class_docstr: (RNN-)Transducer decoder module.
  
  Args:
      vocab_size: Output dimension.
      layers_type: (RNN-)Decoder layers type.
      num_layers: Number of decoder layers.
      hidden_size: Number of decoder units per layer.
      dropout: Dropout rate for decoder layers.
      dropout_embed: Dropout rate for embedding layer.
      embed_pad: Embed/Blank symbol ID.
docstr: Create decoder hidden states.
  
  Args:
      states: Decoder hidden states. ((N, B, D_dec), (N, B, D_dec))
      new_states: Decoder hidden states. [N x ((1, D_dec), (1, D_dec))]
  
  Returns:
      states: Decoder hidden states. ((N, B, D_dec), (N, B, D_dec))
docstr_tok: ["Create","decoder","hidden","states",".","Args",":","states",":","Decoder","hidden","states",".","(","(","N",",","B",",","D_dec",")",",","(","N",",","B",",","D_dec",")",")","new_states",":","Decoder","hidden","states",".","[","N","x","(","(","1",",","D_dec",")",",","(","1",",","D_dec",")",")","]","Returns",":","states",":","Decoder","hidden","states",".","(","(","N",",","B",",","D_dec",")",",","(","N",",","B",",","D_dec",")",")"]
code: def create_batch_states(
      self,
      states: Tuple[torch.Tensor, Optional[torch.Tensor]],
      new_states: List[Tuple[torch.Tensor, Optional[torch.Tensor]]],
      check_list: Optional[List] = None,
  ) -> List[Tuple[torch.Tensor, Optional[torch.Tensor]]]:
      """Create decoder hidden states.
  
      Args:
          states: Decoder hidden states. ((N, B, D_dec), (N, B, D_dec))
          new_states: Decoder hidden states. [N x ((1, D_dec), (1, D_dec))]
  
      Returns:
          states: Decoder hidden states. ((N, B, D_dec), (N, B, D_dec))
  
      """
      return (
          torch.cat([s[0] for s in new_states], dim=1),
          torch.cat([s[1] for s in new_states], dim=1)
          if self.dtype == "lstm"
          else None,
      )
  
file_path: espnet/espnet2/asr/decoder/transducer_decoder.py
imports: from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
  from typeguard import check_argument_types
  from espnet2.asr.decoder.abs_decoder import AbsDecoder
  from espnet2.asr.transducer.beam_search_transducer import ExtendedHypothesis, Hypothesis
label_desc: Use image node_id 9 for calling the TransducerDecoder obj's underlying member method code with example usage: obj.create_batch_states(states, new_states, check_list) and returns: torch,  unknown