Merge pull request #965 from Trusted-AI/dev_1.6.0

Update to ART 1.6.0

Author: beat-buesser

.github/workflows/ci.yml

@@ -31,24 +31,18 @@ jobs:
             tensorflow: 1.15.5
             tf_version: v1
             keras: 2.2.5
-          - name: TensorFlow 2.2.2 (Keras 2.3.1 Python 3.7)
-            framework: tensorflow
-            python: 3.7
-            tensorflow: 2.2.2
-            tf_version: v2
-            keras: 2.3.1
-          - name: TensorFlow 2.2.2v1 (Keras 2.3.1 Python 3.7)
-            framework: tensorflow2v1
-            python: 3.7
-            tensorflow: 2.2.2
-            tf_version: v2
-            keras: 2.3.1
           - name: TensorFlow 2.3.2 (Keras 2.4.3 Python 3.7)
             framework: tensorflow
             python: 3.7
             tensorflow: 2.3.2
             tf_version: v2
             keras: 2.4.3
+          - name: TensorFlow 2.4.1v1 (Keras 2.4.3 Python 3.8)
+            framework: tensorflow2v1
+            python: 3.8
+            tensorflow: 2.4.1
+            tf_version: v2
+            keras: 2.4.3
           - name: TensorFlow 2.4.1 (Keras 2.4.3 Python 3.8)
             framework: tensorflow
             python: 3.8
@@ -79,6 +73,13 @@ jobs:
           - name: mxnet (Python 3.7)
             framework: mxnet
             python: 3.7
+          - name: TensorFlow+Lingvo 2.1.0v1 (Keras 2.3.1 Python 3.6)
+            framework: tensorflow2v1
+            python: 3.6
+            tensorflow: 2.1.0
+            tf_version: v2
+            keras: 2.3.1
+            lingvo: 0.6.4
           - name: legacy (TensorFlow 2.2.1 Keras 2.3.1 scikit-learn 0.22.2 Python 3.7)
             framework: legacy
             python: 3.7
@@ -115,7 +116,7 @@ jobs:
           pip install scikit-learn==${{ matrix.scikit-learn }}
           pip list
       - name: Pre-install tensorflow
-        if: ${{ matrix.framework == 'tensorflow' || matrix.framework == 'keras' || matrix.framework == 'kerastf' }}
+        if: ${{ matrix.framework == 'tensorflow' || matrix.framework == 'keras' || matrix.framework == 'kerastf' || matrix.framework == 'tensorflow2v1' }}
         run: |
           pip install tensorflow==${{ matrix.tensorflow }}
           pip install keras==${{ matrix.keras }}
@@ -125,6 +126,14 @@ jobs:
         run: |
           pip install scikit-learn==${{ matrix.scikit-learn }}
           pip list
+      - name: Pre-install Lingvo ASR
+        if: ${{ matrix.tensorflow == '2.1.0' }}
+        run: |
+          pip install tensorflow==${{ matrix.tensorflow }}
+          pip install lingvo==${{ matrix.lingvo }}
+          pip install tensorflow-addons==0.9.1
+          pip install model-pruning-google-research==0.0.3
+          pip list
       - name: Run ${{ matrix.name }} Tests
         run: ./run_tests.sh ${{ matrix.framework }}
       - name: Upload coverage to Codecov

AUTHORS

@@ -9,3 +9,4 @@
 - Kyushu University
 - Intel Corporation
 - University of Chicago
+- The MITRE Corporation

art/__init__.py

@@ -11,7 +11,7 @@
 from art import wrappers
 
 # Semantic Version
-__version__ = "1.5.3"
+__version__ = "1.6.0-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_patch.adversarial_patch_pytorch import AdversarialPatchPyTorch
 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

art/attacks/evasion/adversarial_patch/adversarial_patch.py

@@ -32,7 +32,6 @@
 from art.attacks.evasion.adversarial_patch.adversarial_patch_tensorflow import AdversarialPatchTensorFlowV2
 from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin
 from art.estimators.classification.classifier import ClassifierMixin
-
 from art.estimators.classification import TensorFlowV2Classifier
 from art.attacks.attack import EvasionAttack
 
@@ -169,6 +168,19 @@ def reset_patch(self, initial_patch_value: Optional[Union[float, np.ndarray]]) -
         """
         self._attack.reset_patch(initial_patch_value=initial_patch_value)
 
+    def insert_transformed_patch(self, x: np.ndarray, patch: np.ndarray, image_coords: np.ndarray):
+        """
+        Insert patch to image based on given or selected coordinates.
+
+        :param x: The image to insert the patch.
+        :param patch: The patch to be transformed and inserted.
+        :param image_coords: The coordinates of the 4 corners of the transformed, inserted patch of shape
+            [[x1, y1], [x2, y2], [x3, y3], [x4, y4]] in pixel units going in clockwise direction, starting with upper
+            left corner.
+        :return: The input `x` with the patch inserted.
+        """
+        return self._attack.insert_transformed_patch(x, patch, image_coords)
+
     def set_params(self, **kwargs) -> None:
         super().set_params(**kwargs)
         self._attack.set_params(**kwargs)

art/attacks/evasion/adversarial_patch/adversarial_patch_numpy.py

@@ -33,6 +33,7 @@
 from tqdm.auto import trange
 
 from art.attacks.attack import EvasionAttack
+from art.attacks.evasion.adversarial_patch.utils import insert_transformed_patch
 from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin
 from art.estimators.classification.classifier import ClassifierMixin
 from art.utils import check_and_transform_label_format
@@ -578,3 +579,17 @@ def reset_patch(self, initial_patch_value: Optional[Union[float, np.ndarray]]) -
             self.patch = initial_patch_value
         else:
             raise ValueError("Unexpected value for initial_patch_value.")
+
+    @staticmethod
+    def insert_transformed_patch(x: np.ndarray, patch: np.ndarray, image_coords: np.ndarray):
+        """
+        Insert patch to image based on given or selected coordinates.
+
+        :param x: The image to insert the patch.
+        :param patch: The patch to be transformed and inserted.
+        :param image_coords: The coordinates of the 4 corners of the transformed, inserted patch of shape
+            [[x1, y1], [x2, y2], [x3, y3], [x4, y4]] in pixel units going in clockwise direction, starting with upper
+            left corner.
+        :return: The input `x` with the patch inserted.
+        """
+        return insert_transformed_patch(x, patch, image_coords)