code: def align(emission, tokens):
      targets = torch.tensor([tokens], dtype=torch.int32, device=device)
      alignments, scores = F.forced_align(emission, targets, blank=0)
  
      alignments, scores = (
          alignments[0],
          scores[0],
      )  # remove batch dimension for simplicity
      scores = scores.exp()  # convert back to probability
      return alignments, scores
  
file_path: audio/examples/tutorials/ctc_forced_alignment_api_tutorial.py
imports: import torch
  import torchaudio
  import IPython
  import matplotlib.pyplot
  import torchaudio.functional
label_desc: Use image node_id 2 for calling a global function with example usage: align(emission, tokens) and returns: alignments,  scores