code: def testQuantileGradsAreNotNaN(self):
      probs = tf.constant([0.2, 0.6])
      x = np.linspace(0.1, 0.9, 20)[..., np.newaxis].astype(np.float32)
      _, grad_prob = gradient.value_and_gradient(
          lambda x: continuous_bernoulli.ContinuousBernoulli(
              probs=probs
          ).quantile(  # pylint: disable=g-long-lambda
              x
          ),
          x,
      )
      self.assertAllNotNan(self.evaluate(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 31 for calling the ContinuousBernoulliTest obj's underlying member method code with example usage: obj.testQuantileGradsAreNotNaN() without return types