diff --git a/colossalai/communication/utils.py b/colossalai/communication/utils.py
index ef9eceea847d..1516df356278 100644
--- a/colossalai/communication/utils.py
+++ b/colossalai/communication/utils.py
@@ -1,10 +1,11 @@
+from typing import List, Tuple, Union
+
 import torch
 import torch.distributed as dist
 
 from colossalai.context.parallel_mode import ParallelMode
 from colossalai.core import global_context as gpc
 from colossalai.utils import get_current_device
-from typing import Union, List, Tuple
 
 TensorShape = Union[torch.Size, List[int], Tuple[int]]
 
diff --git a/colossalai/fx/profiler/experimental/profiler_module/embedding.py b/colossalai/fx/profiler/experimental/profiler_module/embedding.py
index dca6f9453af3..a1ade5d3ad93 100644
--- a/colossalai/fx/profiler/experimental/profiler_module/embedding.py
+++ b/colossalai/fx/profiler/experimental/profiler_module/embedding.py
@@ -1,5 +1,7 @@
 from typing import Tuple
+
 import torch
+
 from ..registry import meta_profiler_module
 
 
@@ -8,4 +10,4 @@ def torch_nn_embedding(self: torch.nn.Embedding, input: torch.Tensor) -> Tuple[i
     # nn.Embedding is a dictionary lookup, so technically it has 0 FLOPs. (https://discuss.pytorch.org/t/correct-way-to-calculate-flops-in-model/67198/6)
     flops = 0
     macs = 0
-    return flops, macs
\ No newline at end of file
+    return flops, macs