import tensorflow as tf

          # Compute Pearson correlation
          pearson = contrib_metrics.streaming_pearson_correlation(
              logits, label_ids, weights=is_real_example)

          # Compute MSE
          # mse = tf.metrics.mean(per_example_loss)
          mse = tf.metrics.mean_squared_error(
              label_ids, logits, weights=is_real_example)

          loss = tf.metrics.mean(
              values=per_example_loss,
              weights=is_real_example)
