code: def testValidateLowerTriangularInput(self, dtype):
      testee_lkj = cholesky_lkj.CholeskyLKJ(
          dimension=2, concentration=dtype(4.0), validate_args=True
      )
      with self.assertRaisesOpError("must be lower triangular"):
          self.evaluate(
              testee_lkj.log_prob(dtype([[1.0, 1.0], [1.0, 1.0]]))
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import cholesky_outer_product
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import square
  from tensorflow_probability.python.distributions import cholesky_lkj
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import lkj
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 6 for calling the CholeskyLKJTest obj's underlying member method code with example usage: obj.testValidateLowerTriangularInput(dtype) without return types