code: def test_set_baseline_Y(self):
      mars = MARS(
          alpha=0.5,
          n_w=3,
          chebyshev_weights=[0.5, 0.5],
      )
      perturbation = InputPerturbation(
          perturbation_set=torch.tensor(
              [[0.0, 0.0], [0.5, 0.5], [1.0, 1.0]]
          )
      )
      model = GenericDeterministicModel(f=lambda X: X, num_outputs=2)
      model.input_transform = perturbation
      X_baseline = torch.tensor([[0.0, 0.0], [1.0, 1.0]])
      mars.set_baseline_Y(model=model, X_baseline=X_baseline)
      self.assertTrue(
          torch.equal(mars.baseline_Y, torch.tensor([[1.5, 1.5]]))
      )
      # With Y_samples.
      mars._baseline_Y = None
      Y_samples = model.posterior(X_baseline).mean
      with warnings.catch_warnings(record=True) as ws, settings.debug(
          True
      ):
          mars.set_baseline_Y(
              model=model, X_baseline=X_baseline, Y_samples=Y_samples
          )
      self.assertTrue(
          torch.equal(mars.baseline_Y, torch.tensor([[1.5, 1.5]]))
      )
      self.assertTrue(any(w.category == BotorchWarning for w in ws))
      # With pre-processing function.
      mars = MARS(
          alpha=0.5,
          n_w=3,
          chebyshev_weights=[0.5, 0.5],
          preprocessing_function=lambda Y: -Y,
      )
      mars.set_baseline_Y(model=model, X_baseline=X_baseline)
      self.assertTrue(
          torch.equal(mars.baseline_Y, torch.tensor([[-0.5, -0.5]]))
      )
  
imports: import warnings
  from typing import Optional
  import torch
  from botorch import settings
  from botorch.acquisition.multi_objective.multi_output_risk_measures import IndependentCVaR, IndependentVaR, MARS, MultiOutputExpectation, MultiOutputRiskMeasureMCObjective, MultiOutputWorstCase, MVaR
  from botorch.acquisition.multi_objective.objective import IdentityMCMultiOutputObjective, WeightedMCMultiOutputObjective
  from botorch.exceptions.errors import UnsupportedError
  from botorch.exceptions.warnings import BotorchWarning
  from botorch.models.deterministic import GenericDeterministicModel
  from botorch.models.transforms.input import InputPerturbation
  from botorch.utils.multi_objective.pareto import is_non_dominated
  from botorch.utils.testing import BotorchTestCase
  from torch import Tensor
label_desc: Use image node_id 2 for calling the TestMARS obj's underlying member method code with example usage: obj.test_set_baseline_Y() without return types