code: def forward(self, x):
      if not self.transposed:
          x = rearrange(x, "b ... d -> b d ...")
  
      if self.stride > 1:
          # einops appears slower than F
          if x.ndim == 3:
              x = F.avg_pool1d(x, self.stride, self.stride)
          elif x.ndim == 4:
              x = F.avg_pool2d(x, self.stride, self.stride)
          else:
              # Reduction string e.g. "b d (l1 2) (l2 2) -> b d l1 l2"
              reduce_str = (
                  "b d "
                  + " ".join(
                      [
                          f"(l{i} {self.stride})"
                          for i in range(x.ndim - 2)
                      ]
                  )
                  + " -> b d "
                  + " ".join([f"l{i}" for i in range(x.ndim - 2)])
              )
              x = reduce(x, reduce_str, "mean")
  
      if self.expand > 1:
          x = repeat(x, "b d ... -> b (d e) ...", e=self.expand)
  
      if not self.transposed:
          x = rearrange(x, "b d ... -> b ... d")
      return x
  
imports: import torch
  import torch.nn.functional
  from einops import rearrange, reduce, repeat
  from torch import nn
  from espnet2.asr.state_spaces.base import SequenceModule
  from espnet2.asr.state_spaces.components import LinearActivation
label_desc: Use image node_id 2 for calling the DownAvgPool obj's underlying member method code with example usage: obj.forward(x) and returns: x