Merge branch 'dev_1.17.0' into hf_model_wrapper_update

.github/workflows/ci-huggingface.yml

@@ -50,8 +50,8 @@ jobs:
           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 tensorflow==2.14.0
+          pip install keras==2.14.0
           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

.github/workflows/ci-keras.yml

@@ -28,30 +28,24 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - name: Keras 2.9.0 (TensorFlow 2.9.2 Python 3.9)
+          - name: Keras 2.13.1 (TensorFlow 2.13.1 Python 3.10)
             framework: keras
-            python: 3.9
-            tensorflow: 2.9.2
-            keras: 2.9.0
-            tf_addons: 0.17.0
-          - name: TensorFlow-Keras 2.9.2 (Keras 2.9.0 Python 3.9)
-            framework: kerastf
-            python: 3.9
-            tensorflow: 2.9.2
-            keras: 2.9.0
-            tf_addons: 0.17.0
-          - name: Keras 2.10.0 (TensorFlow 2.10.1 Python 3.9)
+            python: '3.10'
+            tensorflow: 2.13.1
+            keras: 2.13.1
+            tf_addons: 0.19.0
+          - name: Keras 2.14.0 (TensorFlow 2.14.0 Python 3.10)
             framework: keras
-            python: 3.9
-            tensorflow: 2.10.1
-            keras: 2.10.0
-            tf_addons: 0.18.0
-          - name: TensorFlow-Keras 2.10.1 (Keras 2.10.0 Python 3.9)
+            python: '3.10'
+            tensorflow: 2.14.0
+            keras: 2.14.0
+            tf_addons: 0.20.0
+          - name: TensorFlow-Keras 2.14.0 (Keras 2.14.0 Python 3.10)
             framework: kerastf
-            python: 3.9
-            tensorflow: 2.10.1
-            keras: 2.10.0
-            tf_addons: 0.18.0
+            python: '3.10'
+            tensorflow: 2.14.0
+            keras: 2.14.0
+            tf_addons: 0.20.0
 
     name: ${{ matrix.name }}
     steps:
@@ -66,7 +60,7 @@ jobs:
           sudo apt-get update
           sudo apt-get -y -q install ffmpeg libavcodec-extra
           python -m pip install --upgrade pip setuptools wheel
-          pip install -r requirements_test.txt
+          pip install -q -r <(sed '/^tensorflow/d;/^keras/d;/^tensorflow-addons/d' requirements_test.txt)
           pip install tensorflow==${{ matrix.tensorflow }}
           pip install keras==${{ matrix.keras }}
           pip install tensorflow-addons==${{ matrix.tf_addons }}

.github/workflows/ci-legacy.yml

@@ -29,11 +29,11 @@ jobs:
       matrix:
         module: [attacks_1, attacks_2, estimators, defences, metrics, art]
         include:
-          - name: legacy (TensorFlow 2.10.1 Keras 2.10.0 PyTorch 1.13.1 scikit-learn 1.1.3 Python 3.9)
+          - name: legacy (TensorFlow 2.14.0 Keras 2.14.0 PyTorch 1.13.1 scikit-learn 1.1.3 Python 3.9)
             framework: legacy
-            python: 3.9
-            tensorflow: 2.10.1
-            keras: 2.10.0
+            python: '3.10'
+            tensorflow: 2.14.0
+            keras: 2.14.0
             torch: 1.13.1+cpu
             torchvision: 0.14.1+cpu
             torchaudio: 0.13.1+cpu

.github/workflows/ci-lingvo.yml

@@ -76,7 +76,7 @@ jobs:
           pip install tqdm==4.64.1
           pip list
       - name: Run ${{ matrix.name }} Tests
-        run: ./run_tests.sh ${{ matrix.framework }}
+        run: pytest --cov-report=xml --cov=art --cov-append -q -vv tests/estimators/speech_recognition/test_tensorflow_lingvo.py --framework=${{ matrix.framework }} --durations=0
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v3
         with:

.github/workflows/ci-mxnet.yml

@@ -28,9 +28,9 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - name: mxnet (Python 3.8)
+          - name: mxnet (Python 3.9)
             framework: mxnet
-            python: 3.8
+            python: 3.9
 
     name: Run ${{ matrix.name }} Tests
     steps:
@@ -45,8 +45,6 @@ jobs:
           sudo apt-get update
           sudo apt-get -y -q install ffmpeg libavcodec-extra
           python -m pip install --upgrade pip setuptools wheel
-          pip install tensorflow==2.4.1
-          pip install keras==2.4.3
           pip3 install -q -r requirements_test.txt
           pip list
       - name: Run ${{ matrix.name }} ${{ matrix.module }} Tests

.github/workflows/ci-pytorch.yml

@@ -28,15 +28,9 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - name: PyTorch 1.11.0 (Python 3.9)
-            framework: pytorch
-            python: 3.8
-            torch: 1.11.0+cpu
-            torchvision: 0.12.0+cpu
-            torchaudio: 0.11.0
           - name: PyTorch 1.12.1 (Python 3.9)
             framework: pytorch
-            python: 3.8
+            python: 3.9
             torch: 1.12.1+cpu
             torchvision: 0.13.1+cpu
             torchaudio: 0.12.1
@@ -67,8 +61,6 @@ jobs:
           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

.github/workflows/ci-scikit-learn.yml

@@ -59,8 +59,6 @@ jobs:
           sudo apt-get -y -q install ffmpeg libavcodec-extra
           python -m pip install --upgrade pip setuptools wheel
           pip install -r requirements_test.txt
-          pip install tensorflow==2.10.1
-          pip install keras==2.10.0
           pip install scikit-learn==${{ matrix.scikit-learn }}
           pip list
       - name: Run Tests

.github/workflows/ci-style-checks.yml

@@ -40,15 +40,15 @@ jobs:
         run: |
           python -m pip install --upgrade pip setuptools wheel
           pip install -q pylint==2.12.2 mypy==0.931 pycodestyle==2.8.0 black==21.12b0
-          pip install -q -r requirements_test.txt
+          pip install -q -r <(sed '/^numpy/d;/^pluggy/d;/^tensorflow/d;/^keras/d' requirements_test.txt)
+          pip install numpy==1.22.4
           pip install pluggy==0.13.1
-          pip install tensorflow==2.7.0
-          pip install keras==2.7.0
+          pip install tensorflow==2.13.1
+          pip install keras==2.13.1
           pip install types-six
           pip install types-PyYAML
           pip install types-setuptools
           pip install click==8.0.2
-          pip install numpy==1.21.6
           pip list
       - name: pycodestyle
         run: pycodestyle --ignore=C0330,C0415,E203,E231,W503 --max-line-length=120 art

.github/workflows/ci-tensorflow-v1.yml

@@ -48,14 +48,15 @@ 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 '/^pandas/d;/^scipy/d;/^matplotlib/d;/^xgboost/d;/^jax/d' requirements_test.txt)
+          pip install -q -r <(sed '/^pandas/d;/^scipy/d;/^matplotlib/d;/^xgboost/d;/^tensorflow/d;/^keras/d;/^jax/d' requirements_test.txt)
           pip install pandas==1.3.5
           pip install scipy==1.7.2
           pip install matplotlib==3.5.3
           pip install xgboost==1.6.2
+          pip install protobuf==3.20.1
           pip install tensorflow==${{ matrix.tensorflow }}
           pip install keras==${{ matrix.keras }}
-          pip install jax[cpu]==0.3.25
+          pip install numpy==1.20
           pip list
       - name: Run Tests
         run: ./run_tests.sh ${{ matrix.framework }}

