diff --git a/mindspore/common/initializer.py b/mindspore/common/initializer.py
index d46fa14118..1da5764510 100644
--- a/mindspore/common/initializer.py
+++ b/mindspore/common/initializer.py
@@ -268,10 +268,10 @@ class XavierUniform(Initializer):
     Initialize the array with xavier uniform algorithm, and from a uniform distribution collect samples within
     U[-boundary, boundary] The boundary is defined as :
 
-                    math:`boundary = gain * \sqrt{\frac{6}{n_{in} + n_{out}}}`.
+                    where :math:`boundary = gain * \sqrt{\frac{6}{n_{in} + n_{out}}}`.
 
-    math:`n_{in}` is the number of input units in the weight tensor.
-    math:`n_{out}` is the number of output units in the weight tensor.
+    where :math:`n_{in}` is the number of input units in the weight tensor.
+    where :math:`n_{out}` is the number of output units in the weight tensor.
 
     Args:
         gain (Array): The array to be assigned. Default: 1.
@@ -298,9 +298,9 @@ class HeUniform(Initializer):
     Initialize the array with He kaiming uniform algorithm, and from a uniform distribution collect samples within
     U[-boundary, boundary] The boundary is defined as :
 
-                    math:`boundary = \sqrt{\frac{6}{n_{in}}}`
+                    where :math:`boundary = \sqrt{\frac{6}{n_{in}}}`.
 
-    math:`n_{in}` is the number of input units in the weight tensor.
+    where :math:`n_{in}` is the number of input units in the weight tensor.
 
     Args:
         arr (Array): The array to be assigned.