class_docstr: Transformer-based Speech-to-Text Decoder from OpenAI's Whisper Model:
  
  URL: https://github.com/openai/whisper
class_docstr_tok: ["Transformer-based","Speech-to-Text","Decoder","from","OpenAI","'s","Whisper","Model",":","URL",":","https",":","\/\/github.com\/openai\/whisper"]
docstr: Score.
docstr_tok: ["Score","."]
code: def score(self, ys, state, x):
      """Score."""
      logp, state = self.forward_one_step(
          ys.unsqueeze(0),
          torch.empty(0),
          x.unsqueeze(0),
          cache=state,  # dummy mask
      )
      return logp.squeeze(0), state
  
file_path: espnet/espnet2/asr/decoder/whisper_decoder.py
imports: import copy
  from typing import Any, List, Tuple
  import torch
  from typeguard import check_argument_types
  from espnet2.asr.decoder.abs_decoder import AbsDecoder
  from espnet.nets.scorer_interface import BatchScorerInterface
label_desc: Use image node_id 4 for calling the OpenAIWhisperDecoder obj's underlying member method code with example usage: obj.score(ys, state, x) and returns: logp,  state