text: # Copyright (c) Microsoft Corporation.
  # Licensed under the MIT license.
  
  import torch
  
  
  class Stage13(torch.nn.Module):
      def __init__(self):
          super(Stage13, self).__init__()
          self.layer1 = torch.nn.ReLU(inplace=True)
          self.layer2 = torch.nn.Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          self.layer3 = torch.nn.ReLU(inplace=True)
          self._initialize_weights()
  
      def forward(self, input0):
          out0 = input0.clone()
          out1 = self.layer1(out0)
          out2 = self.layer2(out1)
          out3 = self.layer3(out2)
          return out3
  
      def _initialize_weights(self):
          for m in self.modules():
              if isinstance(m, torch.nn.Conv2d):
                  torch.nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
                  if m.bias is not None:
                      torch.nn.init.constant_(m.bias, 0)
              elif isinstance(m, torch.nn.BatchNorm2d):
                  torch.nn.init.constant_(m.weight, 1)
                  torch.nn.init.constant_(m.bias, 0)
              elif isinstance(m, torch.nn.Linear):
                  torch.nn.init.normal_(m.weight, 0, 0.01)
                  torch.nn.init.constant_(m.bias, 0)
  