docstr: Test the gradients of the samples w.r.t. skewness.
docstr_tok: ["Test","the","gradients","of","the","samples","w.r.t",".","skewness","."]
code: def testDifferentiableSampleNumerically(self, skewness):
      """Test the gradients of the samples w.r.t. skewness."""
      sample_shape = [int(2e3)]
      seed = test_util.test_seed(sampler_type="stateless")
  
      def get_abs_sample_mean(skewness):
          loc = tf.constant(0.0, self.dtype)
          scale = tf.constant(1.0, self.dtype)
          dist = two_piece_normal.TwoPieceNormal(
              loc, scale=scale, skewness=skewness, validate_args=True
          )
          return tf.reduce_mean(
              tf.abs(dist.sample(sample_shape, seed=seed))
          )
  
      err = self.compute_max_gradient_error(
          get_abs_sample_mean,
          [tf.constant(skewness, self.dtype)],
          delta=1e-1,
      )
      maxerr = 0.2
      self.assertLess(err, maxerr)
  
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 20 for calling the _TwoPieceNormalTest obj's underlying member method code with example usage: obj.testDifferentiableSampleNumerically(skewness) and returns: tf