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: One-step forward hypothesis.
  
  Args:
      label_sequence: Current label sequence.
      states: Decoder hidden states. None
  
  Returns:
      : Decoder output sequence. (1, D_emb)
      state: Decoder hidden states. None
docstr_tok: ["One-step","forward","hypothesis",".","Args",":","label_sequence",":","Current","label","sequence",".","states",":","Decoder","hidden","states",".","None","Returns",":",":","Decoder","output","sequence",".","(","1",",","D_emb",")","state",":","Decoder","hidden","states",".","None"]
code: def score(
      self,
      label_sequence: List[int],
      states: Optional[Any] = None,
  ) -> Tuple[torch.Tensor, None]:
      """One-step forward hypothesis.
  
      Args:
          label_sequence: Current label sequence.
          states: Decoder hidden states. None
  
      Returns:
          : Decoder output sequence. (1, D_emb)
          state: Decoder hidden states. None
  
      """
      str_labels = "_".join(map(str, label_sequence))
  
      if str_labels in self.score_cache:
          embed = self.score_cache[str_labels]
      else:
          label = torch.full(
              (1, 1),
              label_sequence[-1],
              dtype=torch.long,
              device=self.device,
          )
  
          embed = self.embed(label)
  
          self.score_cache[str_labels] = embed
  
      return embed[0], 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 3 for calling the StatelessDecoder obj's underlying member method code with example usage: obj.score(label_sequence, states) and returns: embed,  None