code: def testSingularScaleRaises(self):
      mu = None
      chol = [[1.0, 0.0], [0.0, 0.0]]
      with self.assertRaisesOpError("Singular operator"):
          mvn = mvn_tril.MultivariateNormalTriL(
              mu, chol, validate_args=True
          )
          self.evaluate(mvn.sample(seed=test_util.test_seed()))
  
imports: import os
  from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.bijectors import transform_diagonal
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 10 for calling the MultivariateNormalTriLTest obj's underlying member method code with example usage: obj.testSingularScaleRaises() without return types