From bda70b4b6676359a9d87eabb6524aca16dc9c15f Mon Sep 17 00:00:00 2001
From: puck_WCR <46049915+WANG-CR@users.noreply.github.com>
Date: Mon, 16 May 2022 14:43:32 +0800
Subject: [PATCH] [NFC] polish colossalai/kernel/cuda_native/layer_norm.py code
 style (#980)

---
 colossalai/kernel/cuda_native/layer_norm.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/colossalai/kernel/cuda_native/layer_norm.py b/colossalai/kernel/cuda_native/layer_norm.py
index af66eb827..38e95e2f8 100644
--- a/colossalai/kernel/cuda_native/layer_norm.py
+++ b/colossalai/kernel/cuda_native/layer_norm.py
@@ -24,8 +24,8 @@ class FusedLayerNormAffineFunction(torch.autograd.Function):
         input_ = input.contiguous()
         weight_ = weight.contiguous()
         bias_ = bias.contiguous()
-        output, mean, invvar = colossal_layer_norm_cuda.forward_affine(
-            input_, ctx.normalized_shape, weight_, bias_, ctx.eps)
+        output, mean, invvar = colossal_layer_norm_cuda.forward_affine(input_, ctx.normalized_shape, weight_, bias_,
+                                                                       ctx.eps)
         ctx.save_for_backward(input_, weight_, bias_, mean, invvar)
 
         return output
@@ -72,8 +72,7 @@ class MixedFusedLayerNorm(torch.nn.Module):
 
     def forward(self, input):
 
-        return FusedLayerNormAffineFunction.apply(input, self.weight, self.bias,
-                                                  self.normalized_shape, self.eps)
+        return FusedLayerNormAffineFunction.apply(input, self.weight, self.bias, self.normalized_shape, self.eps)
 
     def __repr__(self):
         return f'MixedFusedLayerNorm(normalized_shape={self.normalized_shape}, eps={self.eps})'