class_docstr: A ready-to-use Whisper ASR model
  
  The class can be used  to  run the entire encoder-decoder whisper model
  (transcribe()) to transcribe speech. The given YAML must contains the fields
  specified in the *_NEEDED[] lists.
  
  Example
  -------
  >>> from speechbrain.inference.ASR import WhisperASR
  >>> tmpdir = getfixture("tmpdir")
  >>> asr_model = WhisperASR.from_hparams(source="speechbrain/asr-whisper-large-v2-commonvoice-fr", savedir=tmpdir,) # doctest: +SKIP
  >>> asr_model.transcribe_file("speechbrain/asr-whisper-large-v2-commonvoice-fr/example-fr.mp3") # doctest: +SKIP
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docstr: Runs full transcription - note: no gradients through decoding
docstr_tok: ["Runs","full","transcription","-","note",":","no","gradients","through","decoding"]
code: def forward(self, wavs, wav_lens):
      """Runs full transcription - note: no gradients through decoding"""
      return self.transcribe_batch(wavs, wav_lens)
  
imports: import torch
  import sentencepiece
  import speechbrain
  from speechbrain.inference.interfaces import Pretrained
  from speechbrain.utils.fetching import fetch
  from speechbrain.utils.data_utils import split_path
label_desc: Use image node_id 5 for calling the WhisperASR obj's underlying member method code with example usage: obj.forward(wavs, wav_lens) and returns: self