Merge branch 'dev_1.6.1' into development_issue_1047

Author: beat-buesser

.github/actions/deepspeech-v2/action.yml

@@ -1,5 +1,5 @@
-name: 'Test deepspeech version 2'
-description: 'Run tests on deepspeech version 2'
+name: 'Test DeepSpeech v2'
+description: 'Run tests for DeepSpeech v2'
 runs:
   using: 'composite'
   steps:

.github/workflows/ci-deepspeech-v2.yml

@@ -1,4 +1,4 @@
-name: Continuous Integration Deepspeech v2
+name: CI PyTorchDeepSpeech v2
 on:
   # Run on manual trigger
   workflow_dispatch:
@@ -20,7 +20,7 @@ on:
 
 jobs:
   test_deepspeech_v2:
-    name: A job to test deepspeech version 2
+    name: PyTorchDeepSpeech v2
     runs-on: ubuntu-latest
     container: minhitbk/art_testing_envs:deepspeech_v2
     steps:

.github/workflows/ci-lingvo.yml

@@ -1,4 +1,4 @@
-name: Continuous Integration
+name: CI Lingvo
 on:
   # Run on manual trigger
   workflow_dispatch:

.github/workflows/ci-mxnet.yml

@@ -1,4 +1,4 @@
-name: Continuous Integration
+name: CI MXNet
 on:
   # Run on manual trigger
   workflow_dispatch:

.github/workflows/ci-pytorch-fasterrcnn.yml

@@ -0,0 +1,49 @@
+name: CI PyTorchFasterRCNN
+on:
+  # Run on manual trigger
+  workflow_dispatch:
+
+  # Run on pull requests
+  pull_request:
+    paths-ignore:
+      - '*.md'
+
+  # Run when pushing to main or dev branches
+  push:
+    branches:
+      - main
+      - dev*
+
+  # Run scheduled CI flow daily
+  schedule:
+    - cron: '0 8 * * 0'
+
+jobs:
+  test_pytorch_fasterrcnn:
+    name: PyTorchFasterRCNN
+    runs-on: ubuntu-20.04
+    strategy:
+      fail-fast: false
+    steps:
+      - name: Checkout Repo
+        uses: actions/checkout@v2
+      - name: Setup Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.7
+      - 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 -q -r requirements.txt
+          pip list
+      - name: Pre-install torch
+        run: |
+          pip install torch==1.6.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
+          pip install torchvision==0.7.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
+          pip install torchaudio==0.6.0 -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Run Test Action
+        run: pytest --cov-report=xml --cov=art --cov-append -q -vv tests/estimators/object_detection/test_pytorch_faster_rcnn.py --framework=pytorch --skip_travis=True --durations=0
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v1

.github/workflows/ci.yml

@@ -1,4 +1,4 @@
-name: Continuous Integration
+name: CI General
 on:
   # Run on manual trigger
   workflow_dispatch:
@@ -78,7 +78,7 @@ jobs:
             scikit-learn: 0.24.1
             python: 3.8
 
-    name: Run ${{ matrix.name }} Tests
+    name: ${{ matrix.name }}
     steps:
       - name: Checkout Repo
         uses: actions/checkout@v2
@@ -130,7 +130,7 @@ jobs:
           pip install tensorflow-addons==0.9.1
           pip install model-pruning-google-research==0.0.3
           pip list
-      - name: Run ${{ matrix.name }} Tests
+      - name: Run Tests
         run: ./run_tests.sh ${{ matrix.framework }}
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v1

art/attacks/poisoning/bullseye_polytope_attack.py

@@ -337,13 +337,10 @@ def loss_from_center(
                     )
             elif net_repeat == 1:
                 if isinstance(feature_layer, list):
-                    poisons_feats = torch.cat(
-                        [
-                            torch.flatten(net.get_activations(poison_batch(), layer=layer, framework=True), 0)
-                            for layer in feature_layer
-                        ],
-                        0,
-                    )
+                    poisons_feats = [
+                        torch.flatten(net.get_activations(poison_batch(), layer=layer, framework=True), 0)
+                        for layer in feature_layer
+                    ]
                 else:
                     poisons_feats = net.get_activations(poison_batch(), layer=feature_layer, framework=True)
             else:

art/estimators/classification/xgboost.py

@@ -160,7 +160,7 @@ def _get_nb_classes(self, nb_classes: Optional[int]) -> int:
 
         if isinstance(self._model, Booster):
             try:
-                return int(len(self._model.get_dump(dump_format="json")) / self._model.n_estimators)
+                return int(len(self._model.get_dump(dump_format="json")) / self._model.n_estimators)  # type: ignore
             except AttributeError:
                 if nb_classes is not None:
                     return nb_classes

notebooks/README.md

@@ -1,5 +1,11 @@
 # Adversarial Robustness Toolbox notebooks
 
+## Expectation over Transformation (EoT)
+
+[expectation_over_transformation_classification_rotation.ipynb](expectation_over_transformation_classification_rotation.ipynb) [[on nbviewer](https://nbviewer.jupyter.org/github/Trusted-AI/adversarial-robustness-toolbox/blob/main/notebooks/expectation_over_transformation_classification_rotation.ipynb)]
+show how to use Expectation over Transformation (EoT) sampling to make adversarial examples robust against rotation for image classification.
+
+
 ## Video Action Recognition
 
 [adversarial_action_recognition.ipynb](adversarial_action_recognition.ipynb) [[on nbviewer](https://nbviewer.jupyter.org/github/Trusted-AI/adversarial-robustness-toolbox/blob/main/notebooks/adversarial_action_recognition.ipynb)]