = self.inception_3c_double_3x3_2_bn(inception_3c_double_3x3_2_out)
          inception_3c_relu_double_3x3_2_out = self.inception_3c_relu_double_3x3_2(inception_3c_double_3x3_2_bn_out)
          inception_3c_pool_out = self.inception_3c_pool(inception_3b_output_out)
          inception_3c_output_out = torch.cat(
              [inception_3c_relu_3x3_out, inception_3c_relu_double_3x3_2_out, inception_3c_pool_out], 1)
  
          inception_4a_1x1_out = self.inception_4a_1x1(inception_3c_output_out)
          inception_4a_1x1_bn_out = self.inception_4a_1x1_bn(inception_4a_1x1_out)
          inception_4a_relu_1x1_out = self.inception_4a_relu_1x1(inception_4a_1x1_bn_out)
          inception_4a_3x3_reduce_out = self.inception_4a_3x3_reduce(inception_3c_output_out)
          inception_4a_3x3_reduce_bn_out = self.inception_4a_3x3_reduce_bn(inception_4a_3x3_reduce_out)
          inception_4a_relu_3x3_reduce_out = self.inception_4a_relu_3x3_reduce(inception_4a_3x3_reduce_bn_out)
          inception_4a_3x3_out = self.inception_4a_3x3(inception_4a_relu_3x3_reduce_out)
          inception_4a_3x3_bn_out = self.inception_4a_3x3_bn(inception_4a_3x3_out)
          inception_4a_relu_3x3_out = self.inception_4a_relu_3x3(inception_4a_3x3_bn_out)
          inception_4a_double_3x3_reduce_out = self.inception_4a_double_3x3_reduce(inception_3c_output_out)
          inception_4a_double_3x3_reduce_bn_out = self.inception_4a_double_3x3_reduce_bn(
              inception_4a_double_3x3_reduce_out)
          inception_4a_relu_double_3x3_reduce_out = self.inception_4a_relu_double_3x3_reduce(
              inception_4a_double_3x3_reduce_bn_out)
          inception_4a_double_3x3_1_out = self.inception_4a_double_3x3_1(inception_4a_relu_double_3x3_reduce_out)
          inception_4a_double_3x3_1_bn_out = self.inception_4a_double_3x3_1_bn(inception_4a_double_3x3_1_out)
          inception_4a_relu_double_3x3_1_out = self.inception_4a_relu_double_3x3_1(inception_4a_double_3x3_1_bn_out)
          inception_4a_double_3x3_2_out = self.inception_4a_double_3x3_2(inception_4a_relu_double_3x3_1_out)
          inception_4a_double_3x3_2_bn_out = self.inception_4a_double_3x3_2_bn(inception_4a_double_3x3_2_out)
          inception_4a_relu_double_3x3_2_out = self.inception_4a_relu_double_3x3_2(inception_4a_double_3x3_2_bn_out)
          inception_4a_pool_out = self.inception_4a_pool(inception_3c_output_out)
          inception_4a_pool_proj_out = self.inception_4a_pool_proj(inception_4a_pool_out)
          inception_4a_pool_proj_bn_out = self.inception_4a_pool_proj_bn(inception_4a_pool_proj_out)
          inception_4a_relu_pool_proj_out = self.inception_4a_relu_pool_proj(inception_4a_pool_proj_bn_out)
          inception_4a_output_out = torch.cat(
              [inception_4a_relu_1x1_out, inception_4a_relu_3x3_out, inception_4a_relu_double_3x3_2_out,
               inception_4a_relu_pool_proj_out], 1)
  
