def testNoDNNFeatureColumns(self): learner_config = learner_pb2.LearnerConfig() learner_config.num_classes = 2 with self.assertRaisesRegexp(ValueError, "dnn_feature_columns must be specified"): classifier = estimator.DNNBoostedTreeCombinedClassifier( dnn_hidden_units=[1], dnn_feature_columns=[], tree_learner_config=learner_config, num_trees=1, tree_examples_per_layer=3, n_classes=2) classifier.fit(input_fn=_train_input_fn, steps=5)
def testFitAndEvaluateDontThrowException(self): learner_config = learner_pb2.LearnerConfig() learner_config.num_classes = 2 learner_config.constraints.max_tree_depth = 1 model_dir = tempfile.mkdtemp() config = run_config.RunConfig() classifier = estimator.DNNBoostedTreeCombinedClassifier( dnn_hidden_units=[1], dnn_feature_columns=[feature_column.real_valued_column("x")], tree_learner_config=learner_config, num_trees=1, tree_examples_per_layer=3, n_classes=2, model_dir=model_dir, config=config, dnn_steps_to_train=10, dnn_input_layer_to_tree=False, tree_feature_columns=[feature_column.real_valued_column("x")]) classifier.fit(input_fn=_train_input_fn, steps=15) classifier.evaluate(input_fn=_eval_input_fn, steps=1)