code: def testMode(self):
      # 2 cutpoints i.e. 3 possible outcomes. 3 "batched" distributions with the
      # logistic distribution location well within the large cutpoint spacing so
      # mode is obvious
      dist = ol.OrderedLogistic(
          cutpoints=[-10.0, 10.0], loc=[-20.0, 0.0, 20.0]
      )
      mode = self.evaluate(dist.mode())
      self.assertAllEqual([0, 1, 2], mode)
  
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 6 for calling the OrderedLogisticTest obj's underlying member method code with example usage: obj.testMode() without return types