code: def testMean(self):
      dist = self.make_two_piece_student_ts()
  
      mean = self.evaluate(dist.mean())
      # The following values were calculated using the R package gamlss.dist.
      # Package version: 5.3-2. Distribution: ST3.
      expected_mean = np.array(
          [-2.35825881, 3.0, 8.31037405], dtype=self.dtype
      )
  
      self.assertDTypeEqual(mean, self.dtype)
      self.assertShapeEqual(mean, expected_mean)
      self.assertAllClose(mean, expected_mean)
  
      dist = two_piece_student_t.TwoPieceStudentT(
          df=self.dtype(1.0),
          loc=self.dtype(0.0),
          scale=self.dtype(1.0),
          skewness=self.dtype(1.0),
          validate_args=True,
      )
  
      mean = self.evaluate(dist.mean())
      self.assertDTypeEqual(mean, self.dtype)
      self.assertAllNan(mean)
  
      with self.assertRaisesOpError(
          "mean not defined for " "components of df <= 1"
      ):
          dist = two_piece_student_t.TwoPieceStudentT(
              df=self.dtype(1.0),
              loc=self.dtype(0.0),
              scale=self.dtype(1.0),
              skewness=self.dtype(1.0),
              allow_nan_stats=False,
              validate_args=True,
          )
          self.evaluate(dist.mean())
  
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 13 for calling the _TwoPieceStudentTTest obj's underlying member method code with example usage: obj.testMean() without return types