Fix dependencies

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

Author: beat-buesser

tests/attacks/evasion/test_overload_attack.py

@@ -35,7 +35,20 @@ def test_generate(art_warning):
         from ultralytics import YOLO
 
         torch.serialization.add_safe_globals([torch.nn.modules.container.Sequential])
+        torch.serialization.add_safe_globals([torch.nn.modules.container.ModuleList])
+        torch.serialization.add_safe_globals([torch.nn.modules.pooling.MaxPool2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.batchnorm.BatchNorm2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.activation.SiLU])
+        torch.serialization.add_safe_globals([torch.nn.modules.conv.Conv2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.upsampling.Upsample])
         torch.serialization.add_safe_globals([ultralytics.nn.tasks.DetectionModel])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.SPPF])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.C3])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.Bottleneck])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.Detect])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.Conv])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.Concat])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.DFL])
 
         model = YOLO("yolov5su.pt")
         py_model = PyTorchYolo(model=model, input_shape=(3, 640, 640), channels_first=True)
@@ -73,9 +86,23 @@ def test_check_params(art_warning):
         from ultralytics import YOLO
 
         torch.serialization.add_safe_globals([torch.nn.modules.container.Sequential])
+        torch.serialization.add_safe_globals([torch.nn.modules.container.ModuleList])
+        torch.serialization.add_safe_globals([torch.nn.modules.pooling.MaxPool2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.batchnorm.BatchNorm2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.activation.SiLU])
+        torch.serialization.add_safe_globals([torch.nn.modules.conv.Conv2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.upsampling.Upsample])
         torch.serialization.add_safe_globals([ultralytics.nn.tasks.DetectionModel])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.SPPF])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.C3])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.Bottleneck])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.Detect])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.Conv])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.Concat])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.DFL])
 
         model = YOLO("yolov5su.pt")
+        print(model)
         py_model = PyTorchYolo(model=model, input_shape=(3, 640, 640), channels_first=True)
 
         with pytest.raises(ValueError):

tests/attacks/evasion/test_steal_now_attack_later.py

@@ -38,7 +38,20 @@ def test_generate(art_warning):
         from ultralytics import YOLO
 
         torch.serialization.add_safe_globals([torch.nn.modules.container.Sequential])
+        torch.serialization.add_safe_globals([torch.nn.modules.container.ModuleList])
+        torch.serialization.add_safe_globals([torch.nn.modules.pooling.MaxPool2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.batchnorm.BatchNorm2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.activation.SiLU])
+        torch.serialization.add_safe_globals([torch.nn.modules.conv.Conv2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.upsampling.Upsample])
         torch.serialization.add_safe_globals([ultralytics.nn.tasks.DetectionModel])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.SPPF])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.C3])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.Bottleneck])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.Detect])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.Conv])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.Concat])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.DFL])
 
         model = YOLO("yolov8m")
         py_model = PyTorchYolo(model=model, input_shape=(3, 640, 640), channels_first=True, is_yolov8=True)
@@ -205,9 +218,24 @@ def test_check_params(art_warning):
         from ultralytics import YOLO
 
         torch.serialization.add_safe_globals([torch.nn.modules.container.Sequential])
+        torch.serialization.add_safe_globals([torch.nn.modules.container.ModuleList])
+        torch.serialization.add_safe_globals([torch.nn.modules.pooling.MaxPool2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.batchnorm.BatchNorm2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.activation.SiLU])
+        torch.serialization.add_safe_globals([torch.nn.modules.conv.Conv2d])
+        torch.serialization.add_safe_globals([torch.nn.modules.upsampling.Upsample])
         torch.serialization.add_safe_globals([ultralytics.nn.tasks.DetectionModel])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.SPPF])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.C3])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.Bottleneck])
+        torch.serialization.add_safe_globals([ultralytics.nn.tasks.Detect])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.Conv])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.Concat])
+        torch.serialization.add_safe_globals([ultralytics.nn.modules.DFL])
 
         model = YOLO("yolov8m")
+        print(model)
+        sdf
         py_model = PyTorchYolo(model=model, input_shape=(3, 640, 640), channels_first=True, is_yolov8=True)
 
         def dummy_func(model, imags):