test_multivariate.py 文件源码

def test_value(self):
        with self.test_session(use_gpu=True):
            def _test_value(logits, given):
                logits = np.array(logits, np.float32)
                normalized_logits = logits - misc.logsumexp(
                    logits, axis=-1, keepdims=True)
                given = np.array(given, np.int32)
                cat = OnehotCategorical(logits)
                log_p = cat.log_prob(tf.one_hot(given, logits.shape[-1],
                                                dtype=tf.int32))

                def _one_hot(x, depth):
                    n_elements = x.size
                    ret = np.zeros((n_elements, depth))
                    ret[np.arange(n_elements), x.flat] = 1
                    return ret.reshape(list(x.shape) + [depth])

                target_log_p = np.sum(_one_hot(
                    given, logits.shape[-1]) * normalized_logits, -1)
                self.assertAllClose(log_p.eval(), target_log_p)
                p = cat.prob(tf.one_hot(given, logits.shape[-1],
                                        dtype=tf.int32))
                target_p = np.sum(_one_hot(
                    given, logits.shape[-1]) * np.exp(normalized_logits), -1)
                self.assertAllClose(p.eval(), target_p)

            _test_value([0.], [0, 0, 0])
            _test_value([-50., -10., -50.], [0, 1, 2, 1])
            _test_value([0., 4.], [[0, 1], [0, 1]])
            _test_value([[2., 3., 1.], [5., 7., 4.]],
                        np.ones([3, 1, 1], dtype=np.int32))