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: Get specified ID state from decoder hidden states.
  
  Args:
      states: Decoder hidden states. None
      idx: State ID to extract.
  
  Returns:
      : Decoder hidden state for given ID. None
docstr_tok: ["Get","specified","ID","state","from","decoder","hidden","states",".","Args",":","states",":","Decoder","hidden","states",".","None","idx",":","State","ID","to","extract",".","Returns",":",":","Decoder","hidden","state","for","given","ID",".","None"]
code: def select_state(
      self, states: Optional[torch.Tensor], idx: int
  ) -> None:
      """Get specified ID state from decoder hidden states.
  
      Args:
          states: Decoder hidden states. None
          idx: State ID to extract.
  
      Returns:
          : Decoder hidden state for given ID. 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 7 for calling the StatelessDecoder obj's underlying member method code with example usage: obj.select_state(states, idx) and returns: None