code: def test_timeout(self) -> None:
      problem = SingleObjectiveBenchmarkProblem.from_botorch_synthetic(
          test_problem_class=Branin,
          test_problem_kwargs={},
          num_trials=1000,  # Unachievable num_trials
      )
  
      generation_strategy = get_sobol_botorch_modular_acquisition(
          model_cls=SingleTaskGP,
          acquisition_cls=qLogNoisyExpectedImprovement,
          distribute_replications=False,
      ).generation_strategy
  
      method = BenchmarkMethod(
          name=generation_strategy.name,
          generation_strategy=generation_strategy,
          scheduler_options=SchedulerOptions(
              max_pending_trials=1,
              init_seconds_between_polls=0,
              min_seconds_before_poll=0,
              timeout_hours=0.001,  # Strict timeout of 3.6 seconds
          ),
      )
  
      # Each replication will have a different number of trials
      result = benchmark_one_method_problem(
          problem=problem, method=method, seeds=(0, 1, 2, 3)
      )
  
      # Test the traces get composited correctly. The AggregatedResult's traces
      # should be the length of the shortest trace in the BenchmarkResults
      min_num_trials = min(
          len(res.optimization_trace) for res in result.results
      )
      self.assertEqual(len(result.optimization_trace), min_num_trials)
      self.assertEqual(len(result.score_trace), min_num_trials)
  
imports: import tempfile
  import numpy
  from ax.benchmark.benchmark import benchmark_multiple_problems_methods, benchmark_one_method_problem, benchmark_replication
  from ax.benchmark.benchmark_method import BenchmarkMethod, get_sequential_optimization_scheduler_options
  from ax.benchmark.benchmark_problem import SingleObjectiveBenchmarkProblem
  from ax.benchmark.benchmark_result import BenchmarkResult
  from ax.benchmark.methods.modular_botorch import get_sobol_botorch_modular_acquisition
  from ax.benchmark.problems.registry import get_problem
  from ax.modelbridge.modelbridge_utils import extract_search_space_digest
  from ax.service.utils.scheduler_options import SchedulerOptions
  from ax.storage.json_store.load import load_experiment
  from ax.storage.json_store.save import save_experiment
  from ax.utils.common.testutils import TestCase
  from ax.utils.common.typeutils import not_none
  from ax.utils.testing.benchmark_stubs import get_moo_surrogate, get_multi_objective_benchmark_problem, get_single_objective_benchmark_problem, get_sobol_benchmark_method, get_soo_surrogate
  from ax.utils.testing.core_stubs import get_dataset, get_experiment
  from ax.utils.testing.mock import fast_botorch_optimize
  from botorch.acquisition.logei import qLogNoisyExpectedImprovement
  from botorch.acquisition.multi_objective.monte_carlo import qNoisyExpectedHypervolumeImprovement
  from botorch.models.fully_bayesian import SaasFullyBayesianSingleTaskGP
  from botorch.models.gp_regression import FixedNoiseGP, SingleTaskGP
  from botorch.test_functions.synthetic import Branin
label_desc: Use image node_id 9 for calling the TestBenchmark obj's underlying member method code with example usage: obj.test_timeout() without return types