class_docstr: Module for calculate the overall one-step-forward prediction accuracy.
  
  Example
  -------
  >>> probs = torch.tensor([[0.9, 0.1], [0.1, 0.9], [0.8, 0.2]]).unsqueeze(0)
  >>> stats = AccuracyStats()
  >>> stats.append(torch.log(probs), torch.tensor([1, 1, 0]).unsqueeze(0), torch.tensor([2/3]))
  >>> acc = stats.summarize()
  >>> print(acc)
  0.5
docstr: Computes the accuract metric.
docstr_tok: ["Computes","the","accuract","metric","."]
code: def summarize(self):
      """Computes the accuract metric."""
      return self.correct / self.total
  
imports: import torch
  from speechbrain.dataio.dataio import length_to_mask
label_desc: Use image node_id 3 for calling the AccuracyStats obj's underlying member method code with example usage: obj.summarize() and returns: unknown