code: def __init__(self, nIn, nOut):
      super().__init__()
      self.nIn = nIn
      self.nOut = nOut
  
      if self.nIn < self.nOut:
          nConv = nOut - nIn
      else:
          nConv = nOut
  
      self.conv3x3 = Conv(nIn, nConv, kSize=3, stride=2, padding=1)
      self.max_pool = nn.MaxPool2d(2, stride=2)
      self.bn_prelu = BNPReLU(nOut)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new DownSamplingBlock object from inherited base classes: nn with example: obj = DownSamplingBlock(nIn, nOut)