code: def testReparameterized(self):
      prob = tf.constant([0.2, 0.6])
      _, grad_prob = gradient.value_and_gradient(
          lambda x: continuous_bernoulli.ContinuousBernoulli(  # pylint: disable=g-long-lambda
              probs=x, validate_args=True
          ).sample(
              100, seed=test_util.test_seed()
          ),
          prob,
      )
      self.assertIsNotNone(grad_prob)
  
imports: import numpy
  from scipy import special
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import continuous_bernoulli
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 18 for calling the ContinuousBernoulliTest obj's underlying member method code with example usage: obj.testReparameterized() without return types