code: def partial_plots():
      data = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
  
      x = ["AGE", "RACE"]
      y = "CAPSULE"
      data[y] = data[y].asfactor()
      data["RACE"] = data["RACE"].asfactor()
  
      gbm_model = H2OGradientBoostingEstimator(
          ntrees=50, learn_rate=0.05
      )
      gbm_model.train(x=x, y=y, training_frame=data)
  
      # test saving:
      with TemporaryDirectory() as tmpdir:
          path1 = "{}/plot1.png".format(tmpdir)
          path2 = "{}/plot2.png".format(tmpdir)
          test_plot_result_saving(
              gbm_model.partial_plot(
                  frame=data,
                  cols=["AGE"],
                  server=True,
                  plot=True,
                  row_index=1,
              ),
              path2,
              gbm_model.partial_plot(
                  frame=data,
                  cols=["AGE"],
                  server=True,
                  plot=True,
                  row_index=1,
                  save_plot_path=path1,
              ),
              path1,
          )
  
imports: import sys
  import matplotlib
  from h2o.automl import H2OAutoML
  from h2o.estimators import H2OGradientBoostingEstimator
  from h2o.exceptions import H2OError
  from h2o.transforms import H2OPCA
  import h2o
  from tests import pyunit_utils, test_plot_result_saving, TemporaryDirectory
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator, H2OGeneralizedLinearEstimator
  from h2o.plot import decorate_plot_result, RAISE_ON_FIGURE_ACCESS
label_desc: Use image node_id 5 for calling a global function with example usage: partial_plots() without return types