code: def not_used_col_has_zero_contribution():
      fr = h2o.import_file(
          path=pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
      first_row = fr[0, :]
  
      drf = H2ORandomForestEstimator(ntrees=1, max_depth=1, seed=1234)
      drf.train(x=list(range(2, fr.ncol)), y=1, training_frame=fr)
  
      gbm = H2OGradientBoostingEstimator(
          ntrees=1, max_depth=1, seed=1234
      )
      gbm.train(x=list(range(2, fr.ncol)), y=1, training_frame=fr)
  
      xgb = H2OXGBoostEstimator(ntrees=1, max_depth=1, seed=1234)
      xgb.train(x=list(range(2, fr.ncol)), y=1, training_frame=fr)
  
      print("DRF")
      assert_that_zero_contribution_has_zero_variable_importance(
          drf.predict_contributions(first_row),
          drf.varimp(use_pandas=True),
      )
      print("GBM")
      assert_that_zero_contribution_has_zero_variable_importance(
          gbm.predict_contributions(first_row),
          gbm.varimp(use_pandas=True),
      )
      print("XGB")
      assert_that_zero_contribution_has_zero_variable_importance(
          xgb.predict_contributions(first_row),
          xgb.varimp(use_pandas=True),
      )
  
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils, assert_equals, assert_not_equal
  from h2o.estimators import H2ORandomForestEstimator, H2OGradientBoostingEstimator, H2OXGBoostEstimator
label_desc: Use image node_id 2 for calling a global function with example usage: not_used_col_has_zero_contribution() without return types