[NFC] polish colossalai/amp/naive_amp/_fp16_optimizer.py code style
diff --git a/colossalai/amp/naive_amp/_fp16_optimizer.py b/colossalai/amp/naive_amp/_fp16_optimizer.py
index 58d9e3df116e..b01a3cbf0108 100644
--- a/colossalai/amp/naive_amp/_fp16_optimizer.py
+++ b/colossalai/amp/naive_amp/_fp16_optimizer.py
@@ -9,14 +9,16 @@
 except:
     print('Colossalai should be built with cuda extension to use the FP16 optimizer')
 
+from torch.distributed import ProcessGroup
 from torch.optim import Optimizer
-from colossalai.core import global_context as gpc
+
 from colossalai.context import ParallelMode
+from colossalai.core import global_context as gpc
 from colossalai.logging import get_dist_logger
-from colossalai.utils import (copy_tensor_parallel_attributes, clip_grad_norm_fp32, multi_tensor_applier)
-from torch.distributed import ProcessGroup
-from .grad_scaler import BaseGradScaler
+from colossalai.utils import clip_grad_norm_fp32, copy_tensor_parallel_attributes, multi_tensor_applier
+
 from ._utils import has_inf_or_nan, zero_gard_by_list
+from .grad_scaler import BaseGradScaler
 
 __all__ = ['FP16Optimizer']
 
@@ -41,7 +43,7 @@ def _multi_tensor_copy_this_to_that(this, that, overflow_buf=None):
 
 class FP16Optimizer(Optimizer):
     """Float16 optimizer for fp16 and bf16 data types.
-    
+
     Args:
         optimizer (torch.optim.Optimizer): base optimizer such as Adam or SGD
         grad_scaler (BaseGradScaler): grad scaler for gradient chose in

- [NFC] polish colossalai/amp/naive_amp/_fp16_optimizer.py code style