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Merge branch 'main' into feature/dynamic-backdoor-gan
2 parents 8a553fe + 0c36b85 commit c804ecf

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.github/workflows/ci-huggingface.yml

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@@ -51,13 +51,14 @@ jobs:
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sudo apt-get update
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sudo apt-get -y -q install ffmpeg libavcodec-extra
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python -m pip install --upgrade pip setuptools wheel
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pip install -q -r <(sed '/^tensorflow/d;/^keras/d;/^torch/d;/^torchvision/d;/^torchaudio/d;/^transformers/d' requirements_test.txt)
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pip install -q -r <(sed '/^tensorflow/d;/^keras/d;/^torch/d;/^torchvision/d;/^torchaudio/d;/^transformers/d;/^safetensors/d' requirements_test.txt)
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pip install tensorflow==2.18.1
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pip install keras==3.10.0
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pip install torch==${{ matrix.torch }} --index-url https://download.pytorch.org/whl/cpu
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pip install torchvision==${{ matrix.torchvision }} --index-url https://download.pytorch.org/whl/cpu
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pip install torchaudio==${{ matrix.torchaudio }} --index-url https://download.pytorch.org/whl/cpu
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pip install transformers==${{ matrix.transformers }}
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pip install safetensors==0.5.3
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pip list
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- name: Cache CIFAR-10 dataset

.github/workflows/ci-legacy.yml

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python: '3.10'
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tensorflow: 2.18.1
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keras: 3.10.0
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torch: 2.7.0
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torchvision: 0.22.0
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torchaudio: 2.7.0
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torch: 2.8.0
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torchvision: 0.23.0
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torchaudio: 2.8.0
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scikit-learn: 1.6.1
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name: Run ${{ matrix.module }} ${{ matrix.name }} Tests

.github/workflows/ci-pytorch.yml

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fail-fast: false
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matrix:
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include:
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- name: PyTorch 2.6.0 (Python 3.10)
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framework: pytorch
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python: '3.10'
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torch: 2.6.0
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torchvision: 0.21.0
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torchaudio: 2.6.0
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- name: PyTorch 2.7.1 (Python 3.10)
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framework: pytorch
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python: '3.10'
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torch: 2.7.1
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torchvision: 0.22.1
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torchaudio: 2.7.1
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- name: PyTorch 2.8.0 (Python 3.10)
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framework: pytorch
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python: '3.10'
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torch: 2.8.0
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torchvision: 0.23.0
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torchaudio: 2.8.0
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name: ${{ matrix.name }}
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steps:

art/estimators/certification/deep_z/pytorch.py

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@@ -169,7 +169,7 @@ def concrete_forward(self, in_x: np.ndarray | "torch.Tensor") -> "torch.Tensor":
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# as reshapes are not modules we infer when the reshape from convolutional to dense occurs
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if self.reshape_op_num == op_num:
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x = x.reshape((x.shape[0], -1))
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x = op.concrete_forward(x)
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x = op.concrete_forward(x) # type: ignore
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return x
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def set_forward_mode(self, mode: str) -> None:

art/estimators/certification/interval/pytorch.py

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@@ -179,7 +179,7 @@ def concrete_forward(self, in_x: np.ndarray | "torch.Tensor") -> "torch.Tensor":
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if isinstance(op, PyTorchIntervalConv2D) and self.forward_mode == "attack":
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x = op.conv_forward(x)
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else:
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x = op.concrete_forward(x)
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x = op.concrete_forward(x) # type: ignore
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return x
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def set_forward_mode(self, mode: str) -> None:

requirements_test.txt

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keras==3.10.0
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# PyTorch
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torch==2.7.1
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torchaudio==2.7.1
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torchvision==0.22.1
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torch==2.8.0
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torchaudio==2.8.0
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torchvision==0.23.0
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# PyTorch image transformers
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timm==1.0.19
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# YOLO dependencies
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ultralytics==8.3.170
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ultralytics==8.3.176
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catboost==1.2.8
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GPy==1.13.2
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mypy==1.17.1
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pycodestyle==2.14.0
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black==25.1.0
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ruff==0.12.7
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ruff==0.12.8
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types-six==1.17.0.20250515
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types-PyYAML==6.0.12.20250516
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types-setuptools==80.9.0.20250529
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types-PyYAML==6.0.12.20250809
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types-setuptools==80.9.0.20250809
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# other
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requests~=2.32.4

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