code: def testKLAgainstSampling(self):
      a_cutpoints = self._random_cutpoints([4])
      b_cutpoints = self._random_cutpoints([4])
      loc = self._random_location([])
  
      a = ol.OrderedLogistic(cutpoints=a_cutpoints, loc=loc)
      b = ol.OrderedLogistic(cutpoints=b_cutpoints, loc=loc)
  
      samples = a.sample(int(1e5), seed=test_util.test_seed())
      kl_samples = self.evaluate(
          a.log_prob(samples) - b.log_prob(samples)
      )
      kl = self.evaluate(kullback_leibler.kl_divergence(a, b))
  
      self.assertAllMeansClose(kl_samples, kl, axis=0, atol=2e-2)
  
imports: import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import ascending
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import ordered_logistic
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 11 for calling the OrderedLogisticTest obj's underlying member method code with example usage: obj.testKLAgainstSampling() without return types