categorical_test.py 文件源码

def testEntropyGradient(self):
    with self.test_session() as sess:
      logits = constant_op.constant([[1., 2., 3.], [2., 5., 1.]])

      probabilities = nn_ops.softmax(logits)
      log_probabilities = nn_ops.log_softmax(logits)
      true_entropy = - math_ops.reduce_sum(
          probabilities * log_probabilities, axis=-1)

      categorical_distribution = categorical.Categorical(probs=probabilities)
      categorical_entropy = categorical_distribution.entropy()

      # works
      true_entropy_g = gradients_impl.gradients(true_entropy, [logits])
      categorical_entropy_g = gradients_impl.gradients(
          categorical_entropy, [logits])

      res = sess.run({"true_entropy": true_entropy,
                      "categorical_entropy": categorical_entropy,
                      "true_entropy_g": true_entropy_g,
                      "categorical_entropy_g": categorical_entropy_g})
      self.assertAllClose(res["true_entropy"],
                          res["categorical_entropy"])
      self.assertAllClose(res["true_entropy_g"],
                          res["categorical_entropy_g"])