def setUpClass(cls):
np.random.seed(seed=1234)
cls.sklearn_model = DecisionTreeClassifier()
cls.classifier = ScikitlearnDecisionTreeClassifier(
model=cls.sklearn_model)
cls.classifier.fit(x=x_train, y=y_train)
def setUpClass(cls):
master_seed(seed=1234)
super().setUpClass()
cls.sklearn_model = DecisionTreeClassifier()
cls.classifier = ScikitlearnDecisionTreeClassifier(model=cls.sklearn_model)
cls.classifier.fit(x=cls.x_train_iris, y=cls.y_train_iris)
def setUpClass(cls):
np.random.seed(seed=1234)
sklearn_model = DecisionTreeClassifier()
cls.classifier = ScikitlearnDecisionTreeClassifier(model=sklearn_model)
assert (type(cls.classifier) == type(
SklearnClassifier(model=sklearn_model)))
cls.classifier.fit(x=x_train, y=y_train)
def test_classifier_type_check_fail_gradients(self):
# Use a test classifier not providing gradients required by white-box attack
classifier = ScikitlearnDecisionTreeClassifier(model=DecisionTreeClassifier())
with self.assertRaises(TypeError) as context:
_ = AdversarialPatch(classifier=classifier)
self.assertIn('For `AdversarialPatch` classifier must be an instance of '
'`art.classifiers.classifier.ClassifierNeuralNetwork` and '
'`art.classifiers.classifier.ClassifierGradients`, the provided classifier is instance of '
'(<class \'art.classifiers.scikitlearn.ScikitlearnClassifier\'>,).', str(context.exception))
def test_classifier_type_check_fail_gradients(self):
# Use a test classifier not providing gradients required by white-box attack
from art.classifiers.scikitlearn import ScikitlearnDecisionTreeClassifier
from sklearn.tree import DecisionTreeClassifier
classifier = ScikitlearnDecisionTreeClassifier(model=DecisionTreeClassifier())
with self.assertRaises(TypeError) as context:
_ = ElasticNet(classifier=classifier)
self.assertIn('For `ElasticNet` classifier must be an instance of '
'`art.classifiers.classifier.ClassifierGradients`, the provided classifier is instance of '
'(<class \'art.classifiers.scikitlearn.ScikitlearnClassifier\'>,).', str(context.exception))
def backend_test_classifier_type_check_fail(attack, classifier_expected_list=[], classifier=None):
# Use a useless test classifier to test basic classifier properties
class ClassifierNoAPI:
pass
noAPIClassifier = ClassifierNoAPI
_backend_test_classifier_list_type_check_fail(attack, noAPIClassifier, [Classifier])
if len(classifier_expected_list) > 0:
# Testing additional types of classifiers expected
if classifier is None:
if ClassifierGradients in classifier_expected_list or ClassifierNeuralNetwork in classifier_expected_list:
# Use a test classifier not providing gradients required by white-box attack
classifier = ScikitlearnDecisionTreeClassifier(model=DecisionTreeClassifier())
else:
raise Exception(
"a test classifier must be provided if classifiers other than "
"ClassifierGradients and ClassifierNeuralNetwork are expected"
)
_backend_test_classifier_list_type_check_fail(attack, classifier, classifier_expected_list)