code: def test_without_learned_objective(self) -> None:
      train_batch_shapes = [[], [1], [2]]
      test_batch_shapes = [[], [1], [3]]
      for train_batch_shape, test_batch_shape in product(
          train_batch_shapes, test_batch_shapes
      ):
          # Batched inputs `X_baseline` are currently unsupported by
          # prune_inferior_points
          prune_baseline_ = (
              [False] if len(train_batch_shape) > 0 else [False, True]
          )
          for prune_baseline in prune_baseline_:
              self._base_test_without_learned_objective(
                  train_batch_shape=torch.Size(train_batch_shape),
                  prune_baseline=prune_baseline,
                  test_batch_shape=torch.Size(test_batch_shape),
              )
  
imports: from itertools import product
  from typing import Dict
  from warnings import catch_warnings, simplefilter
  import torch
  from botorch.acquisition.input_constructors import get_acqf_input_constructor
  from botorch.acquisition.logei import qLogExpectedImprovement, qLogNoisyExpectedImprovement
  from botorch.acquisition.monte_carlo import qExpectedImprovement, qNoisyExpectedImprovement, qProbabilityOfImprovement
  from botorch.acquisition.objective import LearnedObjective
  from botorch.exceptions.warnings import InputDataWarning
  from botorch.fit import fit_gpytorch_mll
  from botorch.models import SingleTaskGP
  from botorch.sampling.normal import SobolQMCNormalSampler
  from botorch.utils.datasets import SupervisedDataset
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.mlls.exact_marginal_log_likelihood import ExactMarginalLogLikelihood
label_desc: Use image node_id 8 for calling the TestObjectiveAndConstraintIntegration obj's underlying member method code with example usage: obj.test_without_learned_objective() without return types