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

@@ -28,34 +28,27 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - name: TensorFlow 2.9.2 (Keras 2.9.0 Python 3.9)
+          - name: TensorFlow 2.13.1 (Keras 2.13.1 Python 3.10)
             framework: tensorflow
-            python: 3.9
-            tensorflow: 2.9.2
+            python: '3.10'
+            tensorflow: 2.13.1
             tf_version: v2
-            keras: 2.9.0
-            tf_addons: 0.17.1
-          - name: TensorFlow 2.10.1v1 (Keras 2.10.0 Python 3.9)
+            keras: 2.13.1
+            tf_addons: 0.21.0
+          - name: TensorFlow 2.14.0v1 (Keras 2.14.0 Python 3.10)
             framework: tensorflow2v1
-            python: 3.9
-            tensorflow: 2.10.1
-            tf_version: v2
-            keras: 2.10.0
-            tf_addons: 0.18.0
-          - name: TensorFlow 2.10.1 (Keras 2.10.0 Python 3.9)
-            framework: tensorflow
-            python: 3.9
-            tensorflow: 2.10.1
+            python: '3.10'
+            tensorflow: 2.14.0
             tf_version: v2
-            keras: 2.10.0
-            tf_addons: 0.18.0
-          - name: TensorFlow 2.10.1 (Keras 2.10.0 Python 3.10)
+            keras: 2.14.0
+            tf_addons: 0.21.0
+          - name: TensorFlow 2.14.0 (Keras 2.14.0 Python 3.10)
             framework: tensorflow
             python: '3.10'
-            tensorflow: 2.10.1
+            tensorflow: 2.14.0
             tf_version: v2
-            keras: 2.10.0
-            tf_addons: 0.18.0
+            keras: 2.14.0
+            tf_addons: 0.21.0
 
     name: ${{ matrix.name }}
     steps:
@@ -70,7 +63,7 @@ jobs:
           sudo apt-get update
           sudo apt-get -y -q install ffmpeg libavcodec-extra
           python -m pip install --upgrade pip setuptools wheel
-          pip install -r requirements_test.txt
+          pip install -q -r <(sed '/^tensorflow/d;/^keras/d;/^tensorflow-addons/d' requirements_test.txt)
           pip install tensorflow==${{ matrix.tensorflow }}
           pip install keras==${{ matrix.keras }}
           pip install tensorflow-addons==${{ matrix.tf_addons }}

.github/workflows/dockerhub.yml

@@ -39,7 +39,7 @@ jobs:
             type=semver,pattern={{version}}
 
       - name: Build and push Docker image
-        uses: docker/build-push-action@0565240e2d4ab88bba5387d719585280857ece09
+        uses: docker/build-push-action@4a13e500e55cf31b7a5d59a38ab2040ab0f42f56
         with:
           context: .
           push: true

art/attacks/evasion/adversarial_patch/adversarial_patch_pytorch.py

@@ -25,7 +25,7 @@
 
 import logging
 import math
-from typing import Optional, Tuple, Union, TYPE_CHECKING
+from typing import Any, Optional, Tuple, Union, TYPE_CHECKING
 
 import numpy as np
 from tqdm.auto import trange
@@ -270,15 +270,15 @@ def _get_circular_patch_mask(self, nb_samples: int, sharpness: int = 40) -> "tor
             y = np.linspace(-1, 1, diameter)
             x_grid, y_grid = np.meshgrid(x, y, sparse=True)
             z_grid = (x_grid ** 2 + y_grid ** 2) ** sharpness
-            image_mask = 1 - np.clip(z_grid, -1, 1)
+            image_mask: Union[int, np.ndarray[Any, np.dtype[Any]]] = 1 - np.clip(z_grid, -1, 1)
         elif self.patch_type == "square":
             image_mask = np.ones((diameter, diameter))
 
         image_mask = np.expand_dims(image_mask, axis=0)
         image_mask = np.broadcast_to(image_mask, self.patch_shape)
-        image_mask = torch.Tensor(np.array(image_mask)).to(self.estimator.device)
-        image_mask = torch.stack([image_mask] * nb_samples, dim=0)
-        return image_mask
+        image_mask_tensor = torch.Tensor(np.array(image_mask)).to(self.estimator.device)
+        image_mask_tensor = torch.stack([image_mask_tensor] * nb_samples, dim=0)
+        return image_mask_tensor
 
