code: def testLaplaceFullyReparameterized(self):
      loc = tf.constant(4.0)
      scale = tf.constant(3.0)
      _, [grad_loc, grad_scale] = gradient.value_and_gradient(
          lambda l, s: laplace.Laplace(
              loc=l, scale=s, validate_args=True
          ).sample(  # pylint: disable=g-long-lambda
              100, seed=test_util.test_seed()
          ),
          [loc, scale],
      )
      self.assertIsNotNone(grad_loc)
      self.assertIsNotNone(grad_scale)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import laplace
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 15 for calling the LaplaceTest obj's underlying member method code with example usage: obj.testLaplaceFullyReparameterized() without return types