code: def test_gen_candidates_with_fixed_features(
      self,
      gen_candidates=gen_candidates_scipy,
      options=None,
      timeout_sec=None,
  ):
      options = options or {}
      options = {**options, "maxiter": 5}
      for double in (True, False):
          self._setUp(double=double, expand=True)
          acqfs = [
              qExpectedImprovement(self.model, best_f=self.f_best),
              qKnowledgeGradient(
                  self.model, num_fantasies=4, current_value=self.f_best
              ),
          ]
          for acqf in acqfs:
              ics = self.initial_conditions
              if isinstance(acqf, qKnowledgeGradient):
                  ics = ics.repeat(5, 1)
              candidates, _ = gen_candidates(
                  initial_conditions=ics,
                  acquisition_function=acqf,
                  lower_bounds=0,
                  upper_bounds=1,
                  fixed_features={1: 0.25},
                  options=options,
                  timeout_sec=timeout_sec,
              )
  
              if isinstance(acqf, qKnowledgeGradient):
                  candidates = acqf.extract_candidates(candidates)
  
              candidates = candidates.squeeze(0)
              self.assertTrue(-EPS <= candidates[0] <= 1 + EPS)
              self.assertTrue(candidates[1].item() == 0.25)
  
imports: import math
  import warnings
  from unittest import mock
  import torch
  from botorch.acquisition import qExpectedImprovement, qKnowledgeGradient
  from botorch.exceptions.warnings import OptimizationWarning
  from botorch.fit import fit_gpytorch_mll
  from botorch.generation.gen import gen_candidates_scipy, gen_candidates_torch, get_best_candidates
  from botorch.models import SingleTaskGP
  from botorch.utils.testing import BotorchTestCase, MockAcquisitionFunction
  from gpytorch import settings
  from gpytorch.mlls.exact_marginal_log_likelihood import ExactMarginalLogLikelihood
  from scipy.optimize import OptimizeResult
label_desc: Use image node_id 5 for calling the TestGenCandidates obj's underlying member method code with example usage: obj.test_gen_candidates_with_fixed_features(gen_candidates, options, timeout_sec) without return types