code: def _construct_dummy_fold_strategy(
      num_jobs,
      model_base_cls=AbstractModel,
      time_limit=None,
      num_folds_parallel=8,
  ):
      dummy_model_base = model_base_cls()
      dummy_bagged_ensemble_model = BaggedEnsembleModel(
          dummy_model_base
      )
      train_data, test_data = _prepare_data()
      args = dict(
          model_base=dummy_model_base,
          model_base_kwargs=dict(),
          bagged_ensemble_model=dummy_bagged_ensemble_model,
          X=train_data,
          y=test_data,
          X_pseudo=None,
          y_pseudo=None,
          sample_weight=None,
          time_limit=time_limit,
          time_start=time.time(),
          models=[],
          oof_pred_proba=np.array([]),
          oof_pred_model_repeats=np.array([]),
          save_folds=True,
          num_cpus=ResourceManager.get_cpu_count(),
          num_gpus=ResourceManager.get_gpu_count(),
          num_jobs=num_jobs,
          num_folds_parallel=num_folds_parallel,
          time_limit_fold_ratio=1,
          max_memory_usage_ratio=1,
      )
      return ParallelLocalFoldFittingStrategy(**args)
  
file_path: autogluon/core/tests/unittests/test_parallel_local_folding.py
imports: import math
  import time
  from unittest.mock import patch
  import numpy
  import pandas
  from autogluon.common import space
  from autogluon.common.utils.resource_utils import ResourceManager
  from autogluon.core.models import AbstractModel
  from autogluon.core.models.ensemble.bagged_ensemble_model import BaggedEnsembleModel
  from autogluon.core.models.ensemble.fold_fitting_strategy import ParallelLocalFoldFittingStrategy
  from autogluon.core.searcher import LocalRandomSearcher
label_desc: Use image node_id 2 for calling a global function with example usage: _construct_dummy_fold_strategy(num_jobs, model_base_cls, time_limit, num_folds_parallel) and returns: ParallelLocalFoldFittingStrategy