code: def benchmark_replication(
      problem: BenchmarkProblemBase,
      method: BenchmarkMethod,
      seed: int,
  ) -> BenchmarkResult:
      """Runs one benchmarking replication (equivalent to one optimization loop).
  
      Args:
          problem: The BenchmarkProblem to test against (can be synthetic or real)
          method: The BenchmarkMethod to test
          seed: The seed to use for this replication, set using `manual_seed`
              from `botorch.utils.sampling`.
      """
  
      experiment = _create_benchmark_experiment(
          problem=problem, method_name=method.name
      )
  
      scheduler = Scheduler(
          experiment=experiment,
          generation_strategy=method.generation_strategy.clone_reset(),
          options=method.scheduler_options,
      )
  
      with manual_seed(seed=seed):
          scheduler.run_n_trials(max_trials=problem.num_trials)
  
      optimization_trace = np.array(scheduler.get_trace())
      num_baseline_trials = (
          scheduler.standard_generation_strategy._steps[0].num_trials
      )
      score_trace = compute_score_trace(
          optimization_trace=optimization_trace,
          num_baseline_trials=num_baseline_trials,
          problem=problem,
      )
  
      fit_time, gen_time = get_model_times(
          experiment=scheduler.experiment
      )
  
      return BenchmarkResult(
          name=scheduler.experiment.name,
          seed=seed,
          experiment=scheduler.experiment,
          optimization_trace=optimization_trace,
          score_trace=score_trace,
          fit_time=fit_time,
          gen_time=gen_time,
      )
  
file_path: Ax/ax/benchmark/benchmark.py
imports: from itertools import product
  from logging import Logger
  from time import time
  from typing import Iterable, List
  import numpy
  from ax.benchmark.benchmark_method import BenchmarkMethod
  from ax.benchmark.benchmark_problem import BenchmarkProblemBase, BenchmarkProblemWithKnownOptimum
  from ax.benchmark.benchmark_result import AggregatedBenchmarkResult, BenchmarkResult
  from ax.core.experiment import Experiment
  from ax.core.utils import get_model_times
  from ax.service.scheduler import Scheduler
  from ax.utils.common.logger import get_logger
  from botorch.utils.sampling import manual_seed
label_desc: Use image node_id 3 for calling a global function with example usage: benchmark_replication(problem, method, seed) and returns: BenchmarkResult