import tensorflow as tf

                train_op=train_op,
                scaffold_fn=scaffold_fn)
        elif mode == tf.estimator.ModeKeys.EVAL:

            def metric_fn(per_example_loss, label_ids, logits, is_real_example):
                predictions = tf.argmax(logits, axis=-1, output_type=tf.int32)
                accuracy = tf.metrics.accuracy(
                    labels=label_ids, predictions=predictions, weights=is_real_example)
                loss = tf.metrics.mean(values=per_example_loss, weights=is_real_example)
                return {
                    "eval_accuracy": accuracy,
                    "eval_loss": loss,
