code: def test_permutation_importance_plot_works():
      import matplotlib
  
      matplotlib.use("agg")
      import matplotlib.pyplot as plt
  
      # train model
      (
          model,
          fr,
      ) = (
          gbm_model_build()
      )  # type: Tuple[h2o.model.ModelBase, H2OFrame]
  
      # The following should not fail
      # barplot
      model.permutation_importance_plot(fr)
      # boxplot
      model.permutation_importance_plot(fr, n_repeats=5)
      plt.close("all")
  
file_path: h2o-3/h2o-py/tests/testdir_jira/pyunit_pubdev_7139_permutation_var_imp.py
imports: import sys, os
  import h2o
  from h2o.utils.typechecks import is_type
  from h2o.estimators import H2OGradientBoostingEstimator, H2OGeneralizedLinearEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 4 for calling a global function with example usage: test_permutation_importance_plot_works() without return types