[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/zero/low_level/bookkeeping/__init__.py

@@ -3,4 +3,4 @@ from .gradient_store import GradientStore
 from .parameter_store import ParameterStore
 from .tensor_bucket import TensorBucket
 
-__all__ = ['GradientStore', 'ParameterStore', 'BucketStore', 'TensorBucket']
+__all__ = ["GradientStore", "ParameterStore", "BucketStore", "TensorBucket"]

colossalai/zero/low_level/bookkeeping/base_store.py

@@ -3,7 +3,6 @@ from torch.distributed import ProcessGroup
 
 
 class BaseStore:
-
     def __init__(self, torch_pg: ProcessGroup):
         self._world_size = dist.get_world_size(group=torch_pg)
         self._local_rank = dist.get_rank(group=torch_pg)

colossalai/zero/low_level/bookkeeping/bucket_store.py

@@ -9,7 +9,6 @@ from .base_store import BaseStore
 
 
 class BucketStore(BaseStore):
-
     def __init__(self, torch_pg: ProcessGroup):
         super().__init__(torch_pg)
 
@@ -38,8 +37,7 @@ class BucketStore(BaseStore):
         return self._num_elements_in_bucket
 
     def reset_num_elements_in_bucket(self):
-        """Set the number of elements in bucket to zero.
-        """
+        """Set the number of elements in bucket to zero."""
 
         self._num_elements_in_bucket = 0
 
@@ -54,7 +52,7 @@ class BucketStore(BaseStore):
 
         self._param_list.append(param)
         self._padding_size.append(padding_size)
-        self._num_elements_in_bucket += (param.numel() + padding_size)
+        self._num_elements_in_bucket += param.numel() + padding_size
         self.current_group_id = group_id
 
         # number of tensors in current bucket
@@ -119,8 +117,7 @@ class BucketStore(BaseStore):
         return self.grad_to_param_mapping[id(grad)]
 
     def reset(self):
-        """Reset the bucket storage after reduction, only release the tensors have been reduced
-        """
+        """Reset the bucket storage after reduction, only release the tensors have been reduced"""
         cur_offset = self.offset_list.pop(0)
         self._param_list = self._param_list[cur_offset:]
         self._padding_size = self._padding_size[cur_offset:]

colossalai/zero/low_level/bookkeeping/gradient_store.py

@@ -1,13 +1,11 @@
 from typing import List
 
 from torch import Tensor
-from torch._utils import _flatten_dense_tensors
 
 from .base_store import BaseStore
 
 
 class GradientStore(BaseStore):
-
     def __init__(self, *args, partition_grad: bool = False):
         super().__init__(*args)
         """

colossalai/zero/low_level/bookkeeping/parameter_store.py

@@ -5,7 +5,6 @@ from .base_store import BaseStore
 
 
 class ParameterStore(BaseStore):
-
     def __init__(self, torch_pg: ProcessGroup):
         super().__init__(torch_pg)
 

colossalai/zero/low_level/bookkeeping/tensor_bucket.py

@@ -2,7 +2,6 @@ from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
 
 
 class TensorBucket:
-
     def __init__(self, size):
         self._max_size = size
         self._current_size = 0
@@ -26,8 +25,7 @@ class TensorBucket:
         tensor_size = tensor.numel()
 
         if not allow_oversize and self.will_exceed_max_size(tensor_size):
-            msg = f"The param bucket max size {self._max_size} is exceeded" \
-                + f"by tensor (size {tensor_size})"
+            msg = f"The param bucket max size {self._max_size} is exceeded" + f"by tensor (size {tensor_size})"
             raise RuntimeError(msg)
 
         self._bucket.append(tensor)