[misc] update pre-commit and run all files (#4752)

* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format

colossalai/booster/plugin/plugin_base.py

@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Callable, Iterator, List, Optional, Tuple, Union
+from typing import Callable, Iterator, List, Optional, Tuple
 
 import torch.nn as nn
 from torch.optim import Optimizer
@@ -9,11 +9,10 @@ from torch.utils.data import DataLoader, Dataset
 from colossalai.checkpoint_io import CheckpointIO
 from colossalai.interface import OptimizerWrapper
 
-__all__ = ['Plugin']
+__all__ = ["Plugin"]
 
 
 class Plugin(ABC):
-
     @abstractmethod
     def supported_devices(self) -> List[str]:
         pass
@@ -51,33 +50,31 @@ class Plugin(ABC):
         """
         Whether the plugin controls the checkpoint io
         """
-        pass
 
     @abstractmethod
     def get_checkpoint_io(self) -> CheckpointIO:
         """
         Get checkpoint io object for this plugin, only invoked when control_checkpoint_io is True.
         """
-        pass
 
     @abstractmethod
     def no_sync(self, model: nn.Module, optimizer: OptimizerWrapper) -> Iterator[None]:
         """
         Context manager to disable gradient synchronization.
         """
-        pass
 
     @abstractmethod
-    def prepare_dataloader(self,
-                           dataset: Dataset,
-                           batch_size: int,
-                           shuffle: bool = False,
-                           seed: int = 1024,
-                           drop_last: bool = False,
-                           pin_memory: bool = False,
-                           num_workers: int = 0,
-                           **kwargs):
+    def prepare_dataloader(
+        self,
+        dataset: Dataset,
+        batch_size: int,
+        shuffle: bool = False,
+        seed: int = 1024,
+        drop_last: bool = False,
+        pin_memory: bool = False,
+        num_workers: int = 0,
+        **kwargs,
+    ):
         """Prepare a dataloader for distributed training. The dataloader will be wrapped by
         `torch.utils.data.DataLoader`
         """
-        pass