code: def test_eval_metric_early_stopping_native_scoring_only():
      history = check_eval_metric_early_stopping(
          True, eval_metric="mae"
      )
      for col in history.columns:
          if col.startswith("training_") and col != "training_custom":
              is_missing = history[col].isnull()
              # scoring history is not defined for H2O metrics...
              assert is_missing.sum() == len(is_missing) - 1
              # ...except for the final scoring metric
              assert not is_missing.iloc[-1]
  
file_path: h2o-3/h2o-py/tests/testdir_algos/xgboost/pyunit_xgboost_eval_metric_stopping.py
imports: import sys
  from h2o import upload_custom_metric
  from tests import pyunit_utils
  from tests.pyunit_utils import dataset_prostate
  from h2o.estimators.xgboost import H2OXGBoostEstimator
  from tests.pyunit_utils import CustomMaeFunc
label_desc: Use image node_id 5 for calling a global function with example usage: test_eval_metric_early_stopping_native_scoring_only() without return types