code: def testBernoulliBernoulliKL(self):
      batch_size = 6
      a_p = np.array([0.5] * batch_size, dtype=np.float32)
      b_p = np.array([0.4] * batch_size, dtype=np.float32)
  
      a = bernoulli.Bernoulli(probs=a_p)
      b = bernoulli.Bernoulli(probs=b_p)
  
      kl = kullback_leibler.kl_divergence(a, b)
      kl_val = self.evaluate(kl)
  
      kl_expected = a_p * np.log(a_p / b_p) + (1.0 - a_p) * np.log(
          (1.0 - a_p) / (1.0 - b_p)
      )
  
      self.assertEqual(kl.get_shape(), (batch_size,))
      self.assertAllClose(kl_val, kl_expected)
  
imports: import importlib
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops.distributions import bernoulli
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 21 for calling the BernoulliTest obj's underlying member method code with example usage: obj.testBernoulliBernoulliKL() without return types