code: def testNotReparameterized(self):
      if tf1.control_flow_v2_enabled():
          self.skipTest("b/138796859")
      total_count = tf.constant(5.0)
      probs = tf.constant([0.4, 0.6])
      _, [grad_total_count, grad_probs] = gradient.value_and_gradient(
          lambda n, p: multinomial.Multinomial(  # pylint: disable=g-long-lambda
              total_count=n, probs=p, validate_args=True
          ).sample(
              100, seed=test_util.test_seed()
          ),
          [total_count, probs],
      )
      self.assertIsNone(grad_total_count)
      self.assertIsNone(grad_probs)
  
imports: import unittest
  from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.distributions import multinomial
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 29 for calling the MultinomialTest obj's underlying member method code with example usage: obj.testNotReparameterized() without return types