class_docstr: Monitors layer calls to the divergence implementation.
class_docstr_tok: ["Monitors","layer","calls","to","the","divergence","implementation","."]
code: def __init__(self, result):
      self.result = result
      self.args = []
      self.called = Counter()
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.layers import dense_variational
  from tensorflow_probability.python.layers import util
  from tensorflow_probability.python.random import random_ops
  from tensorflow_probability.python.util import seed_stream
label_desc: Use image node_id 1 to create a new MockKLDivergence object from inherited base classes: object with example: obj = MockKLDivergence(result)