code: def testBetaFullyReparameterized(self):
      a = tf.constant(1.0)
      b = tf.constant(2.0)
      _, [grad_a, grad_b] = gradient.value_and_gradient(
          lambda a_, b_: beta.Beta(
              a_, b_, validate_args=True
          ).sample(  # pylint: disable=g-long-lambda
              100, seed=test_util.test_seed()
          ),
          [a, b],
      )
      self.assertIsNotNone(grad_a)
      self.assertIsNotNone(grad_b)
      self.assertNotAllZero(grad_a)
      self.assertNotAllZero(grad_b)
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 22 for calling the BetaTest obj's underlying member method code with example usage: obj.testBetaFullyReparameterized() without return types