Merge pull request #906 from Trusted-AI/dev_1.5.2

Update to ART 1.5.2

Author: beat-buesser

.github/workflows/ci.yml

@@ -25,45 +25,45 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - name: TensorFlow 1.15.4 (Keras 2.2.5 Python 3.7)
+          - name: TensorFlow 1.15.5 (Keras 2.2.5 Python 3.7)
             framework: tensorflow
             python: 3.7
-            tensorflow: 1.15.4
+            tensorflow: 1.15.5
             tf_version: v1
             keras: 2.2.5
-          - name: TensorFlow 2.2.0 (Keras 2.3.1 Python 3.7)
+          - name: TensorFlow 2.2.2 (Keras 2.3.1 Python 3.7)
             framework: tensorflow
             python: 3.7
-            tensorflow: 2.2.0
+            tensorflow: 2.2.2
             tf_version: v2
             keras: 2.3.1
-          - name: TensorFlow 2.2.0v1 (Keras 2.3.1 Python 3.7)
+          - name: TensorFlow 2.2.2v1 (Keras 2.3.1 Python 3.7)
             framework: tensorflow2v1
             python: 3.7
-            tensorflow: 2.2.0
+            tensorflow: 2.2.2
             tf_version: v2
             keras: 2.3.1
-          - name: TensorFlow 2.3.1 (Keras 2.4.3 Python 3.7)
+          - name: TensorFlow 2.3.2 (Keras 2.4.3 Python 3.7)
             framework: tensorflow
             python: 3.7
-            tensorflow: 2.3.1
+            tensorflow: 2.3.2
             tf_version: v2
             keras: 2.4.3
-          - name: TensorFlow 2.4.0rc3 (Keras 2.4.3 Python 3.8)
+          - name: TensorFlow 2.4.1 (Keras 2.4.3 Python 3.8)
             framework: tensorflow
             python: 3.8
-            tensorflow: 2.4.0rc3
+            tensorflow: 2.4.1
             tf_version: v2
             keras: 2.4.3
           - name: Keras 2.3.1 (TensorFlow 2.2.1 Python 3.7)
             framework: keras
             python: 3.7
             tensorflow: 2.2.1
             keras: 2.3.1
-          - name: TensorFlow-Keras 2.3.1 (Keras 2.4.3 Python 3.7)
+          - name: TensorFlow-Keras 2.3.2 (Keras 2.4.3 Python 3.7)
             framework: kerastf
             python: 3.7
-            tensorflow: 2.3.1
+            tensorflow: 2.3.2
             keras: 2.4.3
           - name: PyTorch (Python 3.7)
             framework: pytorch
@@ -85,10 +85,10 @@ jobs:
             tensorflow: 2.2.1
             keras: 2.3.1
             scikit-learn: 0.22.2
-          - name: legacy (TensorFlow 2.3.1 Keras 2.4.3 scikit-learn 0.23.2 Python 3.8)
+          - name: legacy (TensorFlow 2.3.2 Keras 2.4.3 scikit-learn 0.23.2 Python 3.8)
             framework: legacy
             python: 3.8
-            tensorflow: 2.3.1
+            tensorflow: 2.3.2
             keras: 2.4.3
             scikit-learn: 0.23.2
 
@@ -143,7 +143,7 @@ jobs:
         run: |
           sudo apt-get update
           sudo apt-get -y -q install ffmpeg libavcodec-extra
-          pip install tensorflow==2.2.0
+          pip install tensorflow==2.2.2
           pip install keras==2.3.1
       - name: Install Dependencies
         run: |

art/__init__.py

@@ -11,7 +11,7 @@
 from art import wrappers
 
 # Semantic Version
-__version__ = "1.5.1"
+__version__ = "1.5.2-dev"
 
 # pylint: disable=C0103
 

art/attacks/evasion/__init__.py

@@ -4,6 +4,7 @@
 from art.attacks.evasion.adversarial_patch.adversarial_patch import AdversarialPatch
 from art.attacks.evasion.adversarial_patch.adversarial_patch_numpy import AdversarialPatchNumpy
 from art.attacks.evasion.adversarial_patch.adversarial_patch_tensorflow import AdversarialPatchTensorFlowV2
+from art.attacks.evasion.adversarial_asr import CarliniWagnerASR
 from art.attacks.evasion.auto_attack import AutoAttack
 from art.attacks.evasion.auto_projected_gradient_descent import AutoProjectedGradientDescent
 from art.attacks.evasion.brendel_bethge import BrendelBethgeAttack

art/attacks/evasion/adversarial_patch/adversarial_patch.py

@@ -127,10 +127,14 @@ def generate(self, x: np.ndarray, y: Optional[np.ndarray] = None, **kwargs) -> T
 
         :param x: An array with the original input images of shape NHWC or NCHW or input videos of shape NFHWC or NFCHW.
         :param y: An array with the original true labels.
-        :param mask: An boolean array of shape equal to the shape of a single samples (1, H, W) or the shape of `x`
+        :param mask: A boolean array of shape equal to the shape of a single samples (1, H, W) or the shape of `x`
                      (N, H, W) without their channel dimensions. Any features for which the mask is True can be the
                      center location of the patch during sampling.
         :type mask: `np.ndarray`
+        :param reset_patch: If `True` reset patch to initial values of mean of minimal and maximal clip value, else if
+                            `False` (default) restart from previous patch values created by previous call to `generate`
+                            or mean of minimal and maximal clip value if first call to `generate`.
+        :type reset_patch: bool
         :return: An array with adversarial patch and an array of the patch mask.
         """
         logger.info("Creating adversarial patch.")
@@ -157,6 +161,14 @@ def apply_patch(self, x: np.ndarray, scale: float, patch_external: Optional[np.n
         """
         return self._attack.apply_patch(x, scale, patch_external=patch_external)
 
+    def reset_patch(self, initial_patch_value: Optional[Union[float, np.ndarray]]) -> None:
+        """
+        Reset the adversarial patch.
+
+        :param initial_patch_value: Patch value to use for resetting the patch.
+        """
+        self._attack.reset_patch(initial_patch_value=initial_patch_value)
+
     def set_params(self, **kwargs) -> None:
         super().set_params(**kwargs)
         self._attack.set_params(**kwargs)