code: def testQuantile(self):
      dist = self.make_two_piece_student_ts()
  
      p = np.array(
          [[1e-6], [0.25], [0.5], [0.75], [1.0 - 1e-5]],
          dtype=self.dtype,
      )
  
      quantile = self.evaluate(dist.quantile(p))
      # The following values were calculated using the R package gamlss.dist.
      # Package version: 5.3-2. Distribution: ST3.
      # pylint: disable=bad-whitespace
      expected_quantile = np.array(
          [
              [
                  -244.884076670630000,
                  -175.303145006555,
                  -123.86764610382800,
              ],
              [-9.334084600342130, -4.175581964914, -0.12407156338927],
              [-0.872658556456447, 3.000000000000, 6.83723135012289],
              [6.092263521199590, 10.175581964914, 15.28370839341050],
              [
                  88.250979391306600,
                  123.316531781276,
                  169.92793695323400,
              ],
          ],
          dtype=self.dtype,
      )
      # pylint: enable=bad-whitespace
  
      self.assertDTypeEqual(quantile, self.dtype)
      self.assertShapeEqual(quantile, expected_quantile)
      self.assertAllClose(
          quantile,
          expected_quantile,
          atol=0.0,
          rtol=3e-4 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 12 for calling the _TwoPieceStudentTTest obj's underlying member method code with example usage: obj.testQuantile() without return types