code: def test_explanation_automl_pareto_front():
      train = h2o.upload_file(
          pyunit_utils.locate("smalldata/logreg/prostate.csv")
      )
      y = "CAPSULE"
      train[y] = train[y].asfactor()
      aml = H2OAutoML(seed=1234, max_models=5)
      aml.train(y=y, training_frame=train)
  
      assert isinstance(
          aml.pareto_front(train).figure(), matplotlib.pyplot.Figure
      )
      matplotlib.pyplot.close()
  
      assert isinstance(
          aml.pareto_front(None, "mse", "rmse").figure(),
          matplotlib.pyplot.Figure,
      )
      matplotlib.pyplot.close()
  
imports: import os
  import sys
  import pandas
  from h2o.grid import H2OGridSearch
  import matplotlib
  import h2o
  import pandas
  import matplotlib.pyplot
  from tests import pyunit_utils, test_plot_result_saving
  from h2o.automl import H2OAutoML
  from h2o.estimators import *
  from h2o.explanation._explain import H2OExplanation
label_desc: Use image node_id 14 for calling a global function with example usage: test_explanation_automl_pareto_front() without return types