docstr: Given an input batch it computes the output probabilities.
code: def compute_forward(self, batch, stage):
      "Given an input batch it computes the output probabilities."
      batch = batch.to(self.device)
      wavs, wav_lens = batch.sig
      phns_bos, _ = batch.phn_encoded_bos
      feats = self.hparams.compute_features(wavs)
      feats = self.modules.mean_var_norm(feats, wav_lens)
      x = self.modules.enc(feats)
  
      # Prepend bos token at the beginning
      e_in = self.modules.emb(phns_bos)
      h, w = self.modules.dec(e_in, x, wav_lens)
      logits = self.modules.lin(h)
      outputs = self.hparams.softmax(logits)
  
      seq = None
      if stage != sb.Stage.TRAIN:
          seq, _, _, _ = self.hparams.searcher(x, wav_lens)
  
      return outputs, seq
  
file_path: speechbrain/tests/integration/ASR_seq2seq/example_asr_seq2seq_experiment.py
imports: import pathlib
  import speechbrain
  from hyperpyyaml import load_hyperpyyaml
label_desc: Use image node_id 1 for calling the seq2seqBrain obj's underlying member method code with example usage: obj.compute_forward(batch, stage) and returns: outputs,  seq