class_docstr: ## Down-sampling layer
docstr: :param x: is the input feature map with shape `[batch_size, channels, height, width]`
code: def forward(self, x: torch.Tensor):
      """
      :param x: is the input feature map with shape `[batch_size, channels, height, width]`
      """
      # Add padding
      x = F.pad(x, (0, 1, 0, 1), mode="constant", value=0)
      # Apply convolution
      return self.conv(x)
  
imports: from typing import List
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the DownSample obj's underlying member method code with example usage: obj.forward(x) and returns: self