code: def testNonSPDHintsRaise(self):
      with self.subTest("base_operator must be positive definite"):
          base_operator = tf.linalg.LinearOperatorDiag(
              # It actually is PD, but the hint is set wrong
              [1.0, 1.0],
              is_positive_definite=False,
          )
          cov_operator = tf.linalg.LinearOperatorLowRankUpdate(
              base_operator, u=tf.zeros((2, 2))
          )
          with self.assertRaisesRegex(ValueError, "must be positive"):
              MultivariateNormalLowRankUpdateLinearOperatorCovariance(
                  cov_operator=cov_operator
              )
  
      with self.subTest("U must equal V"):
          base_operator = tf.linalg.LinearOperatorDiag(
              [1.0, 1.0], is_positive_definite=True
          )
          cov_operator = tf.linalg.LinearOperatorLowRankUpdate(
              base_operator, u=tf.zeros((2, 2)), v=tf.ones((2, 2))
          )
          with self.assertRaisesRegex(ValueError, "must be the same"):
              MultivariateNormalLowRankUpdateLinearOperatorCovariance(
                  cov_operator=cov_operator
              )
  
imports: import collections
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import mvn_low_rank_update_linear_operator_covariance
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.stats import sample_stats
label_desc: Use image node_id 9 for calling the MultivariateNormalLowRankUpdateLinearOperatorCovarianceTest obj's underlying member method code with example usage: obj.testNonSPDHintsRaise() without return types