code: def test_different_for_maximize_and_minimize(self):
      train_X = torch.rand(15, 1, device=self.device)
  
      quality_function_for_max = ExpectedImprovementQualityFunction(
          self.previous_model, maximize=True
      )
      scores_for_max = quality_function_for_max(train_X)
  
      quality_function_for_min = ExpectedImprovementQualityFunction(
          self.previous_model, maximize=False
      )
      scores_for_min = quality_function_for_min(train_X)
  
      self.assertFalse(torch.equal(scores_for_min, scores_for_max))
  
imports: import gc
  import torch
  from botorch.exceptions.errors import UnsupportedError
  from botorch.models.approximate_gp import SingleTaskVariationalGP
  from botorch.models.utils.inducing_point_allocators import _pivoted_cholesky_init, ExpectedImprovementQualityFunction, GreedyImprovementReduction, GreedyVarianceReduction, UnitQualityFunction
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.kernels import MaternKernel, ScaleKernel
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.mlls import VariationalELBO
label_desc: Use image node_id 4 for calling the TestExpectedImprovementQualityFunction obj's underlying member method code with example usage: obj.test_different_for_maximize_and_minimize() without return types