code: def __init__(self, nIn, d=1, kSize=3, dkSize=3):
      super().__init__()
  
      self.bn_relu_1 = BNPReLU(nIn)
      self.conv3x3 = Conv(
          nIn, nIn // 2, kSize, 1, padding=1, bn_acti=True
      )
  
      self.dconv3x1 = Conv(
          nIn // 2,
          nIn // 2,
          (dkSize, 1),
          1,
          padding=(1, 0),
          groups=nIn // 2,
          bn_acti=True,
      )
      self.dconv1x3 = Conv(
          nIn // 2,
          nIn // 2,
          (1, dkSize),
          1,
          padding=(0, 1),
          groups=nIn // 2,
          bn_acti=True,
      )
      self.ddconv3x1 = Conv(
          nIn // 2,
          nIn // 2,
          (dkSize, 1),
          1,
          padding=(1 * d, 0),
          dilation=(d, 1),
          groups=nIn // 2,
          bn_acti=True,
      )
      self.ddconv1x3 = Conv(
          nIn // 2,
          nIn // 2,
          (1, dkSize),
          1,
          padding=(0, 1 * d),
          dilation=(1, d),
          groups=nIn // 2,
          bn_acti=True,
      )
  
      self.bn_relu_2 = BNPReLU(nIn // 2)
      self.conv1x1 = Conv(nIn // 2, nIn, 1, 1, padding=0, bn_acti=False)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new DABModule object from inherited base classes: nn with example: obj = DABModule(nIn, d, kSize, dkSize)