def test_predict_batched(self):
cs = SimpleRegressionPipeline.get_hyperparameter_search_space()
default = cs.get_default_configuration()
cls = SimpleRegressionPipeline(default)
X_train, Y_train, X_test, Y_test = get_dataset(dataset='boston')
cls.fit(X_train, Y_train)
X_test_ = X_test.copy()
prediction_ = cls.predict(X_test_)
cls_predict = mock.Mock(wraps=cls.pipeline_)
cls.pipeline_ = cls_predict
prediction = cls.predict(X_test, batch_size=20)
self.assertEqual((356,), prediction.shape)
self.assertEqual(18, cls_predict.predict.call_count)
assert_array_almost_equal(prediction_, prediction)
def test_predict_batched(self):
cs = SimpleRegressionPipeline.get_hyperparameter_search_space()
default = cs.get_default_configuration()
cls = SimpleRegressionPipeline(default)
X_train, Y_train, X_test, Y_test = get_dataset(dataset='boston')
cls.fit(X_train, Y_train)
X_test_ = X_test.copy()
prediction_ = cls.predict(X_test_)
cls_predict = mock.Mock(wraps=cls.pipeline_)
cls.pipeline_ = cls_predict
prediction = cls.predict(X_test, batch_size=20)
self.assertEqual((356,), prediction.shape)
self.assertEqual(18, cls_predict.predict.call_count)
assert_array_almost_equal(prediction_, prediction)
def test_predict_batched(self):
cs = SimpleRegressionPipeline.get_hyperparameter_search_space(
include={'regressor': ['decision_tree']})
default = cs.get_default_configuration()
cls = SimpleRegressionPipeline(default)
X_train, Y_train, X_test, Y_test = get_dataset(dataset='diabetes')
cls.fit(X_train, Y_train)
X_test_ = X_test.copy()
prediction_ = cls.predict(X_test_)
cls_predict = unittest.mock.Mock(wraps=cls.pipeline_)
cls.pipeline_ = cls_predict
prediction = cls.predict(X_test, batch_size=20)
self.assertEqual((292, ), prediction.shape)
self.assertEqual(15, cls_predict.predict.call_count)
assert_array_almost_equal(prediction_, prediction)
