diff --git a/develop/doc_cn/_sources/howto/dev/new_op_cn.md.txt b/develop/doc_cn/_sources/howto/dev/new_op_cn.md.txt
index ebd2cf3ff04567e3f34b1707696d025b834c58eb..7f8da2da5a0d42ff065265c5d173d0e6167dc08a 100644
--- a/develop/doc_cn/_sources/howto/dev/new_op_cn.md.txt
+++ b/develop/doc_cn/_sources/howto/dev/new_op_cn.md.txt
@@ -5,12 +5,13 @@
    - [定义ProtoMaker类](#定义ProtoMaker类)
    - [定义Operator类](#定义Operator类)
    - [定义OpKernel类](#定义OpKernel类)
-   - [注册类](#注册类)
+   - [注册Operator](#注册Operator)
    - [编译](#编译)
  - [绑定Python](#绑定Python)
  - [实现单元测试](#实现单元测试)
    - [前向Operator单测](#前向Operator单测)
    - [反向Operator单测](#反向Operator单测)
+   - [编译和执行](#编译和执行)
 
 
 ## 概念简介
@@ -22,19 +23,17 @@
 - `framework::OperatorWithKernel`：继承自OperatorBase，Op有计算函数，称作有Kernel。
 - `class OpProtoAndCheckerMaker`：描述该Op的输入、输出、属性、注释,主要用于Python API接口生成
 
-依据是否包含kernel，将Op分为两种：包含Kernel的Op和不包含kernel的Op，前者Op的定义继承自`OperatorBase`，后者继承自`OperatorWithKernel`。本教程主要介绍带Kernel的Op如何写，简单总结如下：
+依据是否包含kernel，将Op分为两种：包含Kernel的Op和不包含kernel的Op，前者Op的定义继承自`OperatorBase`，后者继承自`OperatorWithKernel`。本教程主要介绍带Kernel的Op如何写，简单总结Op需要包含的内容如下：
 
-Forward Op需要包含：
-
-   - OpProtoMake定义
-   - Op定义
-   - Kernel实现
+  
+ 内容            | 定义位置         
+--------------  | :----------------------  
+OpProtoMake定义  | `.cc`文件，Backward Op不需要定义OpProtoMake
+Op定义           | `.cc`文件 
+Kernel实现       | CPU、GPU共享Kernel在`.h`文件，否则，CPU可以在`.cc`文件，GPU可在`.cu`文件。 
+注册Op           | Op注册在`.cc`文件；Kernel注册CPU在`.cc`文件，GPU在`.cu`文件
+     
      
-与之对应的Backward Op包含：
-
-   - Op定义
-   - Kernel实现
-
 下面以矩阵乘操作，即[MulOp](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/mul_op.cc)为例来介绍如何写带Kernel的Operator。
 
 
@@ -137,8 +136,9 @@ MulOp(const std::string &type, const framework::VariableNameMap &inputs,
 ```	
 	
 还需要重写`InferShape`接口。`InferShape`为const函数，不能修改Op的成员变量，参数为`const framework::InferShapeContext &ctx`，通过该参数可获取到输入输出以及属性。它的功能是：
-	 - 1). 做检查， 尽早报错：检查输入数据维度、类型等是否合法
-	 - 2). 设置输出Tensor的形状
+
+  - 1). 做检查， 尽早报错：检查输入数据维度、类型等是否合法。
+  - 2). 设置输出Tensor的形状。
 
 通常`OpProtoMaker`和`Op`类的定义写在`.cc`文件中，和要讲到的注册函数一起放在`.cc`中
 
@@ -172,7 +172,7 @@ class MulKernel : public framework::OpKernel {
    
 到此前向Op实现完成，需要在`.cc`文件中注册该op和kernel。反向Op类的定义和Kernel定义与前向Op类似，这里不再重复。但注意，反向Op没有`ProtoMaker`。
    
-### 4. 注册类
+### 4. 注册Operator
 
 在`.cc`文件中注册前向、反向Op类，注册CPU Kernel。
 
@@ -297,4 +297,28 @@ class TestMulOp(unittest.TestCase):
    - 调用`create_op("mul")`创建反向Op对应的前向Op。
    - 定义输入`inputs`。
    - 调用`compare_grad`函数对比CPU、GPU计算结果。
-   - 调用`check_grad`检查梯度稳定性。
+   - 调用`check_grad`检查梯度稳定性，这里采用数值法检测梯度正确性。
+      - 第一个参数`op` : 前向op。
+      - 第二个参数`inputs` : 输入词典，词典的Key和`ProtoMaker`定义保持一致。
+      - 第三个参数`set(["X", "Y"])` : 指定对输入变量`X`、`Y`做梯度检测。
+      - 第四个参数`"Out"` : 指定前向网络最终的输出目标变量`Out`
+
+
+### 编译和执行 
+
+单测完成之后，在[`python/paddle/v2/framework/tests/CMakeLists.txt`](https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/v2/framework/tests/CMakeLists.txt)里添加编译：
+
+```
+py_test(test_mul_op SRCS test_mul_op.py)
+```
+
+编译时需要打开`WITH_TESTING`, 即 `cmake paddle_dir -DWITH_TESTING=ON`，编译成功之后执行单测命令为：
+
+```
+make test ARGS="-R test_mul_op -V"
+```
+或者:
+
+```
+ctest -R test_mul_op
+```
diff --git a/develop/doc_cn/howto/dev/new_op_cn.html b/develop/doc_cn/howto/dev/new_op_cn.html
