code: def testShapeWithPlaceholders(self):
      loc = tf.Variable(self.dtype(0), shape=tf.TensorShape(None))
      scale = tf.Variable(
          self.dtype([1.0, 2.0]), shape=tf.TensorShape(None)
      )
      skewness = tf.Variable(
          self.dtype([[0.75, 1.33]]).T, shape=tf.TensorShape(None)
      )
      self.evaluate(
          [loc.initializer, scale.initializer, skewness.initializer]
      )
      dist = two_piece_normal.TwoPieceNormal(
          loc=loc, scale=scale, skewness=skewness, validate_args=True
      )
  
      # get_batch_shape should return an '<unknown>' tensor (graph mode only).
      self.assertEqual(dist.event_shape, ())
      self.assertEqual(dist.batch_shape, tf.TensorShape(None))
      self.assertAllEqual(self.evaluate(dist.event_shape_tensor()), [])
      self.assertAllEqual(
          self.evaluate(dist.batch_shape_tensor()), [2, 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 23 for calling the _TwoPieceNormalTest obj's underlying member method code with example usage: obj.testShapeWithPlaceholders() without return types