code: def test_maxrsweep_replacement():
      allPreds = a = list(range(10, 30, 10))
      for npred in allPreds:
          h2o.remove_all()
          train = h2o.import_file(
              pyunit_utils.locate(
                  "bigdata/laptop/model_selection/maxrglm200Cols50KRows.csv"
              )
          )
          response = "response"
          predictors = train.names
          predictors.remove(response)
          maxrsweep3_model = H2OModelSelectionEstimator(
              mode="maxrsweep",
              max_predictor_number=npred,
              intercept=True,
              build_glm_model=False,
          )
          maxrsweep3_model.train(
              x=predictors, y=response, training_frame=train
          )
          print(
              "Maxrsweep Run time for npred {1} (ms): {0}".format(
                  maxrsweep3_model._model_json["output"]["run_time"],
                  npred,
              )
          )
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.model_selection import H2OModelSelectionEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_maxrsweep_replacement() without return types