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)
