[pre-commit.ci] pre-commit suggestions (#9137)

<!--pre-commit.ci start-->
updates:
- [github.com/adrienverge/yamllint.git: v1.33.0 →
v1.35.1](https://github.com/adrienverge/yamllint.git/compare/v1.33.0...v1.35.1)
- [github.com/PyCQA/flake8: 6.1.0 →
7.0.0](PyCQA/flake8@6.1.0...7.0.0)
- [github.com/astral-sh/ruff-pre-commit: v0.1.9 →
v0.3.5](astral-sh/ruff-pre-commit@v0.1.9...v0.3.5)
<!--pre-commit.ci end-->

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: rusty1s <[email protected]>

.github/labeler.yml

@@ -55,4 +55,4 @@ benchmark:
       - any-glob-to-any-file: ["benchmark/**/*", "torch_geometric/profile/**/*"]
 
 skip-changelog:
-  - head-branch: ['^skip']
+  - head-branch: ['^skip', '^pre-commit-ci']

.pre-commit-config.yaml

@@ -27,7 +27,7 @@ repos:
           )$
 
   - repo: https://github.com/adrienverge/yamllint.git
-    rev: v1.33.0
+    rev: v1.35.1
     hooks:
       - id: yamllint
         name: Lint yaml
@@ -47,14 +47,14 @@ repos:
         name: Sort imports
 
   - repo: https://github.com/PyCQA/flake8
-    rev: 6.1.0
+    rev: 7.0.0
     hooks:
       - id: flake8
         name: Check PEP8
         additional_dependencies: [Flake8-pyproject]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.9
+    rev: v0.3.5
     hooks:
       - id: ruff
         name: Ruff formatting

torch_geometric/datasets/pascal.py

@@ -227,10 +227,12 @@ def hook(module: torch.nn.Module, x: Tensor, y: Tensor) -> None:
 
             # Add a small offset to the bounding because some keypoints lay
             # outside the bounding box intervals.
-            box = (min(float(pos[:, 0].min().floor()), box[0]) - 16,
-                   min(float(pos[:, 1].min().floor()), box[1]) - 16,
-                   max(float(pos[:, 0].max().ceil()), box[2]) + 16,
-                   max(float(pos[:, 1].max().ceil()), box[3]) + 16)
+            box = (
+                min(int(pos[:, 0].min().floor()), box[0]) - 16,
+                min(int(pos[:, 1].min().floor()), box[1]) - 16,
+                max(int(pos[:, 0].max().ceil()), box[2]) + 16,
+                max(int(pos[:, 1].max().ceil()), box[3]) + 16,
+            )
 
             # Rescale keypoints.
             pos[:, 0] = (pos[:, 0] - box[0]) * 256.0 / (box[2] - box[0])
@@ -239,7 +241,7 @@ def hook(module: torch.nn.Module, x: Tensor, y: Tensor) -> None:
             path = osp.join(image_path, f'{filename}.jpg')
             with open(path, 'rb') as f:
                 img = Image.open(f).convert('RGB').crop(box)
-                img = img.resize((256, 256), resample=Image.BICUBIC)
+                img = img.resize((256, 256), resample=Image.Resampling.BICUBIC)
 
             img = transform(img)
 

torch_geometric/datasets/willow_object_class.py

@@ -142,7 +142,7 @@ def hook(module: torch.nn.Module, x: Tensor, y: Tensor) -> None:
             pos[:, 0] = pos[:, 0] * 256.0 / (img.size[0])
             pos[:, 1] = pos[:, 1] * 256.0 / (img.size[1])
 
-            img = img.resize((256, 256), resample=Image.BICUBIC)
+            img = img.resize((256, 256), resample=Image.Resampling.BICUBIC)
             img = transform(img)
 
             data = Data(img=img, pos=pos, name=name)