code: def verify_predictions(predictions):
      
      # Check that it contains only zeros and ones
      predictions = np.array(predictions, copy=False)
      if not np.array_equal(predictions, predictions.astype(bool)):
          raise ValueError("predictions contains invalid values. " +
                           "The only permitted values are 0 or 1.")
      if predictions.ndim == 1:
          predictions = predictions[:,np.newaxis]
      return predictions
docs: Ensures that predictions is stored as a numpy array and checks that
      all values are either 0 or 1.