from tensorflow.python.training import adagrad

        linear_feature_columns=(bucketized_feature,),
        linear_optimizer=ftrl.FtrlOptimizer(learning_rate=0.1),
        dnn_feature_columns=(cont_feature,),
        dnn_hidden_units=(3, 3),
        dnn_optimizer=adagrad.AdagradOptimizer(learning_rate=0.1))

    input_fn = test_data.iris_input_logistic_fn
    metrics = classifier.fit(input_fn=input_fn, steps=_ITERS).evaluate(
