code: def prepare_dataset():
      prostate = h2o.import_file(
          path=pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
      prostate["CAPSULE"] = prostate["CAPSULE"].asfactor()
      prostate["RACE"] = prostate["RACE"].asfactor()
      predictors = [
          "ID",
          "AGE",
          "RACE",
          "DPROS",
          "DCAPS",
          "PSA",
          "VOL",
          "GLEASON",
      ]
      response = "CAPSULE"
  
      return prostate, predictors, response
  
imports: import os
  import sys
  import h2o
  from h2o.estimators import H2OGradientBoostingEstimator
  from tests import pyunit_utils, compare_frames_local
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_dataset() and returns: prostate,  predictors,  response