code: def _get_acqf_inputs(
      self, train_batch_shape: torch.Size, m: int
  ) -> Dict:
      train_x = torch.rand(
          (*train_batch_shape, 5, self.d), **self.tkwargs
      )
      y = torch.rand((*train_batch_shape, 5, m), **self.tkwargs)
  
      training_data = SupervisedDataset(
          X=train_x,
          Y=y,
          feature_names=[f"x{i}" for i in range(self.d)],
          outcome_names=[f"y{i}" for i in range(m)],
      )
      utility = y.sum(-1).unsqueeze(-1)
  
      with catch_warnings():
          simplefilter("ignore", category=InputDataWarning)
          model = SingleTaskGP(train_x, y)
      mll = ExactMarginalLogLikelihood(model.likelihood, model)
      fit_gpytorch_mll(mll=mll)
  
      with catch_warnings():
          simplefilter("ignore", category=InputDataWarning)
          pref_model = SingleTaskGP(y, utility)
      pref_mll = ExactMarginalLogLikelihood(
          pref_model.likelihood, pref_model
      )
      fit_gpytorch_mll(mll=pref_mll)
      return {
          "training_data": training_data,
          "model": model,
          "pref_model": pref_model,
          "train_x": train_x,
      }
  
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 2 for calling the TestObjectiveAndConstraintIntegration obj's underlying member method code with example usage: obj._get_acqf_inputs(train_batch_shape, m) and returns: dict