     def _random_overlay(
         self,

art/attacks/evasion/boundary.py

@@ -24,7 +24,7 @@
 from __future__ import absolute_import, division, print_function, unicode_literals
 
 import logging
-from typing import Optional, Tuple, TYPE_CHECKING
+from typing import List, Optional, Tuple, TYPE_CHECKING
 
 import numpy as np
 from tqdm.auto import tqdm, trange
@@ -268,14 +268,14 @@ def _attack(
         for _ in trange(self.max_iter, desc="Boundary attack - iterations", disable=not self.verbose):
             # Trust region method to adjust delta
             for _ in range(self.num_trial):
-                potential_advs = []
+                potential_advs_list: List[np.ndarray] = []
                 for _ in range(self.sample_size):
                     potential_adv = x_adv + self._orthogonal_perturb(self.curr_delta, x_adv, original_sample)
                     potential_adv = np.clip(potential_adv, clip_min, clip_max)
-                    potential_advs.append(potential_adv)
+                    potential_advs_list.append(potential_adv)
 
                 preds = np.argmax(
-                    self.estimator.predict(np.array(potential_advs), batch_size=self.batch_size),
+                    self.estimator.predict(np.array(potential_advs_list), batch_size=self.batch_size),
                     axis=1,
                 )
 
@@ -292,7 +292,7 @@ def _attack(
                     self.curr_delta /= self.step_adapt
 
                 if delta_ratio > 0:
-                    x_advs = np.array(potential_advs)[np.where(satisfied)[0]]
+                    x_advs = np.array(potential_advs_list)[np.where(satisfied)[0]]
                     break
             else:  # pragma: no cover
                 logger.warning("Adversarial example found but not optimal.")

art/attacks/evasion/brendel_bethge.py

@@ -2378,7 +2378,7 @@ def generate(
         return best_advs.astype(config.ART_NUMPY_DTYPE)
 
     def norms(self, x: np.ndarray) -> np.ndarray:
-        order = self.norm if self.norm != "inf" else np.inf
+        order = float(self.norm) if self.norm != "inf" else np.inf
         norm = np.linalg.norm(x=x.reshape(x.shape[0], -1), ord=order, axis=1)
         return norm
 
@@ -2542,15 +2542,15 @@ def _binary_search(
         """
         # First set upper and lower bounds as well as the threshold for the binary search
         if norm == 2:
-            (upper_bound, lower_bound) = (1, 0)
+            (upper_bound, lower_bound) = (np.array(1.0), np.array(0.0))
 
             if threshold is None:
                 threshold = self.theta
 
         else:
             (upper_bound, lower_bound) = (
                 np.max(abs(original_sample - current_sample)),
-                0,
+                np.array(0.0),
             )
 
             if threshold is None:
@@ -2580,7 +2580,7 @@ def _binary_search(
         result = self._interpolate(
             current_sample=current_sample,
             original_sample=original_sample,
-            alpha=upper_bound,
+            alpha=float(upper_bound),
             norm=norm,
         )
 

art/attacks/evasion/carlini.py

@@ -136,7 +136,7 @@ def __init__(
         self._tanh_smoother = 0.999999
 
     def _loss(
-        self, x: np.ndarray, x_adv: np.ndarray, target: np.ndarray, c_weight: float
+        self, x: np.ndarray, x_adv: np.ndarray, target: np.ndarray, c_weight: np.ndarray
     ) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
         """
         Compute the objective function value.

art/attacks/evasion/dpatch_robust.py

@@ -409,8 +409,8 @@ def _untransform_gradients(
         gradients = transforms["brightness"] * gradients
 
         # Undo rotations:
-        rot90 = (4 - transforms["rot90"]) % 4
-        gradients = np.rot90(gradients, rot90, (1, 2))
+        rot90 = int((4 - transforms["rot90"]) % 4)
+        gradients = np.rot90(gradients, k=rot90, axes=(1, 2))
 
         # Account for cropping when considering the upper left point of the patch:
         x_1 = self.patch_location[0] - int(transforms["crop_x"])