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)
      """
      assert len(state) > 0
      y, state = state[0], state[1:]
      if len(state) == 0:
          assert x is not None
          if self.transposed:
              x = x.unsqueeze(-1)
          x = self.linear(x)
          if self.transposed:
              x = x.squeeze(-1)
          x = rearrange(x, "... (h s) -> ... h s", s=self.stride)
          state = list(torch.unbind(x, dim=-1))
      else:
          assert x is None
      return y, 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 UpPool obj's underlying member method code with example usage: obj.step(x, state) and returns: y,  state