code: def __init__(self, channels, reduction):
      super(SEModule, self).__init__()
      self.avg_pool = nn.AdaptiveAvgPool2d(1)
      self.fc1 = nn.Conv2d(
          channels, channels // reduction, kernel_size=1, padding=0
      )
      self.relu = nn.ReLU(inplace=True)
      self.fc2 = nn.Conv2d(
          channels // reduction, channels, kernel_size=1, padding=0
      )
      self.sigmoid = nn.Sigmoid()
  
imports: from __future__ import print_function, division, absolute_import
  from collections import OrderedDict
  import math
  import torch.nn
  from torch.utils import model_zoo
label_desc: Use image node_id 1 to create a new SEModule object from inherited base classes: nn with example: obj = SEModule(channels, reduction)