index 60fc51ae794832ba945f11a229304011d19e0017..6e8cafc695c4cc0106b97733759be69f5a0c7fa6 100644
--- a/develop/doc_cn/howto/dev/new_op_cn.html
+++ b/develop/doc_cn/howto/dev/new_op_cn.html
@@ -193,7 +193,7 @@
 <li><a class="reference external" href="#定义ProtoMaker类">定义ProtoMaker类</a></li>
 <li><a class="reference external" href="#定义Operator类">定义Operator类</a></li>
 <li><a class="reference external" href="#定义OpKernel类">定义OpKernel类</a></li>
-<li><a class="reference external" href="#注册类">注册类</a></li>
+<li><a class="reference external" href="#注册Operator">注册Operator</a></li>
 <li><a class="reference external" href="#编译">编译</a></li>
 </ul>
 </li>
@@ -201,6 +201,7 @@
 <li><a class="reference external" href="#实现单元测试">实现单元测试</a><ul>
 <li><a class="reference external" href="#前向Operator单测">前向Operator单测</a></li>
 <li><a class="reference external" href="#反向Operator单测">反向Operator单测</a></li>
+<li><a class="reference external" href="#编译和执行">编译和执行</a></li>
 </ul>
 </li>
 </ul>
@@ -213,18 +214,11 @@
 <li><code class="docutils literal"><span class="pre">framework::OperatorWithKernel</span></code>：继承自OperatorBase，Op有计算函数，称作有Kernel。</li>
 <li><code class="docutils literal"><span class="pre">class</span> <span class="pre">OpProtoAndCheckerMaker</span></code>：描述该Op的输入、输出、属性、注释,主要用于Python API接口生成</li>
 </ul>
-<p>依据是否包含kernel，将Op分为两种：包含Kernel的Op和不包含kernel的Op，前者Op的定义继承自<code class="docutils literal"><span class="pre">OperatorBase</span></code>，后者继承自<code class="docutils literal"><span class="pre">OperatorWithKernel</span></code>。本教程主要介绍带Kernel的Op如何写，简单总结如下：</p>
-<p>Forward Op需要包含：</p>
-<ul class="simple">
-<li>OpProtoMake定义</li>
-<li>Op定义</li>
-<li>Kernel实现</li>
-</ul>
-<p>与之对应的Backward Op包含：</p>
-<ul class="simple">
-<li>Op定义</li>
-<li>Kernel实现</li>
-</ul>
+<p>依据是否包含kernel，将Op分为两种：包含Kernel的Op和不包含kernel的Op，前者Op的定义继承自<code class="docutils literal"><span class="pre">OperatorBase</span></code>，后者继承自<code class="docutils literal"><span class="pre">OperatorWithKernel</span></code>。本教程主要介绍带Kernel的Op如何写，简单总结Op需要包含的内容如下：</p>
+<p>内容            | 定义位置&#8212;&#8212;&#8212;&#8212;&#8211;  | :&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;-OpProtoMake定义  | <code class="docutils literal"><span class="pre">.cc</span></code>文件，Backward Op不需要定义OpProtoMake
+Op定义           | <code class="docutils literal"><span class="pre">.cc</span></code>文件
+Kernel实现       | CPU、GPU共享Kernel在<code class="docutils literal"><span class="pre">.h</span></code>文件，否则，CPU可以在<code class="docutils literal"><span class="pre">.cc</span></code>文件，GPU可在<code class="docutils literal"><span class="pre">.cu</span></code>文件。
+注册Op           | Op注册在<code class="docutils literal"><span class="pre">.cc</span></code>文件；Kernel注册CPU在<code class="docutils literal"><span class="pre">.cc</span></code>文件，GPU在<code class="docutils literal"><span class="pre">.cu</span></code>文件</p>
 <p>下面以矩阵乘操作，即<a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/mul_op.cc">MulOp</a>为例来介绍如何写带Kernel的Operator。</p>
 </div>
 <div class="section" id="c">
@@ -311,9 +305,11 @@
