code: def testLogPDF(self):
      dist = self.make_two_piece_student_ts()
  
      x = np.array(
          [[-123.0], [-4.0], [3.0], [10.0], [88.0]], dtype=self.dtype
      )
  
      log_pdf = self.evaluate(dist.log_prob(x))
      # The following values were calculated using the R package gamlss.dist.
      # Package version: 5.3-2. Distribution: ST3.
      # pylint: disable=bad-whitespace
      expected_log_pdf = np.array(
          [
              [-12.982363352394, -14.857559749935, -16.838090065368],
              [-3.461022986748, -3.537764063953, -3.775393050210],
              [-3.303825343266, -3.263003348746, -3.303127355368],
              [-3.778307595268, -3.537764063953, -3.461096404463],
              [-14.186695915359, -12.251526109418, -10.495893758498],
          ],
          dtype=self.dtype,
      )
      # pylint: enable=bad-whitespace
  
      self.assertDTypeEqual(log_pdf, self.dtype)
      self.assertShapeEqual(log_pdf, expected_log_pdf)
      self.assertAllClose(
          log_pdf,
          expected_log_pdf,
          atol=0.0,
          rtol=1e-6 if self.dtype == np.float32 else 2e-9,
      )
  
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 9 for calling the _TwoPieceStudentTTest obj's underlying member method code with example usage: obj.testLogPDF() without return types