docstr: Step one time step as a recurrent model.
  
  x: (..., H)
code: def step(self, x, state, **kwargs):
      """Step one time step as a recurrent model.
  
      x: (..., H)
      """
      if x is None:
          return None, state
      state.append(x)
      if len(state) == self.stride:
          x = rearrange(
              torch.stack(state, dim=-1), "... h s -> ... (h s)"
          )
          if self.transposed:
              x = x.unsqueeze(-1)
          x = self.linear(x)
          if self.transposed:
              x = x.squeeze(-1)
          return x, []
      else:
          return None, state
  
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 3 for calling the DownPool obj's underlying member method code with example usage: obj.step(x, state) and returns: None,  state, x,  list, None,  state