content: import torch
  import torch.nn as nn
  import torch.nn.functional as F
  
  class myResnet(nn.Module):
      def __init__(self, resnet):
          super(myResnet, self).__init__()
          self.resnet = resnet
  
      def forward(self, img, att_size=6):
          x = img
  
          x = self.resnet.conv1(x)
          x = self.resnet.bn1(x)
          x = self.resnet.relu(x)
          x = self.resnet.maxpool(x)
  
          x = self.resnet.layer1(x)
          x = self.resnet.layer2(x)
          x = self.resnet.layer3(x)
          x = self.resnet.layer4(x)
  
          fc = x.mean(3).mean(2).squeeze()
          att = F.adaptive_avg_pool2d(x,[att_size,att_size]).squeeze().permute(1, 2, 0)
          
          return fc, att
  
  