diff --git a/.github/workflows/ci-legacy.yml b/.github/workflows/ci-legacy.yml index ac32fa41f4..d41429599f 100644 --- a/.github/workflows/ci-legacy.yml +++ b/.github/workflows/ci-legacy.yml @@ -34,9 +34,9 @@ jobs: python: '3.10' tensorflow: 2.18.1 keras: 3.10.0 - torch: 2.7.0 - torchvision: 0.22.0 - torchaudio: 2.7.0 + torch: 2.8.0 + torchvision: 0.23.0 + torchaudio: 2.8.0 scikit-learn: 1.6.1 name: Run ${{ matrix.module }} ${{ matrix.name }} Tests diff --git a/.github/workflows/ci-pytorch.yml b/.github/workflows/ci-pytorch.yml index 4ecb102791..93d010501e 100644 --- a/.github/workflows/ci-pytorch.yml +++ b/.github/workflows/ci-pytorch.yml @@ -28,18 +28,18 @@ jobs: fail-fast: false matrix: include: - - name: PyTorch 2.6.0 (Python 3.10) - framework: pytorch - python: '3.10' - torch: 2.6.0 - torchvision: 0.21.0 - torchaudio: 2.6.0 - name: PyTorch 2.7.1 (Python 3.10) framework: pytorch python: '3.10' torch: 2.7.1 torchvision: 0.22.1 torchaudio: 2.7.1 + - name: PyTorch 2.8.0 (Python 3.10) + framework: pytorch + python: '3.10' + torch: 2.8.0 + torchvision: 0.23.0 + torchaudio: 2.8.0 name: ${{ matrix.name }} steps: diff --git a/art/estimators/certification/deep_z/pytorch.py b/art/estimators/certification/deep_z/pytorch.py index e62d4142a0..62582d832c 100644 --- a/art/estimators/certification/deep_z/pytorch.py +++ b/art/estimators/certification/deep_z/pytorch.py @@ -169,7 +169,7 @@ def concrete_forward(self, in_x: np.ndarray | "torch.Tensor") -> "torch.Tensor": # as reshapes are not modules we infer when the reshape from convolutional to dense occurs if self.reshape_op_num == op_num: x = x.reshape((x.shape[0], -1)) - x = op.concrete_forward(x) + x = op.concrete_forward(x) # type: ignore return x def set_forward_mode(self, mode: str) -> None: diff --git a/art/estimators/certification/interval/pytorch.py b/art/estimators/certification/interval/pytorch.py index b8125d4bc8..322f14d41b 100644 --- a/art/estimators/certification/interval/pytorch.py +++ b/art/estimators/certification/interval/pytorch.py @@ -179,7 +179,7 @@ def concrete_forward(self, in_x: np.ndarray | "torch.Tensor") -> "torch.Tensor": if isinstance(op, PyTorchIntervalConv2D) and self.forward_mode == "attack": x = op.conv_forward(x) else: - x = op.concrete_forward(x) + x = op.concrete_forward(x) # type: ignore return x def set_forward_mode(self, mode: str) -> None: diff --git a/requirements_test.txt b/requirements_test.txt index 783292fc9f..2dfa3ebc3f 100644 --- a/requirements_test.txt +++ b/requirements_test.txt @@ -28,9 +28,9 @@ tensorflow==2.18.1 keras==3.10.0 # PyTorch -torch==2.7.1 -torchaudio==2.7.1 -torchvision==0.22.1 +torch==2.8.0 +torchaudio==2.8.0 +torchvision==0.23.0 # PyTorch image transformers timm==1.0.19