code: def test_inducing_points_different_when_minimizing(self):
      ipa_for_max = GreedyImprovementReduction(
          self.previous_model, maximize=True
      )
      ipa_for_min = GreedyImprovementReduction(
          self.previous_model, maximize=False
      )
  
      train_X = torch.rand(15, 1, device=self.device)
      inducing_points_for_max = ipa_for_max.allocate_inducing_points(
          inputs=train_X,
          covar_module=MaternKernel(),
          num_inducing=10,
          input_batch_shape=torch.Size([]),
      )
      inducing_points_for_min = ipa_for_min.allocate_inducing_points(
          inputs=train_X,
          covar_module=MaternKernel(),
          num_inducing=10,
          input_batch_shape=torch.Size([]),
      )
  
      self.assertFalse(
          torch.equal(inducing_points_for_min, inducing_points_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 6 for calling the TestGreedyImprovementReduction obj's underlying member method code with example usage: obj.test_inducing_points_different_when_minimizing() without return types