code: def download_model():
      prostate = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
      prostate["CAPSULE"] = prostate["CAPSULE"].asfactor()
  
      prostate_gbm = H2OGradientBoostingEstimator(
          distribution="bernoulli",
          ntrees=10,
          max_depth=8,
          min_rows=10,
          learn_rate=0.2,
      )
      prostate_gbm.train(
          x=["AGE", "RACE", "PSA", "VOL", "GLEASON"],
          y="CAPSULE",
          training_frame=prostate,
      )
  
      path = pyunit_utils.locate("results")
  
      downloaded_model_path = prostate_gbm.download_model(path=path)
      assert os.path.isfile(
          downloaded_model_path
      ), "Expected load file {0} to exist, but it does not.".format(
          downloaded_model_path
      )
  
      loaded_model = h2o.load_model(downloaded_model_path)
      assert isinstance(
          loaded_model, H2OGradientBoostingEstimator
      ), "Expected an H2OGradientBoostingEstimator, but got {0}".format(
          downloaded_model_path
      )
  
      uploaded_model = h2o.upload_model(downloaded_model_path)
      assert isinstance(
          uploaded_model, H2OGradientBoostingEstimator
      ), "Expected an H2OGradientBoostingEstimator, but got {0}".format(
          downloaded_model_path
      )
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  import os
  from h2o.estimators import H2OGradientBoostingEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: download_model() without return types