code: def setUp(self):
      super().setUp()
      self.model = mock.MagicMock()
      self.objective = DummyMCMultiOutputObjective()
      self.X_observed = torch.tensor([[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]])
      self.X_pending = torch.tensor([[1.0, 3.0, 4.0]])
      self.mc_samples = 250
      self.qmc = True
      self.ref_point = [0.0, 0.0]
      self.Y = torch.tensor([[1.0, 2.0]])
      self.seed = 1
  
imports: import warnings
  from itertools import product
  from unittest import mock
  import torch
  from botorch.acquisition.multi_objective.objective import MCMultiOutputObjective, UnstandardizeMCMultiOutputObjective
  from botorch.acquisition.multi_objective.utils import compute_sample_box_decomposition, get_default_partitioning_alpha, prune_inferior_points_multi_objective, random_search_optimizer, sample_optimal_points
  from botorch.exceptions.errors import UnsupportedError
  from botorch.models.gp_regression import SingleTaskGP
  from botorch.models.model_list_gp_regression import ModelListGP
  from botorch.models.transforms.outcome import Standardize
  from botorch.utils.gp_sampling import get_gp_samples
  from botorch.utils.multi_objective import is_non_dominated
  from botorch.utils.testing import BotorchTestCase, MockModel, MockPosterior
  from torch import Tensor
label_desc: Use image node_id 1 for calling the TestMultiObjectiveUtils obj's underlying member method code with example usage: obj.setUp() without return types