text: import torch
  import torch.nn as nn
  
  
  class SELayer(nn.Module):
      def __init__(self, channel, reduction=16):
          super(SELayer, self).__init__()
          self.avg_pool = nn.AdaptiveAvgPool2d(1)
          self.fc = nn.Sequential(
              nn.Linear(channel, channel // reduction, bias=False),
              nn.ReLU(inplace=True),
              nn.Linear(channel // reduction, channel, bias=False),
              nn.Sigmoid()
          )
  
      def forward(self, x):
          b, c, _, _ = x.size()
          y = self.avg_pool(x).view(b, c)
          y = self.fc(y).view(b, c, 1, 1)
          return x * y.expand_as(x)
  