code: def _kl_bernoulli_bernoulli(a, b, name=None):
      """Calculate the batched KL divergence KL(a || b) for Continuous Bernoullis.
  
      Args:
        a: instance of a continuous Bernoulli distribution object.
        b: instance of a continuous Bernoulli distribution object.
        name: Python `str` name to use for created operations.
          Default value: `None`
          (i.e., `'kl_continuous_bernoulli_continuous_bernoulli'`).
  
      Returns:
        Batchwise KL(a || b)
      """
      with tf.name_scope(
          name or "kl_continuous_bernoulli_continuous_bernoulli"
      ):
          (
              a_log_probs0,
              a_log_probs1,
              a_logits,
          ) = a._outcome_log_probs()  # pylint:disable=protected-access
          (
              b_log_probs0,
              b_log_probs1,
              b_probs,
          ) = b._outcome_log_probs()  # pylint:disable=protected-access
          a_mean = a._mean(a_logits)  # pylint:disable=protected-access
          a_log_norm = a._log_normalizer(
              a_logits
          )  # pylint:disable=protected-access
          b_log_norm = b._log_normalizer(
              b_probs
          )  # pylint:disable=protected-access
  
          return (
              a_mean
              * (
                  a_log_probs1
                  + b_log_probs0
                  - a_log_probs0
                  - b_log_probs1
              )
              + a_log_norm
              - b_log_norm
              + a_log_probs0
              - b_log_probs0
          )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import generic
label_desc: Use image node_id 3 for calling a global function with example usage: _kl_bernoulli_bernoulli(a, b, name) and returns: unknown