code: def testAssertValidCorrelationMatrix(self, dtype):
      dist = lkj.LKJ(
          dimension=2,
          concentration=dtype([1.0, 4.0]),
          validate_args=True,
      )
      with self.assertRaisesOpError("Correlations must be >= -1."):
          self.evaluate(
              dist.log_prob(dtype([[1.0, -1.3], [-1.3, 1.0]]))
          )
      with self.assertRaisesOpError("Correlations must be <= 1."):
          self.evaluate(dist.log_prob(dtype([[1.0, 1.3], [1.3, 1.0]])))
      with self.assertRaisesOpError("Self-correlations must be = 1."):
          self.evaluate(dist.log_prob(dtype([[0.5, 0.5], [0.5, 1.0]])))
      with self.assertRaisesOpError(
          "Correlation matrices must be symmetric."
      ):
          self.evaluate(dist.log_prob(dtype([[1.0, 0.2], [0.3, 1.0]])))
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import lkj
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 10 for calling the LKJTest obj's underlying member method code with example usage: obj.testAssertValidCorrelationMatrix(dtype) without return types