          inception_4b_1x1_out = self.inception_4b_1x1(inception_4a_output_out)
          inception_4b_1x1_bn_out = self.inception_4b_1x1_bn(inception_4b_1x1_out)
          inception_4b_relu_1x1_out = self.inception_4b_relu_1x1(inception_4b_1x1_bn_out)
          inception_4b_3x3_reduce_out = self.inception_4b_3x3_reduce(inception_4a_output_out)
          inception_4b_3x3_reduce_bn_out = self.inception_4b_3x3_reduce_bn(inception_4b_3x3_reduce_out)
          inception_4b_relu_3x3_reduce_out = self.inception_4b_relu_3x3_reduce(inception_4b_3x3_reduce_bn_out)
          inception_4b_3x3_out = self.inception_4b_3x3(inception_4b_relu_3x3_reduce_out)
          inception_4b_3x3_bn_out = self.inception_4b_3x3_bn(inception_4b_3x3_out)
          inception_4b_relu_3x3_out = self.inception_4b_relu_3x3(inception_4b_3x3_bn_out)
          inception_4b_double_3x3_reduce_out = self.inception_4b_double_3x3_reduce(inception_4a_output_out)
          inception_4b_double_3x3_reduce_bn_out = self.inception_4b_double_3x3_reduce_bn(
              inception_4b_double_3x3_reduce_out)
          inception_4b_relu_double_3x3_reduce_out = self.inception_4b_relu_double_3x3_reduce(
              inception_4b_double_3x3_reduce_bn_out)
          inception_4b_double_3x3_1_out = self.inception_4b_double_3x3_1(inception_4b_relu_double_3x3_reduce_out)
          inception_4b_double_3x3_1_bn_out = self.inception_4b_double_3x3_1_bn(inception_4b_double_3x3_1_out)
          inception_4b_relu_double_3x3_1_out = self.inception_4b_relu_double_3x3_1(inception_4b_double_3x3_1_bn_out)
          inception_4b_double_3x3_2_out = self.inception_4b_double_3x3_2(inception_4b_relu_double_3x3_1_out)
          inception_4b_double_3x3_2_bn_out = self.inception_4b_double_3x3_2_bn(inception_4b_double_3x3_2_out)
          inception_4b_relu_double_3x3_2_out = self.inception_4b_relu_double_3x3_2(inception_4b_double_3x3_2_bn_out)
          inception_4b_pool_out = self.inception_4b_pool(inception_4a_output_out)
          inception_4b_pool_proj_out = self.inception_4b_pool_proj(inception_4b_pool_out)
          inception_4b_pool_proj_bn_out = self.inception_4b_pool_proj_bn(inception_4b_pool_proj_out)
          inception_4b_relu_pool_proj_out = self.inception_4b_relu_pool_proj(inception_4b_pool_proj_bn_out)
          inception_4b_output_out = torch.cat(
              [inception_4b_relu_1x1_out, inception_4b_relu_3x3_out, inception_4b_relu_double_3x3_2_out,
               inception_4b_relu_pool_proj_out], 1)
  
          inception_4c_1x1_out = self.inception_4c_1x1(inception_4b_output_out)
          inception_4c_1x1_bn_out = self.inception_4c_1x1_bn(inception_4c_1x1_out)
          inception_4c_relu_1x1_out = self.inception_4c_relu_1x1(inception_4c_1x1_bn_out)
          inception_4c_3x3_reduce_out = self.inception_4c_3x3_reduce(inception_4b_output_out)
          inception_4c_3x3_reduce_bn_out = self.inception_4c_3x3_reduce_bn(inception_4c_3x3_reduce_out)
          inception_4c_relu_3x3_reduce_out = self.inception_4c_relu_3x3_reduce(inception_4c_3x3_reduce_bn_out)
          inception_4c_3x3_out = self.inception_4c_3x3(inception_4c_relu_3x3_reduce_out)
          inception_4c_3x3_bn_out = self.inception_4c_3x3_bn(inception_4c_3x3_out)
          inception_4c_relu_3x3_out = self.inception_4c_relu_3x3(inception_4c_3x3_bn_out)
          inception_4c_double_3x3_reduce_out = self.inception_4c_double_3x3_reduce(inception_4b_output_out)
          inception_4c_double_3x3_reduce_bn_out = self.inception_4c_double_3x3_reduce_bn(
              inception_4c_double_3x3_reduce_out)
          inception_4c_relu_double_3x3_reduce_out = self.inception_4c_relu_double_3x3_reduce(
              inception_4c_double_3x3_reduce_bn_out)
          inception_4c_double_3x3_1_out = self.inception_4c_double_3x3_1(inception_4c_relu_double_3x3_reduce_out)
          inception_4c_double_3x3_1_bn_out = self.inception_4c_double_3x3_1_bn(inception_4c_double_3x3_1_out)
          inception_4c_relu_double_3x3_1_out = self.inception_4c_relu_double_3x3_1(inception_4c_double_3x3_1_bn_out)
          inception_4c_double_3x3_2_out = self.inception_4c_double_3x3_2(inception_4c_relu_double_3x3_1_out)
          inception_4c_double_3x3_2_bn_out = self.inception_4c_double_3x3_2_bn(inception_4c_double_3x3_2_out)
          inception_4c_relu_double_3x3_2_out = self.inception_4c_relu_double_3x3_2(inception_4c_double_3x3_2_bn_out)
          inception_4c_pool_out = self.inception_4c_pool(inception_4b_output_out)
          inception_4c_pool_proj_out = self.inception_4c_pool_proj(inception_4c_pool_out)
          inception_4c_pool_proj_bn_out = self.inception_4c_pool_proj_bn(inception_4c_pool_proj_out)
          inception_4c_relu_pool_proj_out = self.inception_4c_relu_pool_proj(inception_4c_pool_proj_bn_out)
          inception_4c_output_out = torch.cat(
              [inception_4c_relu_1x1_out, inception_4c_relu_3x3_out, inception_4c_relu_double_3x3_2_out,
               inception_4c_relu_pool_proj_out], 1)
  
