ci: pre-commit autoupdate

.pre-commit-config.yaml

@@ -13,7 +13,7 @@ ci:
 
 repos:
   - repo: https://github.com/compilerla/conventional-pre-commit
-    rev: v2.4.0
+    rev: v4.3.0
     hooks:
       - id: conventional-pre-commit
         stages: [commit-msg]
@@ -36,7 +36,7 @@ repos:
           ]
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.5.0
+    rev: v6.0.0
     hooks:
       - id: trailing-whitespace
       - id: end-of-file-fixer
@@ -70,71 +70,71 @@ repos:
       - id: text-unicode-replacement-char
 
   - repo: https://github.com/Lucas-C/pre-commit-hooks-safety
-    rev: v1.3.2
+    rev: v1.4.2
     hooks:
     -   id: python-safety-dependencies-check
         files: pyproject.toml
 
   - repo: https://github.com/PyCQA/docformatter
-    rev: v1.7.5
+    rev: v1.7.7
     hooks:
       - id: docformatter
 
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.7.0
+    rev: 1.9.1
     hooks:
       - id: nbqa-check-ast
       - id: nbqa-mypy
         args: ["--config-file=pyproject.toml"]
       - id: nbqa-pyupgrade
 
   - repo: https://github.com/bwhmather/ssort
-    rev: v0.11.6
+    rev: 0.15.0
     hooks:
       - id: ssort
 
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.15.0
+    rev: v3.21.1
     hooks:
       - id: pyupgrade
 
-  - repo: https://github.com/psf/black
-    rev: 23.10.1
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 25.11.0
     hooks:
       - id: black
       - id: black-jupyter
         files: \.ipynb$
 
   - repo: https://github.com/PyCQA/isort
-    rev: 5.12.0
+    rev: 7.0.0
     hooks:
       - id: isort
         args: ["--profile=black"]
 
   - repo: https://github.com/PyCQA/pylint
-    rev: v3.0.1
+    rev: v4.0.2
     hooks:
       - id: pylint
         args: ["--rcfile=pyproject.toml"]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.6.1
+    rev: v1.18.2
     hooks:
       - id: mypy
         args:
           - "--config-file=pyproject.toml"
         exclude: "tests"
 
   - repo: https://github.com/PyCQA/bandit
-    rev: 1.7.5
+    rev: 1.8.6
     hooks:
       - id: bandit
         exclude: "^tests/"
         args:
           - "-r"
 
   - repo: https://github.com/kynan/nbstripout
-    rev: 0.6.1
+    rev: 0.8.1
     hooks:
       - id: nbstripout
 

src/autoembedder/data.py

@@ -28,7 +28,7 @@ def __init__(
 
     @staticmethod
     def _data_from_source(
-        source: Union[str, dd.DataFrame, pd.DataFrame]
+        source: Union[str, dd.DataFrame, pd.DataFrame],
     ) -> dd.DataFrame:
         if isinstance(source, str):
             try:

src/autoembedder/evaluator.py

@@ -37,9 +37,11 @@ def _predict(
     device = torch.device(
         "cuda"
         if torch.cuda.is_available()
-        else "mps"
-        if torch.backends.mps.is_available() and parameters.get("use_mps", False)
-        else "cpu"
+        else (
+            "mps"
+            if torch.backends.mps.is_available() and parameters.get("use_mps", False)
+            else "cpu"
+        )
     )
 
     with torch.no_grad():

src/autoembedder/learner.py

@@ -362,9 +362,12 @@ def fit(
         torch.device(
             "cuda"
             if torch.cuda.is_available()
-            else "mps"
-            if torch.backends.mps.is_available() and parameters.get("use_mps", False)
-            else "cpu"
+            else (
+                "mps"
+                if torch.backends.mps.is_available()
+                and parameters.get("use_mps", False)
+                else "cpu"
+            )
         )
     )
     if (
@@ -437,10 +440,12 @@ def fit(
             map_location=torch.device(
                 "cuda"
                 if torch.cuda.is_available()
-                else "mps"
-                if torch.backends.mps.is_available()
-                and parameters.get("use_mps", False)
-                else "cpu"
+                else (
+                    "mps"
+                    if torch.backends.mps.is_available()
+                    and parameters.get("use_mps", False)
+                    else "cpu"
+                )
             ),
         )
         Checkpoint.load_objects(

src/autoembedder/model.py

@@ -58,9 +58,11 @@ def model_input(
     device = torch.device(
         "cuda"
         if torch.cuda.is_available()
-        else "mps"
-        if torch.backends.mps.is_available() and parameters.get("use_mps", False)
-        else "cpu"
+        else (
+            "mps"
+            if torch.backends.mps.is_available() and parameters.get("use_mps", False)
+            else "cpu"
+        )
     )
     cat = []
     cont = []