code: def testSampleMultiDimensional(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
      )
      n = tf.constant(100000)
      samples = mvn.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
  
      self.assertEqual(samples.shape, (100000, 3, 5, 2))
      self.assertAllClose(
          sample_values[:, 1, 1, :].mean(axis=0), mu[1, 1, :], atol=0.05
      )
      self.assertAllClose(
          np.cov(sample_values[:, 1, 1, :], rowvar=0),
          sigma[1, 1, :, :],
          atol=1e-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 12 for calling the MultivariateNormalTriLTest obj's underlying member method code with example usage: obj.testSampleMultiDimensional() without return types