code: def testVariance(self):
      dist = self.make_two_piece_normals()
  
      variance = self.evaluate(dist.variance())
      expected_variance = np.array(
          [112.365005, 100.0, 112.14502], dtype=self.dtype
      )
  
      self.assertAllEqual(variance.shape, expected_variance.shape)
      self.assertAllClose(variance, expected_variance)
  
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 15 for calling the _TwoPieceNormalTest obj's underlying member method code with example usage: obj.testVariance() without return types