code: def test_repr(self):
      for d in self.distributions:
          r = repr(d)
          self.assertTrue(f"trunc: {d.trunc}" in r)
          self.assertTrue(f"gauss: {d.gauss}" in r)
          self.assertTrue(
              f"cross_covariance_matrix: {d.cross_covariance_matrix.shape}"
              in r
          )
  
imports: from __future__ import annotations
  from copy import deepcopy
  from itertools import count
  from typing import Any, Dict, Optional, Sequence, Tuple
  import torch
  from botorch.utils.probability.mvnxpb import MVNXPB
  from botorch.utils.probability.truncated_multivariate_normal import TruncatedMultivariateNormal
  from botorch.utils.probability.unified_skew_normal import UnifiedSkewNormal
  from botorch.utils.testing import BotorchTestCase
  from linear_operator.operators import DenseLinearOperator
  from torch import Tensor
  from torch.distributions import MultivariateNormal
  from torch.special import ndtri
label_desc: Use image node_id 10 for calling the TestUnifiedSkewNormal obj's underlying member method code with example usage: obj.test_repr() without return types