code: def test_init(self):
      mm = MockModel(MockPosterior(mean=torch.rand(2, 1)))
      # test default init
      acqf = DummyMultiObjectiveAnalyticAcquisitionFunction(model=mm)
      self.assertTrue(
          acqf.posterior_transform is None
      )  # is None by default
      # test custom init
      posterior_transform = DummyPosteriorTransform()
      acqf = DummyMultiObjectiveAnalyticAcquisitionFunction(
          model=mm, posterior_transform=posterior_transform
      )
      self.assertEqual(acqf.posterior_transform, posterior_transform)
      # test unsupported objective
      with self.assertRaises(UnsupportedError):
          DummyMultiObjectiveAnalyticAcquisitionFunction(
              model=mm,
              posterior_transform=IdentityMCMultiOutputObjective(),
          )
      acqf = DummyMultiObjectiveAnalyticAcquisitionFunction(model=mm)
      # test set_X_pending
      with self.assertRaises(UnsupportedError):
          acqf.set_X_pending()
  
imports: import torch
  from botorch.acquisition.multi_objective.analytic import ExpectedHypervolumeImprovement, MultiObjectiveAnalyticAcquisitionFunction
  from botorch.acquisition.multi_objective.objective import IdentityMCMultiOutputObjective
  from botorch.acquisition.objective import PosteriorTransform
  from botorch.exceptions.errors import BotorchError, UnsupportedError
  from botorch.posteriors import GPyTorchPosterior
  from botorch.utils.multi_objective.box_decompositions.non_dominated import NondominatedPartitioning
  from botorch.utils.testing import BotorchTestCase, MockModel, MockPosterior
  from torch import Tensor
label_desc: Use image node_id 2 for calling the TestMultiObjectiveAnalyticAcquisitionFunction obj's underlying member method code with example usage: obj.test_init() without return types