[format] applied code formatting on changed files in pull request 4908 (#4918)

Co-authored-by: github-actions <github-actions@github.com>

applications/Colossal-LLaMA-2/colossal_llama2/utils/flash_attention_patch.py

@@ -6,25 +6,20 @@ from typing import Optional, Tuple
 
 import torch
 import torch.nn.functional as F
+from einops import rearrange
+from flash_attn.bert_padding import pad_input, unpad_input
+from flash_attn.flash_attn_interface import flash_attn_func, flash_attn_varlen_kvpacked_func
+from flash_attn.ops.rms_norm import rms_norm
 from transformers.models.llama.modeling_llama import (
-    LlamaRMSNorm,
     LlamaAttention,
-    LlamaModel,
     LlamaForCausalLM,
+    LlamaModel,
+    LlamaRMSNorm,
     apply_rotary_pos_emb,
     repeat_kv,
 )
 
 from colossalai.logging import get_dist_logger
-from einops import rearrange
-
-from flash_attn.bert_padding import pad_input, unpad_input
-from flash_attn.flash_attn_interface import (
-    flash_attn_func,
-    flash_attn_varlen_kvpacked_func,
-)
-from flash_attn.ops.rms_norm import rms_norm
-
 
 logger = get_dist_logger()
 
@@ -65,7 +60,7 @@ def attention_forward(
     past_key_value: Optional[Tuple[torch.Tensor]] = None,
     output_attentions: bool = False,
     use_cache: bool = False,
-    **kwargs
+    **kwargs,
 ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
     """
     Re-define LLaMA-2 `LlamaAttention` forward method using flash-attention.