test_stochastic.py 文件源码

def test_Binomial(self):
        with BayesianNet():
            logits = tf.zeros([2, 3])
            n_experiments = tf.placeholder(tf.int32, shape=[])
            n_samples = tf.placeholder(tf.int32, shape=[])
            group_ndims = tf.placeholder(tf.int32, shape=[])
            a = Binomial('a', logits, n_experiments, n_samples,
                         group_ndims)
        sample_ops = set(get_backward_ops(a.tensor))
        for i in [logits, n_experiments, n_samples]:
            self.assertTrue(i.op in sample_ops)
        log_p = a.log_prob(np.ones([2, 3], dtype=np.int32))
        log_p_ops = set(get_backward_ops(log_p))
        for i in [logits, n_experiments, group_ndims]:
            self.assertTrue(i.op in log_p_ops)
        self.assertTrue(a.get_shape()[1:], logits.get_shape())