code: def test_benchmark_multiple_problems_methods(self) -> None:
      aggs = benchmark_multiple_problems_methods(
          problems=[
              get_single_objective_benchmark_problem(num_trials=6)
          ],
          methods=[
              get_sobol_benchmark_method(),
              get_sobol_botorch_modular_acquisition(
                  model_cls=SingleTaskGP,
                  acquisition_cls=qLogNoisyExpectedImprovement,
                  distribute_replications=False,
              ),
          ],
          seeds=(0, 1),
      )
  
      self.assertEqual(len(aggs), 2)
      for agg in aggs:
          for col in ["mean", "P25", "P50", "P75"]:
              self.assertTrue((agg.score_trace[col] <= 100).all())
  
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 8 for calling the TestBenchmark obj's underlying member method code with example usage: obj.test_benchmark_multiple_problems_methods() without return types