   <span class="o">:</span> <span class="n">OperatorWithKernel</span><span class="p">(</span><span class="n">type</span><span class="p">,</span> <span class="n">inputs</span><span class="p">,</span> <span class="n">outputs</span><span class="p">,</span> <span class="n">attrs</span><span class="p">)</span> <span class="p">{}</span>
 </pre></div>
 </div>
-<p>还需要重写<code class="docutils literal"><span class="pre">InferShape</span></code>接口。<code class="docutils literal"><span class="pre">InferShape</span></code>为const函数，不能修改Op的成员变量，参数为<code class="docutils literal"><span class="pre">const</span> <span class="pre">framework::InferShapeContext</span> <span class="pre">&amp;ctx</span></code>，通过该参数可获取到输入输出以及属性。它的功能是：
-- 1). 做检查， 尽早报错：检查输入数据维度、类型等是否合法
-- 2). 设置输出Tensor的形状</p>
+<p>还需要重写<code class="docutils literal"><span class="pre">InferShape</span></code>接口。<code class="docutils literal"><span class="pre">InferShape</span></code>为const函数，不能修改Op的成员变量，参数为<code class="docutils literal"><span class="pre">const</span> <span class="pre">framework::InferShapeContext</span> <span class="pre">&amp;ctx</span></code>，通过该参数可获取到输入输出以及属性。它的功能是：</p>
+<ul class="simple">
+<li>1). 做检查， 尽早报错：检查输入数据维度、类型等是否合法。</li>
+<li>2). 设置输出Tensor的形状。</li>
+</ul>
 <p>通常<code class="docutils literal"><span class="pre">OpProtoMaker</span></code>和<code class="docutils literal"><span class="pre">Op</span></code>类的定义写在<code class="docutils literal"><span class="pre">.cc</span></code>文件中，和要讲到的注册函数一起放在<code class="docutils literal"><span class="pre">.cc</span></code>中</p>
 </div>
 <div class="section" id="opkernel">
@@ -342,8 +338,8 @@
 <p>注意，不同设备(CPU、GPU)共享一个Op定义，是否则共享同一个<code class="docutils literal"><span class="pre">OpKernel</span></code>，取决于<code class="docutils literal"><span class="pre">Compute</span></code>调用的函数是否支持不同设备。<code class="docutils literal"><span class="pre">MulOp</span></code>的CPU、GPU实现共享同一个<code class="docutils literal"><span class="pre">Kernel</span></code>，<code class="docutils literal"><span class="pre">OpKernel</span></code>不共享的例子可以参考<a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/cross_entropy_op.h#L43"><code class="docutils literal"><span class="pre">OnehotCrossEntropyOpKernel</span></code></a>。</p>
 <p>到此前向Op实现完成，需要在<code class="docutils literal"><span class="pre">.cc</span></code>文件中注册该op和kernel。反向Op类的定义和Kernel定义与前向Op类似，这里不再重复。但注意，反向Op没有<code class="docutils literal"><span class="pre">ProtoMaker</span></code>。</p>
 </div>
-<div class="section" id="">
-<span id="id3"></span><h3>4. 注册类<a class="headerlink" href="#" title="永久链接至标题">¶</a></h3>
+<div class="section" id="operator">
+<span id="id3"></span><h3>4. 注册Operator<a class="headerlink" href="#operator" title="永久链接至标题">¶</a></h3>
 <p>在<code class="docutils literal"><span class="pre">.cc</span></code>文件中注册前向、反向Op类，注册CPU Kernel。</p>
 <div class="highlight-c++"><div class="highlight"><pre><span></span><span class="k">namespace</span> <span class="n">ops</span> <span class="o">=</span> <span class="n">paddle</span><span class="o">::</span><span class="n">operators</span><span class="p">;</span>