          inception_4d_1x1_out = self.inception_4d_1x1(inception_4c_output_out)
          inception_4d_1x1_bn_out = self.inception_4d_1x1_bn(inception_4d_1x1_out)
          inception_4d_relu_1x1_out = self.inception_4d_relu_1x1(inception_4d_1x1_bn_out)
          inception_4d_3x3_reduce_out = self.inception_4d_3x3_reduce(inception_4c_output_out)
          inception_4d_3x3_reduce_bn_out = self.inception_4d_3x3_reduce_bn(inception_4d_3x3_reduce_out)
          inception_4d_relu_3x3_reduce_out = self.inception_4d_relu_3x3_reduce(inception_4d_3x3_reduce_bn_out)
          inception_4d_3x3_out = self.inception_4d_3x3(inception_4d_relu_3x3_reduce_out)
          inception_4d_3x3_bn_out = self.inception_4d_3x3_bn(inception_4d_3x3_out)
          inception_4d_relu_3x3_out = self.inception_4d_relu_3x3(inception_4d_3x3_bn_out)
          inception_4d_double_3x3_reduce_out = self.inception_4d_double_3x3_reduce(inception_4c_output_out)
          inception_4d_double_3x3_reduce_bn_out = self.inception_4d_double_3x3_reduce_bn(
              inception_4d_double_3x3_reduce_out)
          inception_4d_relu_double_3x3_reduce_out = self.inception_4d_relu_double_3x3_reduce(
              inception_4d_double_3x3_reduce_bn_out)
          inception_4d_double_3x3_1_out = self.inception_4d_double_3x3_1(inception_4d_relu_double_3x3_reduce_out)
          inception_4d_double_3x3_1_bn_out = self.inception_4d_double_3x3_1_bn(inception_4d_double_3x3_1_out)
          inception_4d_relu_double_3x3_1_out = self.inception_4d_relu_double_3x3_1(inception_4d_double_3x3_1_bn_out)
          inception_4d_double_3x3_2_out = self.inception_4d_double_3x3_2(inception_4d_relu_double_3x3_1_out)
          inception_4d_double_3x3_2_bn_out = self.inception_4d_double_3x3_2_bn(inception_4d_double_3x3_2_out)
          inception_4d_relu_double_3x3_2_out = self.inception_4d_relu_double_3x3_2(inception_4d_double_3x3_2_bn_out)
          inception_4d_pool_out = self.inception_4d_pool(inception_4c_output_out)
          inception_4d_pool_proj_out = self.inception_4d_pool_proj(inception_4d_pool_out)
          inception_4d_pool_proj_bn_out = self.inception_4d_pool_proj_bn(inception_4d_pool_proj_out)
          inception_4d_relu_pool_proj_out = self.inception_4d_relu_pool_proj(inception_4d_pool_proj_bn_out)
          inception_4d_output_out = torch.cat(
              [inception_4d_relu_1x1_out, inception_4d_relu_3x3_out, inception_4d_relu_double_3x3_2_out,
               inception_4d_relu_pool_proj_out], 1)
  
