Merge pull request #829 from Trusted-AI/dev_1.5.1

Update to ART 1.5.1

Author: beat-buesser

.github/workflows/ci.yml

@@ -127,6 +127,8 @@ jobs:
           pip list
       - name: Run ${{ matrix.name }} Tests
         run: ./run_tests.sh ${{ matrix.framework }}
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v1
   style:
     name: Style Check
     runs-on: ubuntu-latest

art/attacks/evasion/adversarial_asr.py

@@ -0,0 +1,85 @@
+# MIT License
+#
+# Copyright (C) The Adversarial Robustness Toolbox (ART) Authors 2020
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated
+# documentation files (the "Software"), to deal in the Software without restriction, including without limitation the
+# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit
+# persons to whom the Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all copies or substantial portions of the
+# Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE
+# WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.
+"""
+This module implements the audio adversarial attack on automatic speech recognition systems of Carlini and Wagner
+(2018). It generates an adversarial audio example.
+
+| Paper link: https://arxiv.org/abs/1801.01944
+"""
+from __future__ import absolute_import, division, print_function, unicode_literals
+
+import logging
+from typing import TYPE_CHECKING
+
+from art.attacks.attack import EvasionAttack
+from art.attacks.evasion.imperceptible_asr.imperceptible_asr import ImperceptibleASR
+
+if TYPE_CHECKING:
+    from art.utils import SPEECH_RECOGNIZER_TYPE
+
+logger = logging.getLogger(__name__)
+
+
+class CarliniWagnerASR(ImperceptibleASR):
+    """
+    Implementation of the Carlini and Wagner audio adversarial attack against a speech recognition model.
+
+    | Paper link: https://arxiv.org/abs/1801.01944
+    """
+
+    attack_params = EvasionAttack.attack_params + [
+        "eps",
+        "learning_rate",
+        "max_iter",
+        "batch_size",
+    ]
+
+    def __init__(
+        self,
+        estimator: "SPEECH_RECOGNIZER_TYPE",
+        eps: float = 2000.0,
+        learning_rate: float = 100.0,
+        max_iter: int = 1000,
+        batch_size: int = 16,
+    ):
+        """
+        Create an instance of the :class:`.CarliniWagnerASR`.
+
+        :param estimator: A trained speech recognition estimator.
+        :param eps: Initial max norm bound for adversarial perturbation.
+        :param learning_rate: Learning rate of attack.
+        :param max_iter: Number of iterations.
+        :param batch_size: Batch size.
+        """
+        # pylint: disable=W0231
+
+        # re-implement init such that inherrited methods work
+        EvasionAttack.__init__(self, estimator=estimator)  # pylint: disable=W0233
+        self.masker = None
+        self.eps = eps
+        self.learning_rate_1 = learning_rate
+        self.max_iter_1 = max_iter
+        self.max_iter_2 = 0
+        self._targeted = True
+        self.batch_size = batch_size
+
+        # set remaining stage 2 params to some random values
+        self.alpha = 0.1
+        self.learning_rate_2 = 0.1
+
+        self._check_params()

art/attacks/evasion/adversarial_patch/adversarial_patch_numpy.py

@@ -30,7 +30,7 @@
 import random
 import numpy as np
 from scipy.ndimage import rotate, shift, zoom
-from tqdm import trange
+from tqdm.auto import trange
 
 from art.attacks.attack import EvasionAttack
 from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin

art/attacks/evasion/adversarial_patch/adversarial_patch_tensorflow.py

@@ -28,7 +28,7 @@
 from typing import Optional, Tuple, Union, TYPE_CHECKING
 
 import numpy as np
-from tqdm import trange
+from tqdm.auto import trange
 
 from art.attacks.attack import EvasionAttack
 from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin

art/attacks/evasion/boundary.py

@@ -27,7 +27,7 @@
 from typing import Optional, Tuple, TYPE_CHECKING
 
 import numpy as np
-from tqdm import tqdm, trange
+from tqdm.auto import tqdm, trange
 
 from art.attacks.attack import EvasionAttack
 from art.config import ART_NUMPY_DTYPE

art/attacks/evasion/carlini.py

@@ -30,7 +30,7 @@
 from typing import Optional, Tuple, TYPE_CHECKING
 
 import numpy as np
-from tqdm import trange
+from tqdm.auto import trange
 
 from art.config import ART_NUMPY_DTYPE
 from art.estimators.estimator import BaseEstimator

art/attacks/evasion/decision_tree_attack.py

@@ -24,7 +24,7 @@
 from typing import List, Optional, Union
 
 import numpy as np
-from tqdm import trange
+from tqdm.auto import trange
 
 from art.attacks.attack import EvasionAttack
 from art.estimators.classification.scikitlearn import ScikitlearnDecisionTreeClassifier

art/attacks/evasion/deepfool.py

@@ -26,7 +26,7 @@
 from typing import Optional, TYPE_CHECKING
 
 import numpy as np
-from tqdm import trange
+from tqdm.auto import trange
 
 from art.config import ART_NUMPY_DTYPE
 from art.estimators.estimator import BaseEstimator

art/attacks/evasion/dpatch.py

@@ -26,7 +26,7 @@
 from typing import Dict, List, Optional, Tuple, Union, TYPE_CHECKING
 
 import numpy as np
-from tqdm import trange
+from tqdm.auto import trange
 
 from art.attacks.attack import EvasionAttack
 from art.estimators.estimator import BaseEstimator, LossGradientsMixin

art/attacks/evasion/dpatch_robust.py

@@ -30,7 +30,7 @@
 from typing import Dict, List, Optional, Tuple, Union, TYPE_CHECKING
 
 import numpy as np
-from tqdm import trange
+from tqdm.auto import trange
 
 from art.attacks.attack import EvasionAttack
 from art.estimators.estimator import BaseEstimator, LossGradientsMixin