code: def testLogPDF(self):
      dist = self.make_two_piece_normals()
  
      x = np.array([[-35.0], [3.0], [20.0]], 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: SN2.
      expected_log_pdf = np.array(
          [
              [-7.323596, -10.44152, -16.03311],
              [-3.262346, -3.221524, -3.261648],
              [-5.831235, -4.666524, -4.078539],
          ],
          dtype=self.dtype,
      )
  
      self.assertAllEqual(log_pdf.shape, expected_log_pdf.shape)
      self.assertAllClose(log_pdf, expected_log_pdf)
  
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 10 for calling the _TwoPieceNormalTest obj's underlying member method code with example usage: obj.testLogPDF() without return types