code: def gbm_monotone_synthetic_test():
      metrics = np.array(list(map(train_models, range(10))))
      mean_rmse = metrics.mean(axis=0)
      print(
          "GBM RMSE: %s, XGBoost RMSE: %s"
          % (mean_rmse[0], mean_rmse[1])
      )
      assert (mean_rmse[0] - mean_rmse[1]) / mean_rmse[1] <= 0.07
  
imports: from h2o.estimators.xgboost import *
  from h2o.estimators.gbm import *
  from tests import pyunit_utils
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: gbm_monotone_synthetic_test() without return types