import tensorflow as tf

        }
        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,
                                                     size=(batch_size, 6))})
            self.assertEqual(logits_.shape, (batch_size,))
