code: def random_two_piece_normal(sample_shape, skewness, seed=None):
      """Generate samples from Two-Piece Normal distribution.
  
      The distribution is the Two-Piece Normal distribution with location zero,
      scale one, and skewness `skewness`. To change the location and scale, use:
  
      ```none
      loc + scale * samples
      ```
  
      The samples are pathwise differentiable using the approach of [1].
  
      Note that `skewness` can be negative.
  
      Args:
        sample_shape: 0D or 1D `int32` `Tensor`. Shape of the generated samples.
        skewness: The skewness(es) of the distribution(s).
        seed: PRNG seed; see `tfp.random.sanitize_seed` for details.
  
      Returns:
        A tensor with shape `sample_shape`.
  
      References:
        [1]: Michael Figurnov, Shakir Mohamed, and Andriy Mnih.
             Implicit Reparameterization Gradients. In _Advances in Neural
             Information Processing Systems_, 31, 2018.
             https://arxiv.org/abs/1805.08498
      """
      sample_shape = ps.convert_to_shape_tensor(
          sample_shape, dtype_hint=tf.int32
      )
      skewness = tf.convert_to_tensor(skewness)
      seed = samplers.sanitize_seed(seed, salt="two_piece_normal")
  
      return _two_piece_normal_sample_with_gradient(
          sample_shape, tf.abs(skewness), seed
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import special_math
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import special
  from tensorflow_probability.python.math.numeric import log1psquare
label_desc: Use image node_id 11 for calling a global function with example usage: random_two_piece_normal(sample_shape, skewness, seed) and returns: _two_piece_normal_sample_with_gradient