code: def testCDF(self):
      dist = self.make_two_piece_normals()
  
      x = np.array([[-35.0], [3.0], [20.0]], dtype=self.dtype)
  
      cdf = self.evaluate(dist.cdf(x))
      # The following values were calculated using the R package 'gamlss.dist'.
      # Package version: 5.3-2. Distribution: SN2.
      expected_cdf = np.array(
          [
              [2.798031e-03, 7.234804e-05, 1.562540e-07],
              [6.400000e-01, 5.000000e-01, 3.611542e-01],
              [9.915722e-01, 9.554345e-01, 8.714767e-01],
          ],
          dtype=self.dtype,
      )
  
      self.assertAllEqual(cdf.shape, expected_cdf.shape)
      self.assertAllClose(cdf, expected_cdf)
  
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 11 for calling the _TwoPieceNormalTest obj's underlying member method code with example usage: obj.testCDF() without return types