code: def coverage_score(gold, pred, ignore_in_gold=[], ignore_in_pred=[]):
      
      gold, pred = _preprocess(gold, pred, ignore_in_gold, ignore_in_pred)
  
      return np.sum(pred != 0) / len(pred)
docs: Calculate (global) coverage.
      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 (global) coverage score