import tensorflow as tf

            self.assertEqual(logits_.shape,
                             (batch_size, max_time))

        # case 4
        hparams = {
            "pretrained_model_name": None,
            "regr_strategy": "all_time",
            "max_seq_len": max_time
        }
        inputs = tf.placeholder(tf.int32, shape=[batch_size, 6])
        regressor = XLNetRegressor(hparams=hparams)
        logits = regressor(inputs)

        with self.test_session() as sess:
            sess.run(tf.global_variables_initializer())
            logits_ = sess.run(
                logits,
                feed_dict={inputs: np.random.randint(30521,
