def test_file_output(self):
shutil.rmtree(self.working_directory, ignore_errors=True)
os.mkdir(self.working_directory)
queue_mock = unittest.mock.Mock()
context = BackendContext(
temporary_directory=os.path.join(self.working_directory, 'tmp'),
output_directory=os.path.join(self.working_directory, 'out'),
delete_tmp_folder_after_terminate=True,
delete_output_folder_after_terminate=True,
)
with unittest.mock.patch.object(
Backend, 'load_datamanager') as load_datamanager_mock:
load_datamanager_mock.return_value = get_multiclass_classification_datamanager(
)
backend = Backend(context)
ae = AbstractEvaluator(
backend=backend,
output_y_hat_optimization=False,
queue=queue_mock,
metric=accuracy,
port=self.port,
)
ae.model = sklearn.dummy.DummyClassifier()
rs = np.random.RandomState()
ae.Y_optimization = rs.rand(33, 3)
predictions_ensemble = rs.rand(33, 3)
predictions_test = rs.rand(25, 3)
predictions_valid = rs.rand(25, 3)
ae.file_output(
Y_optimization_pred=predictions_ensemble,
Y_valid_pred=predictions_valid,
Y_test_pred=predictions_test,
)
self.assertTrue(
os.path.exists(
os.path.join(self.working_directory, 'tmp',
'.auto-sklearn', 'runs', '1_0_None')))
shutil.rmtree(self.working_directory, ignore_errors=True)
def test_add_additional_components(self):
shutil.rmtree(self.working_directory, ignore_errors=True)
os.mkdir(self.working_directory)
queue_mock = unittest.mock.Mock()
context = BackendContext(
temporary_directory=os.path.join(self.working_directory, 'tmp'),
delete_tmp_folder_after_terminate=True,
)
with unittest.mock.patch.object(
Backend, 'load_datamanager') as load_datamanager_mock:
load_datamanager_mock.return_value = get_multiclass_classification_datamanager(
)
backend = Backend(context)
with unittest.mock.patch.object(_addons['classification'],
'add_component') as _:
# If the components in the argument `additional_components` are an empty dict
# there is no call to `add_component`, if there's something in it, `add_component
# is called (2nd case)
for fixture, case in ((0, dict()), (1, dict(abc='def'))):
thirdparty_components_patch = unittest.mock.Mock()
thirdparty_components_patch.components = case
additional_components = dict(
classification=thirdparty_components_patch)
AbstractEvaluator(
backend=backend,
output_y_hat_optimization=False,
queue=queue_mock,
metric=accuracy,
port=self.port,
additional_components=additional_components,
)
self.assertEqual(
_addons['classification'].add_component.call_count,
fixture)