code: def testFullyReparameterized(self, skewness):
      n = 100
  
      def sampler(loc, scale, skewness):
          dist = two_piece_normal.TwoPieceNormal(
              loc, scale=scale, skewness=skewness, validate_args=True
          )
          return dist.sample(n, seed=test_util.test_seed())
  
      loc = tf.constant(0.0, self.dtype)
      scale = tf.constant(1.0, self.dtype)
  
      _, grads = gradient.value_and_gradient(
          sampler, [loc, scale, tf.constant(skewness, self.dtype)]
      )
      self.assertIsNotNone(grads[0])  # d/d loc
      self.assertIsNotNone(grads[1])  # d/d scale
      self.assertIsNotNone(grads[2])
  
imports: import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import two_piece_normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 19 for calling the _TwoPieceNormalTest obj's underlying member method code with example usage: obj.testFullyReparameterized(skewness) and returns: dist