[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/tensor/colo_tensor.py

@@ -7,7 +7,7 @@ INPALCE_MAPPING = {
     torch.Tensor.add_: torch.Tensor.add,
     torch.Tensor.sub_: torch.Tensor.sub,
     torch.Tensor.mul_: torch.Tensor.mul,
-    torch.Tensor.div_: torch.Tensor.div
+    torch.Tensor.div_: torch.Tensor.div,
 }
 
 
@@ -18,7 +18,7 @@ def _get_my_nowrap_functions() -> Set[Callable]:
         Tensor._base.__get__,
         Tensor.grad.__get__,
         Tensor._grad.__get__,
-        Tensor.data.__get__,    # make .data returns torch.Tensor rather than ColoTensor
+        Tensor.data.__get__,  # make .data returns torch.Tensor rather than ColoTensor
     }
 
 
@@ -37,17 +37,18 @@ def _convert_output(output, func):
 
 
 class ColoTensor(torch.Tensor):
-    """ Data Structure for Tensor in Colossal-AI. It is a subclass of torch.Tensor.
+    """Data Structure for Tensor in Colossal-AI. It is a subclass of torch.Tensor.
 
     It is only used to trigger the torch function hook.
 
     Args:
         data (torch.Tensor): a torch tensor used as the payload the colotensor.
     """
-    torch_major = int(torch.__version__.split('.')[0])
-    torch_minor = int(torch.__version__.split('.')[1])
 
-    def __new__(cls, data: torch.Tensor) -> 'ColoTensor':
+    torch_major = int(torch.__version__.split(".")[0])
+    torch_minor = int(torch.__version__.split(".")[1])
+
+    def __new__(cls, data: torch.Tensor) -> "ColoTensor":
         """
         The signature of the __new__ has to be consistent with the torch.Tensor.
 
@@ -74,7 +75,7 @@ class ColoTensor(torch.Tensor):
             # we have to capture the `backward` function
             # and make sure that it does not in `torch._C.DisableTorchFunction()` context
             if func is torch.Tensor.backward:
-                assert len(args) == 1    # only has 1 parameter
+                assert len(args) == 1  # only has 1 parameter
                 backward_tensor = torch.Tensor(args[0])
                 tensor_kwargs = {k: torch.Tensor(v) if torch.is_tensor(v) else v for k, v in kwargs.items()}
                 return backward_tensor.backward(**tensor_kwargs)
@@ -83,8 +84,8 @@ class ColoTensor(torch.Tensor):
         if func in INPALCE_MAPPING:
             func = INPALCE_MAPPING[func]
         # set the 'inplace' kwargs to False
-        if 'inplace' in kwargs:
-            kwargs['inplace'] = False
+        if "inplace" in kwargs:
+            kwargs["inplace"] = False
 
         with torch._C.DisableTorchFunction():
             ret = func(*args, **kwargs)