code: def make_two_piece_normal(self):
      if self.dtype is np.float32:
          # Raw Python literals should always be interpreted as float32.
          dist = two_piece_normal.TwoPieceNormal(
              loc=3.0, scale=10.0, skewness=0.75, validate_args=True
          )
      elif self.dtype is np.float64:
          dist = two_piece_normal.TwoPieceNormal(
              loc=tf.constant(3.0, dtype=self.dtype),
              scale=tf.constant(10.0, dtype=self.dtype),
              skewness=tf.constant(0.75, dtype=self.dtype),
              validate_args=True,
          )
  
      return dist
  
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 1 for calling the _TwoPieceNormalTest obj's underlying member method code with example usage: obj.make_two_piece_normal() and returns: dist