docs: def accuracy_score(gold, pred, ignore_in_gold=[], ignore_in_pred=[]):
      """
      Calculate (micro) accuracy.
      Args:
          gold: A 1d array-like of gold labels
          pred: A 1d array-like of predicted labels (assuming abstain = 0)
          ignore_in_gold: A list of labels for which elements having that gold
              label will be ignored.
          ignore_in_pred: A list of labels for which elements having that pred
              label will be ignored.
  
      Returns:
          A float, the (micro) accuracy score
      """
      gold, pred = _preprocess(gold, pred, ignore_in_gold, ignore_in_pred)
  
      if len(gold) and len(pred):
          acc = np.sum(gold == pred) / len(gold)
      else:
          acc = 0
  
      return acc