code: def test_entropy(self):
      sample_shape = [3, 4]
      mvn = independent.Independent(
          normal.Normal(loc=0, scale=[[0.25, 0.5]]), 1
      )
      d = sample.Sample(mvn, sample_shape, validate_args=True)
      expected_entropy = 12 * tf.reduce_sum(
          mvn.distribution.entropy(), axis=-1
      )
      actual_entropy = d.entropy()
      self.assertAllEqual(
          *self.evaluate([expected_entropy, actual_entropy])
      )
  
imports: import functools
  import os
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import scale_matvec_tril
  from tensorflow_probability.python.distributions import cholesky_lkj
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 9 for calling the SampleDistributionTest obj's underlying member method code with example usage: obj.test_entropy() without return types