class_docstr: Stateless Transducer decoder module.
  
  Args:
      vocab_size: Output size.
      embed_size: Embedding size.
      embed_dropout_rate: Dropout rate for embedding layer.
      embed_pad: Embed/Blank symbol ID.
class_docstr_tok: ["Stateless","Transducer","decoder","module",".","Args",":","vocab_size",":","Output","size",".","embed_size",":","Embedding","size",".","embed_dropout_rate",":","Dropout","rate","for","embedding","layer",".","embed_pad",":","Embed\/Blank","symbol","ID","."]
docstr: Create decoder hidden states.
  
  Args:
      new_states: Decoder hidden states. [N x None]
  
  Returns:
      states: Decoder hidden states. None
docstr_tok: ["Create","decoder","hidden","states",".","Args",":","new_states",":","Decoder","hidden","states",".","[","N","x","None","]","Returns",":","states",":","Decoder","hidden","states",".","None"]
code: def create_batch_states(
      self,
      new_states: List[Optional[torch.Tensor]],
  ) -> None:
      """Create decoder hidden states.
  
      Args:
          new_states: Decoder hidden states. [N x None]
  
      Returns:
          states: Decoder hidden states. None
  
      """
      return None
  
file_path: espnet/espnet2/asr_transducer/decoder/stateless_decoder.py
imports: from typing import Any, List, Optional, Tuple
  import torch
  from typeguard import check_argument_types
  from espnet2.asr_transducer.beam_search_transducer import Hypothesis
  from espnet2.asr_transducer.decoder.abs_decoder import AbsDecoder
label_desc: Use image node_id 8 for calling the StatelessDecoder obj's underlying member method code with example usage: obj.create_batch_states(new_states) and returns: None