from tensorflow.python.feature_column import feature_column_lib as core_feature_column

    learner_config.constraints.max_tree_depth = 1
    model_dir = tempfile.mkdtemp()
    config = run_config.RunConfig()

    regressor = estimator.GradientBoostedDecisionTreeRegressor(
        learner_config=learner_config,
        num_trees=1,
        examples_per_layer=3,
        model_dir=model_dir,
        config=config,
        feature_columns=[core_feature_column.numeric_column("x")],
        use_core_libs=True)

    regressor.fit(input_fn=_train_input_fn, steps=15)
    regressor.evaluate(input_fn=_eval_input_fn, steps=1)
    regressor.export(self._export_dir_base)

  def testRankingDontThrowExceptionForForEstimator(self):
    learner_config = learner_pb2.LearnerConfig()
    learner_config.num_classes = 2
