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  # audio
  
      # wav2vec module
      feats = self.modules.wav2vec2(wavs)
  
      # self-attention pooling
      uttr_embeddings = self.modules.attn_pooling(feats)
  
      # norm
      uttr_embeddings = F.normalize(uttr_embeddings, p=2)
  
      # LaBSE
      text_embeddings = self.modules.LaBSE(batch.trans)
  
      return uttr_embeddings, text_embeddings
  
file_path: speechbrain/recipes/IWSLT22_lowresource/AST/transformer/train_samu.py
imports: import sys
  import torch
  import logging
  from hyperpyyaml import load_hyperpyyaml
  import speechbrain
  import torch.nn.functional
  from speechbrain.utils.distributed import run_on_main
label_desc: Use image node_id 1 for calling the ST obj's underlying member method code with example usage: obj.compute_forward(batch, stage) and returns: uttr_embeddings,  text_embeddings