"update img alt"

paddle/framework/backward.md

@@ -60,7 +60,7 @@ A backward network is a series of backward operators. The main idea of building
 
 1. Op 
 
-   when the input forward network is an Op, return its gradient Operator Immediately. If all of its outputs are in no gradient set, then return a special `NOP`.
+   When the input forward network is an Op, return its gradient Operator Immediately. If all of its outputs are in no gradient set, then return a special `NOP`.
 
 2. NetOp 
 
@@ -72,12 +72,12 @@ A backward network is a series of backward operators. The main idea of building
 
 4. Sharing Variables
 
-   **sharing variables**. As illustrated in the pictures, two operator's `Output` `Gradient` will overwrite their sharing input variable.  
+   **sharing variables**. As illustrated in the pictures, two operator's share the same variable name of W@GRAD, which will overwrite their sharing input variable. 
 
 <p align="center">
-<img src="./images/duplicate_op.png" width="50%" ><br/>
+<img src="./images/duplicate_op.png" alt="Sharing variables in operators." width="50%"><br/>
 
-​	pic 1. Sharing variables in operators. 
+​	pic 1. 
 
 </p>