code: def test_bagged_predict_children(model_fit_helper):
      fit_args = dict(k_fold=3)
      dataset_name = "adult"
      model = BaggedEnsembleModel(
          model_base=LGBModel,
          model_base_kwargs=dict(
              hyperparameters=dict(num_boost_round=10)
          ),  # Speed up run
          hyperparameters={
              "fold_fitting_strategy": "sequential_local"
          },  # Speed up run
      )
      model_fit_helper.fit_and_validate_dataset(
          dataset_name=dataset_name,
          model=model,
          fit_args=fit_args,
          check_predict_children=True,
          sample_size=100,
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_bagged_predict_children(model_fit_helper) without return types