docstr: Forward computations from the waveform batches to the output probabilities.
docstr_tok: ["Forward","computations","from","the","waveform","batches","to","the","output","probabilities","."]
code: def compute_forward(self, batch, stage):
      """Forward computations from the waveform batches to the output probabilities."""
  
      batch = batch.to(self.device)
      wavs, wav_lens = batch.sig
      wavs, wav_lens = wavs.to(self.device), wav_lens.to(self.device)
  
      # Add waveform augmentation if specified.
      if stage == sb.Stage.TRAIN and hasattr(
          self.hparams, "wav_augment"
      ):
          wavs, wav_lens = self.hparams.wav_augment(wavs, wav_lens)
  
      # Forward pass
      feats = self.modules.wav2vec2(wavs, wav_lens)
      x = self.modules.enc(feats)
      logits = self.modules.ctc_lin(x)
      p_ctc = self.hparams.log_softmax(logits)
  
      return p_ctc, wav_lens
  
imports: import functools
  import os
  import sys
  from pathlib import Path
  import torch
  import logging
  import speechbrain
  import torchaudio
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.tokenizers.SentencePiece import SentencePiece
  from speechbrain.utils.data_utils import undo_padding
  from speechbrain.utils.distributed import run_on_main, if_main_process
label_desc: Use image node_id 2 for calling the ASR obj's underlying member method code with example usage: obj.compute_forward(batch, stage) and returns: p_ctc,  wav_lens