code: def forward(self, x):
      # pylint: disable=not-callable
      if self.downsample_position == "before":
          x = self.pool(x)
      x = self.conv(x)
      if self.norm is not None:
          x = self.norm(x)
      if self.relu is not None:
          x = self.relu(x)
      if self.downsample_position == "after":
          x = self.pool(x)
  
      return x
  
imports: import numpy
  import torch
  import torch.nn
  import torch.utils.checkpoint
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the Downampling obj's underlying member method code with example usage: obj.forward(x) and returns: x