code: def test_entropy(self):
      u = sample_lib.Sample(normal.Normal(0.0, 0.5), 4)
      self.assertAllEqual(
          tf.fill([2, 3], u.entropy()),
          batch_broadcast.BatchBroadcast(u, [2, 3]).entropy(),
      )
  
imports: import hypothesis
  import hypothesis.strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import batch_broadcast
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import dirichlet
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import mixture_same_family
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.distributions import von_mises_fisher
  from tensorflow_probability.python.distributions import wishart
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.random import random_ops
label_desc: Use image node_id 6 for calling the _BatchBroadcastTest obj's underlying member method code with example usage: obj.test_entropy() without return types