test_inclusive_kl.py 文件源码

def test_objective(self):
        log_qx = stats.norm.logpdf(self._n01_samples).astype(np.float32)
        qx_samples = tf.convert_to_tensor(self._n01_samples)
        log_qx = tf.convert_to_tensor(log_qx)

        def log_joint(observed):
            norm = Normal(std=1.)
            return norm.log_prob(observed['x'])

        lower_bound = klpq(log_joint, observed={},
                           latent={'x': [qx_samples, log_qx]}, axis=0)
        err_msg = "can only be optimized instead of being evaluated"
        with self.assertRaisesRegexp(NotImplementedError, err_msg):
            _ = lower_bound + 1.
        with self.test_session(use_gpu=True) as sess:
            with self.assertRaisesRegexp(NotImplementedError, err_msg):
                sess.run(lower_bound)