code: def __init__(self, feats):
      super().__init__()
  
      self.relu = nn.ReLU(inplace=True)
      for i in range(1, 4):
          self.add_module(
              "block{}".format(i),
              nn.Sequential(
                  nn.MaxPool2d(kernel_size=5, stride=1, padding=2),
                  nn.Conv2d(
                      feats,
                      feats,
                      kernel_size=3,
                      stride=1,
                      padding=1,
                      bias=False,
                  ),
              ),
          )
  
imports: import torch.nn
label_desc: Use image node_id 1 to create a new ChainedResidualPool object from inherited base classes: nn with example: obj = ChainedResidualPool(feats)