code: def testEntropyMultidimensional(self):
      mu = self._rng.rand(3, 5, 2)
      chol, sigma = self._random_chol(3, 5, 2, 2)
      mvn = mvn_tril.MultivariateNormalTriL(
          mu, chol, validate_args=True
      )
      entropy = mvn.entropy()
  
      # Scipy doesn't do batches, so test one of them.
      expected_entropy = stats.multivariate_normal(
          mean=mu[1, 1, :], cov=sigma[1, 1, :, :]
      ).entropy()
      self.assertEqual(entropy.shape, (3, 5))
      self.assertAllClose(
          expected_entropy, self.evaluate(entropy)[1, 1]
      )
  
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 8 for calling the MultivariateNormalTriLTest obj's underlying member method code with example usage: obj.testEntropyMultidimensional() without return types