code: def testCDF(self):
      dist = self.make_two_piece_student_ts()
  
      x = np.array(
          [[-123.0], [-4.0], [3.0], [10.0], [88.0]], 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: ST3.
      expected_cdf = np.array(
          [
              [
                  5.11329136655268e-5,
                  7.65138872532116e-6,
                  1.04125412928787e-6,
              ],
              [
                  3.95781464247676e-1,
                  2.55071690475380e-1,
                  1.40048351817201e-1,
              ],
              [
                  6.40000000000000e-1,
                  5.00000000000000e-1,
                  3.61154248979739e-1,
              ],
              [
                  8.60799760188126e-1,
                  7.44928309524620e-1,
                  6.05481963344001e-1,
              ],
              [
                  9.99989828542182e-1,
                  9.99927435887923e-1,
                  9.99558660780453e-1,
              ],
          ],
          dtype=self.dtype,
      )
  
      self.assertDTypeEqual(cdf, self.dtype)
      self.assertShapeEqual(cdf, expected_cdf)
      self.assertAllClose(
          cdf,
          expected_cdf,
          atol=0.0,
          rtol=5e-6 if self.dtype == np.float32 else 1e-12,
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import two_piece_student_t
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 10 for calling the _TwoPieceStudentTTest obj's underlying member method code with example usage: obj.testCDF() without return types