def test_fit_instantiates_component(self):
"""Make sure that if a preprocessor is added, it's fit
method is called"""
preprocessing_components.add_preprocessor(CrashPreprocessor)
# We reduce the search space as forbidden clauses prevent to instantiate
# the user defined preprocessor manually
cls = SimpleClassificationPipeline(include={'classifier': ['random_forest']})
cs = cls.get_hyperparameter_search_space()
self.assertIn('CrashPreprocessor', str(cs))
config = cs.sample_configuration()
try:
config['feature_preprocessor:__choice__'] = 'CrashPreprocessor'
except Exception as e:
# In case of failure clean up the components and print enough information
# to clean up with check in the future
del preprocessing_components._addons.components['CrashPreprocessor']
self.fail("cs={} config={} Exception={}".format(cs, config, e))
cls.set_hyperparameters(config)
with self.assertRaisesRegex(
ValueError,
"Make sure fit is called"
):
cls.fit(
X=np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]),
y=np.array([1, 0, 1, 1])
)
del preprocessing_components._addons.components['CrashPreprocessor']
def test_add_preprocessor(self):
self.assertEqual(len(preprocessing_components._addons.components), 0)
preprocessing_components.add_preprocessor(DummyPreprocessor)
self.assertEqual(len(preprocessing_components._addons.components), 1)
cs = SimpleClassificationPipeline().get_hyperparameter_search_space()
self.assertIn('DummyPreprocessor', str(cs))
del preprocessing_components._addons.components['DummyPreprocessor']
def test_add_preprocessor(self):
self.assertEqual(len(preprocessing_components._addons.components), 0)
preprocessing_components.add_preprocessor(DummyPreprocessor)
self.assertEqual(len(preprocessing_components._addons.components), 1)
cs = SimpleClassificationPipeline().get_hyperparameter_search_space()
self.assertIn('DummyPreprocessor', str(cs))
del preprocessing_components._addons.components['DummyPreprocessor']
def test_fit_instantiates_component(self):
"""Make sure that if a preprocessor is added, it's fit
method is called"""
preprocessing_components.add_preprocessor(CrashPreprocessor)
cls = SimpleClassificationPipeline()
cs = cls.get_hyperparameter_search_space()
self.assertIn('CrashPreprocessor', str(cs))
config = cs.sample_configuration()
config['feature_preprocessor:__choice__'] = 'CrashPreprocessor'
cls.set_hyperparameters(config)
with self.assertRaisesRegex(
ValueError,
"Make sure fit is called"
):
cls.fit(
X=np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]),
y=np.array([1, 0, 1, 1])
)
del preprocessing_components._addons.components['CrashPreprocessor']
