code: def check_warnings(theModel, warnNumber, dataset):
      buffer = StringIO()  # redirect output
      sys.stderr = buffer
      pred_h2o = theModel.predict(dataset)
      warn_phrase = "missing"
      sys.stderr = (
          sys.__stderr__
      )  # redirect printout back to normal path
      try:  # for python 2.7
          assert len(buffer.buflist) == warnNumber
          if (
              len(buffer.buflist) > 0
          ):  # check to make sure we have the right number of warning
              for index in range(len(buffer.buflist)):
                  print(
                      "*** captured warning message: {0}".format(
                          buffer.buflist[index]
                      )
                  )
                  assert (
                      warn_phrase in buffer.buflist[index]
                  ), "Wrong warning message is received."
      except:  # for python 3.
          if warnNumber == 0:
              try:
                  warns = buffer.getvalue()
                  assert False, "Warning not expected but received..."
              except:
                  assert True, "Warning not expected but received..."
          else:
              warns = buffer.getvalue()
              print("*** captured warning message: {0}".format(warns))
              countWarns = warns.split().count(warn_phrase)
              assert (
                  countWarns == warnNumber
              ), "Expected number of warning: {0}.  But received {1}.".format(
                  warnNumber, countWarns
              )
  
imports: import sys, os
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
label_desc: Use image node_id 2 for calling a global function with example usage: check_warnings(theModel, warnNumber, dataset) without return types