code: def test_weights_column_not_in_train():
      try:
          df = h2o.import_file(
              pyunit_utils.locate("smalldata/prostate/prostate.csv")
          )
          gbm = H2OGradientBoostingEstimator(
              seed=1234, weights_column="foo"
          )
          gbm.train(y=-1, training_frame=df)
          assert False, "Model building should fail."
      except H2OResponseError as e:
          assert "ERRR on field: _weights_column" in str(
              e
          ), "Model building should fail with this in message."
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
  from h2o.exceptions import H2OResponseError
label_desc: Use image node_id 1 for calling a global function with example usage: test_weights_column_not_in_train() without return types