[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

src/lightning/pytorch/cli.py

@@ -126,50 +126,50 @@ def add_lightning_class_args(
         required: bool = True,
     ) -> list[str]:
         """Adds arguments from a lightning class to a nested key of the parser.
-    
+
         Args:
             lightning_class: A callable or any subclass of {Trainer, LightningModule, LightningDataModule, Callback}.
             nested_key: Name of the nested namespace to store arguments.
             subclass_mode: Whether to allow any subclass of the given class.
             required: Whether the argument group is required.
-    
+
         Returns:
             A list with the names of the class arguments added.
+
         """
         if callable(lightning_class) and not isinstance(lightning_class, type):
             lightning_class = class_from_function(lightning_class)
-    
+
         if isinstance(lightning_class, type) and issubclass(
             lightning_class, (Trainer, LightningModule, LightningDataModule, Callback)
         ):
             if issubclass(lightning_class, Callback):
                 self.callback_keys.append(nested_key)
-    
+
             # NEW LOGIC: If subclass_mode=False and required=False, only add if config provides this key
             if not subclass_mode and not required:
                 config_path = f"{self.subcommand}.{nested_key}" if getattr(self, "subcommand", None) else nested_key
                 config = getattr(self, "config", {})
-                if not any(k.startswith(config_path) for k in config.keys()):
+                if not any(k.startswith(config_path) for k in config):
                     # Skip adding class arguments
                     return []
-    
+
             if subclass_mode:
                 return self.add_subclass_arguments(lightning_class, nested_key, fail_untyped=False, required=required)
-    
+
             return self.add_class_arguments(
                 lightning_class,
                 nested_key,
                 fail_untyped=False,
                 instantiate=not issubclass(lightning_class, Trainer),
                 sub_configs=True,
             )
-    
+
         raise MisconfigurationException(
             f"Cannot add arguments from: {lightning_class}. You should provide either a callable or a subclass of: "
             "Trainer, LightningModule, LightningDataModule, or Callback."
         )
 
-
     def add_optimizer_args(
         self,
         optimizer_class: Union[type[Optimizer], tuple[type[Optimizer], ...]] = (Optimizer,),

tests/tests_pytorch/test_cli.py

@@ -1792,30 +1792,28 @@ def test_lightning_cli_args_and_sys_argv_warning():
 
 
 def test_add_class_args_required_false_skips_addition(tmp_path):
-    from lightning.pytorch import cli, callbacks
+    from lightning.pytorch import callbacks, cli
 
     class FooCheckpoint(callbacks.ModelCheckpoint):
         def __init__(self, dirpath, *args, **kwargs):
             super().__init__(dirpath, *args, **kwargs)
 
     class SimpleModel:
-        def __init__(self): pass
+        def __init__(self):
+            pass
 
     class SimpleDataModule:
-        def __init__(self): pass
+        def __init__(self):
+            pass
 
     class FooCLI(cli.LightningCLI):
         def __init__(self):
             super().__init__(
-                model_class=SimpleModel,
-                datamodule_class=SimpleDataModule,
-                run=False,
-                save_config_callback=None
+                model_class=SimpleModel, datamodule_class=SimpleDataModule, run=False, save_config_callback=None
             )
 
         def add_arguments_to_parser(self, parser):
             parser.add_lightning_class_args(FooCheckpoint, "checkpoint", required=False)
 
     # Expectation: No error raised even though FooCheckpoint requires `dirpath`
     FooCLI()
-