[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/nn/lr_scheduler/poly.py

@@ -15,15 +15,11 @@ class PolynomialLR(_LRScheduler):
             the schedule is started from the beginning or When last_epoch=-1, sets initial lr as lr.
     """
 
-    def __init__(self,
-                 optimizer,
-                 total_steps: int,
-                 end_lr: float = 0.0001,
-                 power: float = 1.0,
-                 last_epoch: int = -1,
-                 **kwargs):
+    def __init__(
+        self, optimizer, total_steps: int, end_lr: float = 0.0001, power: float = 1.0, last_epoch: int = -1, **kwargs
+    ):
         if end_lr < 0:
-            raise ValueError(f'end_lr must >= 0, got {end_lr}')
+            raise ValueError(f"end_lr must >= 0, got {end_lr}")
         self.total_steps = total_steps
         self.end_lr = end_lr
         self.power = power
@@ -33,9 +29,11 @@ class PolynomialLR(_LRScheduler):
         return self._get_closed_form_lr()
 
     def _get_closed_form_lr(self):
-        return [(base_lr - self.end_lr) *
-                ((1 - min(self.last_epoch, self.total_steps) / self.total_steps)**self.power) + self.end_lr
-                for base_lr in self.base_lrs]
+        return [
+            (base_lr - self.end_lr) * ((1 - min(self.last_epoch, self.total_steps) / self.total_steps) ** self.power)
+            + self.end_lr
+            for base_lr in self.base_lrs
+        ]
 
 
 class PolynomialWarmupLR(WarmupScheduler):
@@ -51,13 +49,15 @@ class PolynomialWarmupLR(WarmupScheduler):
             the schedule is started from the beginning or When last_epoch=-1, sets initial lr as lr.
     """
 
-    def __init__(self,
-                 optimizer,
-                 total_steps: int,
-                 warmup_steps: int = 0,
-                 end_lr: float = 0.0001,
-                 power: float = 1.0,
-                 last_epoch: int = -1,
-                 **kwargs):
+    def __init__(
+        self,
+        optimizer,
+        total_steps: int,
+        warmup_steps: int = 0,
+        end_lr: float = 0.0001,
+        power: float = 1.0,
+        last_epoch: int = -1,
+        **kwargs,
+    ):
         base_scheduler = PolynomialLR(optimizer, total_steps - warmup_steps, end_lr=end_lr, power=power)
         super().__init__(optimizer, warmup_steps, base_scheduler, last_epoch=last_epoch)