import tensorflow as tf


        # case 2
        hparams = {
            "pretrained_model_name": None,
            "regr_strategy": "cls_time"
        }
        regressor = XLNetRegressor(hparams=hparams)
        logits = regressor(inputs)

        with self.test_session() as sess:
            sess.run(tf.global_variables_initializer())
            logits_ = sess.run(logits)
            self.assertEqual(logits_.shape, (batch_size,))

        # case 3
        hparams = {
            "pretrained_model_name": None,
            "regr_strategy": "time_wise"
        }
        regressor = XLNetRegressor(hparams=hparams)
