code: def create_execution_test_objects(
      max_pending_trials: int = 8,
      resources: Optional[Dict[str, float]] = None,
      reuse_actors: bool = True,
      tune_controller_cls: Type[TuneController] = TuneController,
      **kwargs,
  ):
      os.environ["TUNE_MAX_PENDING_TRIALS_PG"] = str(max_pending_trials)
  
      resources = resources or {"CPU": 4}
  
      storage = kwargs.pop("storage", mock_storage_context())
  
      tune_controller = tune_controller_cls(
          reuse_actors=reuse_actors,
          storage=storage,
          **kwargs,
      )
      resource_manager = BudgetResourceManager(
          total_resources=resources
      )
      resource_updater = _FakeResourceUpdater(resource_manager)
      actor_manger = NoopActorManager(resource_manager)
      tune_controller._actor_manager = actor_manger
      tune_controller._class_cache = NoopClassCache()
      tune_controller._resource_updater = resource_updater
  
      return tune_controller, actor_manger, resource_manager
  
imports: import os
  import uuid
  from typing import Any, Callable, Dict, Optional, Tuple, Type, Union
  import ray
  from ray.air.execution import FixedResourceManager
  from ray.air.execution._internal import RayActorManager
  from ray.air.execution.resources import ResourceManager, ResourceRequest
  from ray.air.execution._internal.tracked_actor import TrackedActor
  from ray.tune.execution.tune_controller import TuneController
  from ray.tune.experiment import Trial
  from ray.tune.utils.resource_updater import _ResourceUpdater
  from ray.train.tests.util import mock_storage_context
label_desc: Use image node_id 1 for calling a global function with example usage: create_execution_test_objects(max_pending_trials, resources, reuse_actors, tune_controller_cls) and returns: tune_controller,  actor_manger,  resource_manager