Fix/format (#4261)

* revise shardformer readme (#4246)

* [example] add llama pretraining (#4257)

* [NFC] polish colossalai/communication/p2p.py code style

---------
Co-authored-by: Jianghai <72591262+CjhHa1@users.noreply.github.com>
Co-authored-by: binmakeswell <binmakeswell@gmail.com>
Co-authored-by: Qianran Ma <qianranm@luchentech.com>

colossalai/communication/p2p.py

 #!/usr/bin/env python
 # -*- encoding: utf-8 -*-
 
+import operator
+from functools import reduce
 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 functools import reduce
-import operator
-from .utils import split_tensor_into_1d_equal_chunks, gather_split_1d_tensor
+
+from .utils import gather_split_1d_tensor, split_tensor_into_1d_equal_chunks
 
 TensorShape = Union[torch.Size, List[int], Tuple[int]]
 
@@ -260,7 +262,7 @@ def send_forward_recv_backward(output_tensor,
                                next_rank=None,
                                dtype=torch.float,
                                scatter_gather_tensors=False) -> Union[torch.Tensor, List[torch.Tensor]]:
-    """Batched communication operation. Sends the input tensor to the 
+    """Batched communication operation. Sends the input tensor to the
     next stage in pipeline, while receives the gradient tensor from the
     next stage in pipeline as the input gradient tensor of this stage.
 
@@ -319,7 +321,7 @@ def send_forward_recv_forward(output_tensor,
                               next_rank=None,
                               dtype=torch.float,
                               scatter_gather_tensors=False) -> Union[torch.Tensor, List[torch.Tensor]]:
-    """Batched communication operation. Sends the input tensor to the 
+    """Batched communication operation. Sends the input tensor to the
     next stage in pipeline, while receives the output tensor from the
     previous stage in pipeline as the input of this stage.