code: def testGammaFullyReparameterized(self):
      concentration = tf.constant(4.0)
      rate = tf.constant(3.0)
      _, [grad_concentration, grad_rate] = gradient.value_and_gradient(
          lambda a, b: gamma_lib.Gamma(  # pylint: disable=g-long-lambda
              concentration=a, rate=b, validate_args=True
          ).sample(100, seed=test_util.test_seed()),
          [concentration, rate],
      )
      self.assertIsNotNone(grad_concentration)
      self.assertIsNotNone(grad_rate)
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  from scipy import misc
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 20 for calling the GammaTest obj's underlying member method code with example usage: obj.testGammaFullyReparameterized() without return types