 <span class="n">REGISTER_OP</span><span class="p">(</span><span class="n">mul</span><span class="p">,</span> <span class="n">ops</span><span class="o">::</span><span class="n">MulOp</span><span class="p">,</span> <span class="n">ops</span><span class="o">::</span><span class="n">MulOpMaker</span><span class="p">,</span> <span class="n">mul_grad</span><span class="p">,</span> <span class="n">ops</span><span class="o">::</span><span class="n">MulOpGrad</span><span class="p">);</span>
@@ -457,9 +453,30 @@
 <li>调用<code class="docutils literal"><span class="pre">create_op(&quot;mul&quot;)</span></code>创建反向Op对应的前向Op。</li>
 <li>定义输入<code class="docutils literal"><span class="pre">inputs</span></code>。</li>
 <li>调用<code class="docutils literal"><span class="pre">compare_grad</span></code>函数对比CPU、GPU计算结果。</li>
-<li>调用<code class="docutils literal"><span class="pre">check_grad</span></code>检查梯度稳定性。</li>
+<li>调用<code class="docutils literal"><span class="pre">check_grad</span></code>检查梯度稳定性，这里采用数值法检测梯度正确性。<ul>
+<li>第一个参数<code class="docutils literal"><span class="pre">op</span></code> : 前向op。</li>
+<li>第二个参数<code class="docutils literal"><span class="pre">inputs</span></code> : 输入词典，词典的Key和<code class="docutils literal"><span class="pre">ProtoMaker</span></code>定义保持一致。</li>
+<li>第三个参数<code class="docutils literal"><span class="pre">set([&quot;X&quot;,</span> <span class="pre">&quot;Y&quot;])</span></code> : 指定对输入变量<code class="docutils literal"><span class="pre">X</span></code>、<code class="docutils literal"><span class="pre">Y</span></code>做梯度检测。</li>
+<li>第四个参数<code class="docutils literal"><span class="pre">&quot;Out&quot;</span></code> : 指定前向网络最终的输出目标变量<code class="docutils literal"><span class="pre">Out</span></code></li>
+</ul>
+</li>
 </ul>
 </div>
+<div class="section" id="">
+<span id="id8"></span><h3>编译和执行<a class="headerlink" href="#" title="永久链接至标题">¶</a></h3>
+<p>单测完成之后，在<a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/v2/framework/tests/CMakeLists.txt"><code class="docutils literal"><span class="pre">python/paddle/v2/framework/tests/CMakeLists.txt</span></code></a>里添加编译：</p>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">py_test</span><span class="p">(</span><span class="n">test_mul_op</span> <span class="n">SRCS</span> <span class="n">test_mul_op</span><span class="o">.</span><span class="n">py</span><span class="p">)</span>
+</pre></div>
+</div>
+<p>编译时需要打开<code class="docutils literal"><span class="pre">WITH_TESTING</span></code>, 即 <code class="docutils literal"><span class="pre">cmake</span> <span class="pre">paddle_dir</span> <span class="pre">-DWITH_TESTING=ON</span></code>，编译成功之后执行单测命令为：</p>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">make</span> <span class="n">test</span> <span class="n">ARGS</span><span class="o">=</span><span class="s2">&quot;-R test_mul_op -V&quot;</span>
+</pre></div>
+</div>
+<p>或者:</p>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">ctest</span> <span class="o">-</span><span class="n">R</span> <span class="n">test_mul_op</span>
+</pre></div>
+</div>
+</div>
 </div>
 </div>
 
diff --git a/develop/doc_cn/searchindex.js b/develop/doc_cn/searchindex.js
index d5e637c4614bfc33aeb1969baba67696fa563e37..4ed2c76785ec308b7a0e71f7acd47828c712a5f8 100644
--- a/develop/doc_cn/searchindex.js
+++ b/develop/doc_cn/searchindex.js
@@ -1 +1 @@
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