Update scikit-learn unit test models for scikit-learn>=1.3.0

Signed-off-by: Beat Buesser <[email protected]>

Author: beat-buesser

tests/utils.py

@@ -28,6 +28,7 @@
 import unittest
 import warnings
 
+import sklearn
 import numpy as np
 
 from art.estimators.classification.tensorflow import TensorFlowV2Classifier
@@ -1746,6 +1747,13 @@ def get_tabular_classifier_scikit_list(clipped=False, model_list_names=None):
         ScikitlearnSVC,
     )
 
+    sklearn_version = list(map(int, sklearn.__version__.split(".")))
+    sklearn_ge_1_3_0 = sklearn_version[0] == 1 and sklearn_version[1] >= 3
+    if sklearn_ge_1_3_0:
+        suffix = "-ge-1.3.0"
+    else:
+        suffix = ""
+
     available_models = {
         "decisionTreeClassifier": ScikitlearnDecisionTreeClassifier,
         # "extraTreeClassifier": ScikitlearnExtraTreeClassifier,
@@ -1775,7 +1783,7 @@ def get_tabular_classifier_scikit_list(clipped=False, model_list_names=None):
                     os.path.join(
                         os.path.dirname(os.path.dirname(__file__)),
                         "utils/resources/models/scikit/",
-                        "scikit-" + model_name + "-iris-clipped.pickle",
+                        "scikit-" + model_name + "-iris-clipped" + suffix + ".pickle",
                     ),
                     "rb",
                 )
@@ -1788,7 +1796,7 @@ def get_tabular_classifier_scikit_list(clipped=False, model_list_names=None):
                     os.path.join(
                         os.path.dirname(os.path.dirname(__file__)),
                         "utils/resources/models/scikit/",
-                        "scikit-" + model_name + "-iris-unclipped.pickle",
+                        "scikit-" + model_name + "-iris-unclipped" + suffix + ".pickle",
                     ),
                     "rb",
                 )

utils/resources/create_model_weights.py

@@ -15,13 +15,14 @@
 # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
 # TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 # SOFTWARE.
-import tensorflow as tf
 import os
 import pickle
+
+import tensorflow as tf
 from tensorflow.keras.models import Sequential
 from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D
+import sklearn
 from sklearn.linear_model import LogisticRegression
-from art.estimators.classification import SklearnClassifier
 from sklearn.svm import SVC, LinearSVC
 from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier
 from sklearn.ensemble import AdaBoostClassifier, BaggingClassifier, ExtraTreesClassifier
@@ -140,42 +141,47 @@ def create_scikit_model_weights():
     }
 
     clipped_models = {
-        model_name: SklearnClassifier(model=model, clip_values=(0, 1)) for model_name, model in model_list.items()
+        model_name: model for model_name, model in model_list.items()
     }
-    unclipped_models = {model_name: SklearnClassifier(model=model) for model_name, model in model_list.items()}
+    unclipped_models = {model_name: model for model_name, model in model_list.items()}
 
     (x_train_iris, y_train_iris), (_, _), _, _ = load_dataset("iris")
 
+    y_train_iris = np.argmax(y_train_iris, axis=1)
+
+    print(sklearn.__version__)
+    dfg
+
     for model_name, model in clipped_models.items():
-        model.fit(x=x_train_iris, y=y_train_iris)
+        model.fit(X=x_train_iris, y=y_train_iris)
         pickle.dump(
             model,
             open(
                 os.path.join(
                     os.path.dirname(os.path.dirname(__file__)),
-                    "utils/resources/models/scikit/",
-                    model_name + "iris_clipped.sav",
+                    "resources/models/scikit/",
+                    "scikit-" + model_name + "-iris-clipped-ge-1.3.0.pickle",
                 ),
                 "wb",
             ),
         )
 
     for model_name, model in unclipped_models.items():
-        model.fit(x=x_train_iris, y=y_train_iris)
+        model.fit(X=x_train_iris, y=y_train_iris)
         pickle.dump(
             model,
             open(
                 os.path.join(
                     os.path.dirname(os.path.dirname(__file__)),
-                    "utils/resources/models/scikit/",
-                    model_name + "iris_unclipped.sav",
+                    "resources/models/scikit/",
+                    "scikit-" + model_name + "-iris-unclipped-ge-1.3.0.pickle",
                 ),
                 "wb",
             ),
         )
 
 
 if __name__ == "__main__":
-    main_mnist_binary()
+    # main_mnist_binary()
     create_scikit_model_weights()
-    main_diabetes()
+    # main_diabetes()