code: def forward(self, x):
      if self.with_conv:
          pad = (0, 1, 0, 1)
          x = torch.nn.functional.pad(x, pad, mode="constant", value=0)
          x = self.conv(x)
      else:
          x = torch.nn.functional.avg_pool2d(x, kernel_size=2, stride=2)
      return x
  
imports: import logging
  import math
  from typing import Any, Callable, Optional
  import numpy
  import torch
  import torch.nn
  from einops import rearrange
  from packaging import version
  from ...modules.attention import LinearAttention, MemoryEfficientCrossAttention
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: x