diff --git a/python/paddle/nn/layer/norm.py b/python/paddle/nn/layer/norm.py
index ff64b4dfd3de8c..6127f31103876b 100644
--- a/python/paddle/nn/layer/norm.py
+++ b/python/paddle/nn/layer/norm.py
@@ -609,7 +609,7 @@ class LayerNorm(Layer):
 
     Parameters:
         normalized_shape(int|list|tuple): Input shape from an expected input of
-            size :math:`[*, normalized_shape[0], normalized_shape[1], ..., normalized_shape[-1]]`.
+            size ``[*, normalized_shape[0], normalized_shape[1], ..., normalized_shape[-1]]`` .
             If it is a single integer, this module will normalize over the last dimension
             which is expected to be of that specific size.
         epsilon(float, optional): The small value added to the variance to prevent
@@ -627,7 +627,7 @@ class LayerNorm(Layer):
         - output: same shape as input x.
 
     Returns:
-        None
+        ``Tensor`` , the dimension is the same as :attr:`x`, but the internal values have been normalized by ``LayerNorm`` .
 
     Examples: