code: def testNotReparameterized(self):
      if tf1.control_flow_v2_enabled():
          self.skipTest("b/138796859")
      n = tf.constant(5.0)
      c1 = tf.constant([0.1, 0.1, 0.1])
      c0 = tf.constant([0.3, 0.3, 0.3])
  
      def f(n, c1, c0):
          dist = beta_binomial.BetaBinomial(
              n, c1, c0, validate_args=True
          )
          return dist.sample(100, seed=test_util.test_seed())
  
      _, [grad_n, grad_c1, grad_c0] = gradient.value_and_gradient(
          f, [n, c1, c0]
      )
      self.assertIsNone(grad_n)
      self.assertIsNone(grad_c1)
      self.assertIsNone(grad_c0)
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import beta_binomial
  from tensorflow_probability.python.distributions import dirichlet_multinomial
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 12 for calling the BetaBinomialTest obj's underlying member method code with example usage: obj.testNotReparameterized() and returns: dist