code: def _batch_state(hypos: List[Hypothesis]) -> List[List[torch.Tensor]]:
      states: List[List[torch.Tensor]] = []
      for i in range(len(_get_hypo_state(hypos[0]))):
          batched_state_components: List[torch.Tensor] = []
          for j in range(len(_get_hypo_state(hypos[0])[i])):
              batched_state_components.append(
                  torch.cat(
                      [_get_hypo_state(hypo)[i][j] for hypo in hypos]
                  )
              )
          states.append(batched_state_components)
      return states
  
imports: from typing import Callable, Dict, List, Optional, Tuple
  import torch
  from torchaudio.models import RNNT
label_desc: Use image node_id 6 for calling a global function with example usage: _batch_state(hypos) and returns: states