Merge pull request #2296 from Trusted-AI/dev_1.16.0

Update to ART 1.16.0

.github/actions/yolo/run.sh

@@ -3,6 +3,9 @@
 exit_code=0
 
 pytest --cov-report=xml --cov=art --cov-append -q -vv tests/estimators/object_detection/test_pytorch_yolo.py --framework=pytorch --durations=0
-if [[ $? -ne 0 ]]; then exit_code=1; echo "Failed estimators/speech_recognition/test_pytorch_yolo tests"; fi
+if [[ $? -ne 0 ]]; then exit_code=1; echo "Failed estimators/object_detection/test_pytorch_yolo tests"; fi
+
+pytest --cov-report=xml --cov=art --cov-append -q -vv tests/estimators/object_detection/test_object_seeker_yolo.py --framework=pytorch --durations=0
+if [[ $? -ne 0 ]]; then exit_code=1; echo "Failed estimators/object_detection/test_object_seeker_yolo tests"; fi
 
 exit ${exit_code}

.github/workflows/ci-huggingface.yml

@@ -0,0 +1,65 @@
+name: CI Huggingface
+on:
+  # Run on manual trigger
+  workflow_dispatch:
+
+  # Run on pull requests
+  pull_request:
+    paths-ignore:
+      - '*.md'
+
+  # Run on merge queue
+  merge_group:
+
+  # Run when pushing to main or dev branches
+  push:
+    branches:
+      - main
+      - dev*
+
+  # Run scheduled CI flow daily
+  schedule:
+    - cron: '0 8 * * 0'
+
+jobs:
+  test:
+    runs-on: ubuntu-20.04
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - name: Huggingface 4.30
+            framework: huggingface
+            python: 3.9
+            torch: 1.13.1+cpu
+            torchvision: 0.14.1+cpu
+            torchaudio: 0.13.1
+            transformers: 4.30.2
+
+    name: ${{ matrix.name }}
+    steps:
+      - name: Checkout Repo
+        uses: actions/checkout@v3
+      - name: Setup Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python }}
+      - name: Install Dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get -y -q install ffmpeg libavcodec-extra
+          python -m pip install --upgrade pip setuptools wheel
+          pip3 install -r requirements_test.txt
+          pip install tensorflow==2.10.1
+          pip install keras==2.10.0
+          pip install torch==${{ matrix.torch }} -f https://download.pytorch.org/whl/cpu/torch_stable.html
+          pip install torchvision==${{ matrix.torchvision }} -f https://download.pytorch.org/whl/cpu/torch_stable.html
+          pip install torchaudio==${{ matrix.torchaudio }} -f https://download.pytorch.org/whl/cpu/torch_stable.html
+          pip install transformers==${{ matrix.transformers }}
+          pip list
+      - name: Run Tests
+        run: ./run_tests.sh ${{ matrix.framework }}
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v3
+        with:
+          fail_ci_if_error: true

.github/workflows/ci-lingvo.yml

@@ -50,7 +50,7 @@ jobs:
           sudo apt-get update
           sudo apt-get -y -q install ffmpeg libavcodec-extra
           python -m pip install --upgrade pip setuptools wheel
-          pip install -q -r <(sed '/^scipy/d;/^matplotlib/d;/^pandas/d;/^statsmodels/d;/^numba/d;/^jax/d;/^h5py/d;/^Pillow/d;/^pytest/d;/^pytest-mock/d;/^torch/d;/^torchaudio/d;/^torchvision/d;/^xgboost/d;/^requests/d;/^tensorflow/d;/^keras/d;/^kornia/d;/^librosa/d;/^tqdm/d' requirements_test.txt)
+          pip install -q -r <(sed '/^scipy/d;/^matplotlib/d;/^pandas/d;/^statsmodels/d;/^numba/d;/^jax/d;/^h5py/d;/^Pillow/d;/^pytest/d;/^pytest-mock/d;/^torch/d;/^torchaudio/d;/^torchvision/d;/^xgboost/d;/^requests/d;/^tensorflow/d;/^keras/d;/^kornia/d;/^librosa/d;/^tqdm/d;/^timm/d' requirements_test.txt)
           pip install scipy==1.5.4
           pip install matplotlib==3.3.4
           pip install pandas==1.1.5

