code: def __init__(self, inplane):
      super(LocalAttenModule, self).__init__()
      self.dconv1 = nn.Sequential(
          nn.Conv2d(
              inplane, inplane, kernel_size=3, groups=inplane, stride=2
          ),
          BatchNorm2d(inplane),
          nn.ReLU(inplace=False),
      )
      self.dconv2 = nn.Sequential(
          nn.Conv2d(
              inplane, inplane, kernel_size=3, groups=inplane, stride=2
          ),
          BatchNorm2d(inplane),
          nn.ReLU(inplace=False),
      )
      self.dconv3 = nn.Sequential(
          nn.Conv2d(
              inplane, inplane, kernel_size=3, groups=inplane, stride=2
          ),
          BatchNorm2d(inplane),
          nn.ReLU(inplace=False),
      )
      self.sigmoid_spatial = nn.Sigmoid()
  
imports: import torch.nn
  import torch
  import torch.nn.functional
  from torch.nn import BatchNorm2d
label_desc: Use image node_id 1 to create a new LocalAttenModule object from inherited base classes: nn with example: obj = LocalAttenModule(inplane)