Merge pull request #2716 from Trusted-AI/dependabot/pip/torch-2.8.0

Bump torch from 2.7.1 to 2.8.0

Author: beat-buesser

.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

.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:

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:

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:

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