class_docstr: Decoder interface for Transducer models.
docstr: One-step forward hypothesis.
  
  Args:
      hyp: Hypothesis.
      cache: Pairs of (dec_out, dec_state) for each token sequence. (key)
  
  Returns:
      dec_out: Decoder output sequence.
      new_state: Decoder hidden states.
      lm_tokens: Label ID for LM.
code: def score(
      self,
      hyp: Hypothesis,
      cache: Dict[str, Any],
  ) -> Tuple[
      torch.Tensor,
      Union[
          Tuple[torch.Tensor, Optional[torch.Tensor]],
          List[Optional[torch.Tensor]],
      ],
      torch.Tensor,
  ]:
      """One-step forward hypothesis.
  
      Args:
          hyp: Hypothesis.
          cache: Pairs of (dec_out, dec_state) for each token sequence. (key)
  
      Returns:
          dec_out: Decoder output sequence.
          new_state: Decoder hidden states.
          lm_tokens: Label ID for LM.
  
      """
      raise NotImplementedError("score(...) is not implemented")
  
file_path: espnet/espnet/nets/transducer_decoder_interface.py
imports: from dataclasses import dataclass
  from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
label_desc: Use image node_id 2 for calling the TransducerDecoderInterface obj's underlying member method code with example usage: obj.score(hyp, cache) without return types