code: def __init__(self, channel, reduction=4):
      super(SEModule, 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),
          Hsigmoid()
          # nn.Sigmoid()
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new SEModule object from inherited base classes: nn with example: obj = SEModule(channel, reduction)