          inception_4e_3x3_reduce_out = self.inception_4e_3x3_reduce(inception_4d_output_out)
          inception_4e_3x3_reduce_bn_out = self.inception_4e_3x3_reduce_bn(inception_4e_3x3_reduce_out)
          inception_4e_relu_3x3_reduce_out = self.inception_4e_relu_3x3_reduce(inception_4e_3x3_reduce_bn_out)
          inception_4e_3x3_out = self.inception_4e_3x3(inception_4e_relu_3x3_reduce_out)
          inception_4e_3x3_bn_out = self.inception_4e_3x3_bn(inception_4e_3x3_out)
          inception_4e_relu_3x3_out = self.inception_4e_relu_3x3(inception_4e_3x3_bn_out)
          inception_4e_double_3x3_reduce_out = self.inception_4e_double_3x3_reduce(inception_4d_output_out)
          inception_4e_double_3x3_reduce_bn_out = self.inception_4e_double_3x3_reduce_bn(
              inception_4e_double_3x3_reduce_out)
          inception_4e_relu_double_3x3_reduce_out = self.inception_4e_relu_double_3x3_reduce(
              inception_4e_double_3x3_reduce_bn_out)
          inception_4e_double_3x3_1_out = self.inception_4e_double_3x3_1(inception_4e_relu_double_3x3_reduce_out)
          inception_4e_double_3x3_1_bn_out = self.inception_4e_double_3x3_1_bn(inception_4e_double_3x3_1_out)
          inception_4e_relu_double_3x3_1_out = self.inception_4e_relu_double_3x3_1(inception_4e_double_3x3_1_bn_out)
          inception_4e_double_3x3_2_out = self.inception_4e_double_3x3_2(inception_4e_relu_double_3x3_1_out)
          inception_4e_double_3x3_2_bn_out = self.inception_4e_double_3x3_2_bn(inception_4e_double_3x3_2_out)
          inception_4e_relu_double_3x3_2_out = self.inception_4e_relu_double_3x3_2(inception_4e_double_3x3_2_bn_out)
          inception_4e_pool_out = self.inception_4e_pool(inception_4d_output_out)
          inception_4e_output_out = torch.cat(
              [inception_4e_relu_3x3_out, inception_4e_relu_double_3x3_2_out, inception_4e_pool_out], 1)
  
          inception_5a_1x1_out = self.inception_5a_1x1(inception_4e_output_out)
          inception_5a_1x1_bn_out = self.inception_5a_1x1_bn(inception_5a_1x1_out)
          inception_5a_relu_1x1_out = self.inception_5a_relu_1x1(inception_5a_1x1_bn_out)
          inception_5a_3x3_reduce_out = self.inception_5a_3x3_reduce(inception_4e_output_out)
          inception_5a_3x3_reduce_bn_out = self.inception_5a_3x3_reduce_bn(inception_5a_3x3_reduce_out)
          inception_5a_relu_3x3_reduce_out = self.inception_5a_relu_3x3_reduce(inception_5a_3x3_reduce_bn_out)
          inception_5a_3x3_out = self.inception_5a_3x3(inception_5a_relu_3x3_reduce_out)
          inception_5a_3x3_bn_out = self.inception_5a_3x3_bn(inception_5a_3x3_out)
          inception_5a_relu_3x3_out = self.inception_5a_relu_3x3(inception_5a_3x3_bn_out)
          inception_5a_double_3x3_reduce_out = self.inception_5a_double_3x3_reduce(inception_4e_output_out)
          inception_5a_double_3x3_reduce_bn_out = self.inception_5a_double_3x3_reduce_bn(
              inception_5a_double_3x3_reduce_out)
          inception_5a_relu_double_3x3_reduce_out = self.inception_5a_relu_double_3x3_reduce(
              inception_5a_double_3x3_reduce_bn_out)
          inception_5a_double_3x3_1_out = self.inception_5a_double_3x3_1(inception_5a_relu_double_3x3_reduce_out)
          inception_5a_double_3x3_1_bn_out = self.inception_5a_double_3x3_1_bn(inception_5a_double_3x3_1_out)
          inception_5a_relu_double_3x3_1_out = self.inception_5a_relu_double_3x3_1(inception_5a_double_3x3_1_bn_out)
          inception_5a_double_3x3_2_out = self.inception_5a_double_3x3_2(inception_5a_relu_double_3x3_1_out)
          inception_5a_double_3x3_2_bn_out = self.inception_5a_double_3x3_2_bn(inception_5a_double_3x3_2_out)
          inception_5a_relu_double_3x3_2_out = self.inception_5a_relu_double_3x3_2(inception_5a_double_3x3_2_bn_out)
          inception_5a_pool_out = self.inception_5a_pool(inception_4e_output_out)
          inception_5a_pool_proj_out = self.inception_5a_pool_proj(inception_5a_pool_out)
          inception_5a_pool_proj_bn_out = self.inception_5a_pool_proj_bn(inception_5a_pool_proj_out)
          inception_5a_relu_pool_proj_out = self.inception_5a_relu_pool_proj(inception_5a_pool_proj_bn_out)
          inception_5a_output_out = torch.cat(
              [inception_5a_relu_1x1_out, inception_5a_relu_3x3_out, inception_5a_relu_double_3x3_2_out,
               inception_5a_relu_pool_proj_out], 1)
  
