code: def get_benchmark_problem() -> BenchmarkProblem:
      return BenchmarkProblem.from_botorch(
          test_problem_class=Branin,
          test_problem_kwargs={},
          num_trials=4,
      )
  
imports: import numpy
  from ax.benchmark.benchmark_method import BenchmarkMethod
  from ax.benchmark.benchmark_problem import BenchmarkProblem, MultiObjectiveBenchmarkProblem, SingleObjectiveBenchmarkProblem
  from ax.benchmark.benchmark_result import AggregatedBenchmarkResult, BenchmarkResult
  from ax.benchmark.problems.surrogate import MOOSurrogateBenchmarkProblem, SOOSurrogateBenchmarkProblem
  from ax.core.experiment import Experiment
  from ax.modelbridge.generation_strategy import GenerationStep, GenerationStrategy
  from ax.modelbridge.registry import Models
  from ax.models.torch.botorch_modular.surrogate import Surrogate
  from ax.service.scheduler import SchedulerOptions
  from ax.utils.common.constants import Keys
  from ax.utils.testing.core_stubs import get_branin_multi_objective_optimization_config, get_branin_optimization_config, get_branin_search_space
  from botorch.acquisition.monte_carlo import qNoisyExpectedImprovement
  from botorch.models.gp_regression import SingleTaskGP
  from botorch.test_functions.multi_objective import BraninCurrin
  from botorch.test_functions.synthetic import Branin
label_desc: Use image node_id 1 for calling a global function with example usage: get_benchmark_problem() and returns: BenchmarkProblem