code: def testNotReparameterized(self):
      if tf1.control_flow_v2_enabled():
          self.skipTest("b/138796859")
      total_count = tf.constant(5.0)
      concentration = tf.constant([0.1, 0.1, 0.1])
      _, [
          grad_total_count,
          grad_concentration,
      ] = gradient.value_and_gradient(
          lambda n, c: dm.DirichletMultinomial(
              n, c, validate_args=True
          ).sample(  # pylint: disable=g-long-lambda
              100, seed=test_util.test_seed()
          ),
          [total_count, concentration],
      )
      self.assertIsNone(grad_total_count)
      self.assertIsNone(grad_concentration)
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import dirichlet_multinomial
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 27 for calling the DirichletMultinomialTest obj's underlying member method code with example usage: obj.testNotReparameterized() without return types