          inception_5b_1x1_out = self.inception_5b_1x1(inception_5a_output_out)
          inception_5b_1x1_bn_out = self.inception_5b_1x1_bn(inception_5b_1x1_out)
          inception_5b_relu_1x1_out = self.inception_5b_relu_1x1(inception_5b_1x1_bn_out)
          inception_5b_3x3_reduce_out = self.inception_5b_3x3_reduce(inception_5a_output_out)
          inception_5b_3x3_reduce_bn_out = self.inception_5b_3x3_reduce_bn(inception_5b_3x3_reduce_out)
          inception_5b_relu_3x3_reduce_out = self.inception_5b_relu_3x3_reduce(inception_5b_3x3_reduce_bn_out)
          inception_5b_3x3_out = self.inception_5b_3x3(inception_5b_relu_3x3_reduce_out)
          inception_5b_3x3_bn_out = self.inception_5b_3x3_bn(inception_5b_3x3_out)
          inception_5b_relu_3x3_out = self.inception_5b_relu_3x3(inception_5b_3x3_bn_out)
          inception_5b_double_3x3_reduce_out = self.inception_5b_double_3x3_reduce(inception_5a_output_out)
          inception_5b_double_3x3_reduce_bn_out = self.inception_5b_double_3x3_reduce_bn(
              inception_5b_double_3x3_reduce_out)
          inception_5b_relu_double_3x3_reduce_out = self.inception_5b_relu_double_3x3_reduce(
              inception_5b_double_3x3_reduce_bn_out)
          inception_5b_double_3x3_1_out = self.inception_5b_double_3x3_1(inception_5b_relu_double_3x3_reduce_out)
          inception_5b_double_3x3_1_bn_out = self.inception_5b_double_3x3_1_bn(inception_5b_double_3x3_1_out)
          inception_5b_relu_double_3x3_1_out = self.inception_5b_relu_double_3x3_1(inception_5b_double_3x3_1_bn_out)
          inception_5b_double_3x3_2_out = self.inception_5b_double_3x3_2(inception_5b_relu_double_3x3_1_out)
          inception_5b_double_3x3_2_bn_out = self.inception_5b_double_3x3_2_bn(inception_5b_double_3x3_2_out)
          inception_5b_relu_double_3x3_2_out = self.inception_5b_relu_double_3x3_2(inception_5b_double_3x3_2_bn_out)
          inception_5b_pool_out = self.inception_5b_pool(inception_5a_output_out)
          inception_5b_pool_proj_out = self.inception_5b_pool_proj(inception_5b_pool_out)
          inception_5b_pool_proj_bn_out = self.inception_5b_pool_proj_bn(inception_5b_pool_proj_out)
          inception_5b_relu_pool_proj_out = self.inception_5b_relu_pool_proj(inception_5b_pool_proj_bn_out)
          inception_5b_output_out = torch.cat(
              [inception_5b_relu_1x1_out, inception_5b_relu_3x3_out, inception_5b_relu_double_3x3_2_out,
               inception_5b_relu_pool_proj_out], 1)
  
          return inception_5b_output_out
  
      def forward(self, input, normalized=False):
          bbout = self.features(input)
          x = self.head(bbout)
  
          if normalized:
              norm = x.norm(dim=1, p=2, keepdim=True)
              x = x.div(norm.expand_as(x))
  
          return x
  