diff --git a/python/paddle/incubate/autograd/composite_rules.py b/python/paddle/incubate/autograd/composite_rules.py
index 9d0229627728d798bf555b8c64f1b758c03b8f04..ba92c5dba718dba14aab6903a4960af328495631 100644
--- a/python/paddle/incubate/autograd/composite_rules.py
+++ b/python/paddle/incubate/autograd/composite_rules.py
@@ -160,8 +160,8 @@ def layernorm_composite(x, scale, bias, epsilon, begin_norm_axis):
     var_tmp1 = difference * difference
     variance = mean(var_tmp1, axis=axis, keepdim=True)
     var_tmp3 = variance + epsilon
-    sqrt_var = sqrt(var_tmp3)
-    out = difference / sqrt_var
+    rsqrt_var = rsqrt(var_tmp3)
+    out = difference * rsqrt_var
 
     if scale is not None:
         scale = reshape(scale, x.shape[begin_norm_axis:])
diff --git a/python/paddle/incubate/autograd/primitives.py b/python/paddle/incubate/autograd/primitives.py
index cc8ba89423d7c86c3b131c1f60b98f51a560e207..9f52d9d69ac23354e5b77413a3139b5a01c95dcf 100644
--- a/python/paddle/incubate/autograd/primitives.py
+++ b/python/paddle/incubate/autograd/primitives.py
@@ -50,6 +50,7 @@ from paddle.tensor import ones  # noqa: F401
 from paddle.tensor import pow  # noqa: F401
 from paddle.tensor import prod  # noqa: F401
 from paddle.tensor import reshape  # noqa: F401
+from paddle.tensor import rsqrt  # noqa: F401
 from paddle.tensor import sign  # noqa: F401
 from paddle.tensor import sin  # noqa: F401
 from paddle.tensor import sinh  # noqa: F401
@@ -117,6 +118,7 @@ sub_prim = [
     'ones',
     'zeros',
     'sqrt',
+    'rsqrt',
 ]
 
 others = [