import tensorflow as tf

              predictions, label_ids, weights=is_real_example)

          # Compute Matthew's correlation
          mcc = tf.div_no_nan(
              tp * tn - fp * fn,
              tf.pow((tp + fp) * (tp + fn) * (tn + fp) * (tn + fn), 0.5))

          # Compute accuracy
          accuracy = tf.metrics.accuracy(
              labels=label_ids, predictions=predictions,
