diff --git a/paddle/framework/backward.md b/paddle/framework/backward.md
index 74c001b06a..c8fa3fefe5 100644
--- a/paddle/framework/backward.md
+++ b/paddle/framework/backward.md
@@ -21,18 +21,32 @@ grad_op_builder(fengjiayi)
given a forward network, it generates the backward network. We only care about the Gradients—`OutputGradients`,`InputGradients`.
-1. bla bla bla (yuyang)
+1. Op
+
+ when the input forward network is a Op, return its gradient Operator Immediately.
2. NetOp
- when the input forward network is a NetOp, it need to call the sub NetOp/Operators backward function recursively and ensure them done. During the process, we need to collect the `OutputGradients` name.
+ when the input forward network is a NetOp, it need to call the sub NetOp/Operators backward function recursively. During the process, we need to collect the `OutputGradients` name according to forward NetOp.
+
+ **shared variable**. As illustrated in the pictures, two operator's `Output` `Gradient` will overwirte their shared input variable.
+
+
+ 
+
+ 1. shared variable in two operators.
+
+
+
+ Share variable between operators or same input variable used in multiple operators lead to a duplicate gradient variable. As demo show above, we need to rename gradient name recursively, and add a generic add operator replace the overwirte links.
+
+
+ 
- We share variable in the same scope, as a result, duplicate operator `OutputGradients` will overwirte then duplicate variable.
+ 2. replace shared variable gradient with `Add` Operator
- ![./images/duplicate_op]()
+
- Share variable between operators or same input variable used in multiple operators lead to a duplicate gradient variable. As demo show above, we need to rename gradient name recursively, and add a generic add operator instead.
-![./images/duplicate_op2]()
- Then collect the sub graph OutputGradients/InputGradients as the NetOp's and return it.
+ Then collect the sub graph `OutputGradients`/`InputGradients` as the NetOp's and return it.