code: def upsample(x, stride=1, expand=1, transposed=False):
      if x is None:
          return None
      if expand > 1:
          if transposed:
              x = reduce(x, "... (d e) l -> ... d l", "mean", e=expand)
          else:
              x = reduce(x, "... (d e) -> ... d", "mean", e=expand)
      if stride > 1:
          if transposed:
              x = repeat(x, "... l -> ... (l e)", e=stride)
          else:
              x = repeat(x, "... l d -> ... (l e) d", e=stride)
      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 a global function with example usage: upsample(x, stride, expand, transposed) and returns: x, None