.github/workflows/ci-pytorch-object-detectors.yml

@@ -52,6 +52,8 @@ jobs:
         run: pytest --cov-report=xml --cov=art --cov-append -q -vv tests/estimators/object_detection/test_pytorch_faster_rcnn.py --framework=pytorch --durations=0
       - name: Run Test Action - test_pytorch_detection_transformer
         run: pytest --cov-report=xml --cov=art --cov-append -q -vv tests/estimators/object_detection/test_pytorch_detection_transformer.py --framework=pytorch --durations=0
+      - name: Run Test Action - test_pytorch_object_seeker_faster_rcnn
+        run: pytest --cov-report=xml --cov=art --cov-append -q -vv tests/estimators/object_detection/test_object_seeker_faster_rcnn.py --framework=pytorch --durations=0
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v3
         with:

art/attacks/attack.py

@@ -159,6 +159,8 @@ def set_params(self, **kwargs) -> None:
         for key, value in kwargs.items():
             if key in self.attack_params:
                 setattr(self, key, value)
+            else:
+                raise ValueError(f'The attribute "{key}" cannot be set for this attack.')
         self._check_params()
 
     def _check_params(self) -> None:
@@ -186,6 +188,19 @@ def is_estimator_valid(estimator, estimator_requirements) -> bool:
                 return False
         return True
 
+    def __repr__(self):
+        """
+        Returns a string describing the attack class and attack_params
+        """
+        param_str = ""
+        for param in self.attack_params:
+            if hasattr(self, param):
+                param_str += f"{param}={getattr(self, param)}, "
+            elif hasattr(self, "_attack"):
+                if hasattr(self._attack, param):
+                    param_str += f"{param}={getattr(self._attack, param)}, "
+        return f"{type(self).__name__}({param_str})"
+
 
 class EvasionAttack(Attack):
     """

art/attacks/evasion/adversarial_patch/adversarial_patch_tensorflow.py

@@ -274,10 +274,10 @@ def _random_overlay(
             name=None,
         )
 
-        pad_h_before = int((self.image_shape[self.i_h] - image_mask.shape[self.i_h_patch + 1]) / 2)
+        pad_h_before = int((self.image_shape[self.i_h] - image_mask.shape.as_list()[self.i_h_patch + 1]) / 2)
         pad_h_after = int(self.image_shape[self.i_h] - pad_h_before - image_mask.shape[self.i_h_patch + 1])
 
-        pad_w_before = int((self.image_shape[self.i_w] - image_mask.shape[self.i_w_patch + 1]) / 2)
+        pad_w_before = int((self.image_shape[self.i_w] - image_mask.shape.as_list()[self.i_w_patch + 1]) / 2)
         pad_w_after = int(self.image_shape[self.i_w] - pad_w_before - image_mask.shape[self.i_w_patch + 1])
 
         image_mask = tf.pad(  # pylint: disable=E1123
@@ -323,10 +323,10 @@ def _random_overlay(
 
             if mask is None:
                 padding_after_scaling_h = (
-                    self.image_shape[self.i_h] - im_scale * padded_patch.shape[self.i_h + 1]
+                    self.image_shape[self.i_h] - im_scale * padded_patch.shape.as_list()[self.i_h + 1]
                 ) / 2.0
                 padding_after_scaling_w = (
-                    self.image_shape[self.i_w] - im_scale * padded_patch.shape[self.i_w + 1]
+                    self.image_shape[self.i_w] - im_scale * padded_patch.shape.as_list()[self.i_w + 1]
                 ) / 2.0
                 x_shift = np.random.uniform(-padding_after_scaling_w, padding_after_scaling_w)
                 y_shift = np.random.uniform(-padding_after_scaling_h, padding_after_scaling_h)