code: def test_fix_features(self):
      (
          X,
          X_null_two,
          X_expected,
          X_expected_null_two,
      ) = self._getTensors()
      X.requires_grad_(True)
      X_null_two.requires_grad_(True)
  
      X_fix = fix_features(X, {0: -1, 2: -2})
      X_fix_null_two = fix_features(X_null_two, {0: -1, 2: None})
  
      self.assertTrue(torch.equal(X_fix, X_expected))
      self.assertTrue(torch.equal(X_fix_null_two, X_expected_null_two))
  
      def f(X):
          return X.sum()
  
      f(X).backward()
      self.assertTrue(torch.equal(X.grad, torch.ones_like(X)))
      X.grad.zero_()
  
      f(X_fix).backward()
      self.assertTrue(
          torch.equal(
              X.grad,
              torch.tensor(
                  [[0.0, 1.0, 0.0], [0.0, 1.0, 0.0]], device=self.device
              ),
          )
      )
  
      f(X_null_two).backward()
      self.assertTrue(torch.equal(X_null_two.grad, torch.ones_like(X)))
      X_null_two.grad.zero_()
      f(X_fix_null_two).backward()
      self.assertTrue(
          torch.equal(
              X_null_two.grad,
              torch.tensor(
                  [[0.0, 1.0, 0.0], [0.0, 1.0, 0.0]], device=self.device
              ),
          )
      )
  
imports: from __future__ import annotations
  import warnings
  import torch
  from botorch import settings
  from botorch.acquisition.fixed_feature import FixedFeatureAcquisitionFunction
  from botorch.acquisition.monte_carlo import qExpectedImprovement, qNoisyExpectedImprovement
  from botorch.acquisition.multi_objective.max_value_entropy_search import qMultiObjectiveMaxValueEntropy
  from botorch.acquisition.multi_objective.monte_carlo import qExpectedHypervolumeImprovement, qNoisyExpectedHypervolumeImprovement
  from botorch.exceptions import BotorchError
  from botorch.exceptions.warnings import BotorchWarning
  from botorch.models import ModelListGP, SingleTaskGP
  from botorch.models.transforms.input import Warp
  from botorch.optim.utils import columnwise_clamp, fix_features, get_X_baseline
  from botorch.sampling.normal import IIDNormalSampler
  from botorch.utils.multi_objective.box_decompositions.non_dominated import FastNondominatedPartitioning
  from botorch.utils.testing import BotorchTestCase, MockModel, MockPosterior
label_desc: Use image node_id 2 for calling the TestFixFeatures obj's underlying member method code with example usage: obj.test_fix_features() and returns: X