distribution_util_test.py 文件源码

def testGetLogitsAndProbsProbabilityValidateArgsMultidimensional(self):
    p = np.array([[0.3, 0.4, 0.3], [0.1, 0.5, 0.4]], dtype=np.float32)
    # Component less than 0. Still sums to 1.
    p2 = np.array([[-.3, 0.4, 0.9], [0.1, 0.5, 0.4]], dtype=np.float32)
    # Component greater than 1. Does not sum to 1.
    p3 = np.array([[1.3, 0.0, 0.0], [0.1, 0.5, 0.4]], dtype=np.float32)
    # Does not sum to 1.
    p4 = np.array([[1.1, 0.3, 0.4], [0.1, 0.5, 0.4]], dtype=np.float32)

    with self.test_session():
      _, prob = distribution_util.get_logits_and_probs(
          probs=p, multidimensional=True)
      prob.eval()

      with self.assertRaisesOpError("Condition x >= 0"):
        _, prob = distribution_util.get_logits_and_probs(
            probs=p2, multidimensional=True, validate_args=True)
        prob.eval()

      _, prob = distribution_util.get_logits_and_probs(
          probs=p2, multidimensional=True, validate_args=False)
      prob.eval()

      with self.assertRaisesOpError(
          "(probs has components greater than 1|probs does not sum to 1)"):
        _, prob = distribution_util.get_logits_and_probs(
            probs=p3, multidimensional=True, validate_args=True)
        prob.eval()

      _, prob = distribution_util.get_logits_and_probs(
          probs=p3, multidimensional=True, validate_args=False)
      prob.eval()

      with self.assertRaisesOpError("probs does not sum to 1"):
        _, prob = distribution_util.get_logits_and_probs(
            probs=p4, multidimensional=True, validate_args=True)
        prob.eval()

      _, prob = distribution_util.get_logits_and_probs(
          probs=p4, multidimensional=True, validate_args=False)
      prob.eval()