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7 changed file
--- a/develop/doc/_sources/howto/dev/new_op_en.md.txt
+++ b/develop/doc/_sources/howto/dev/new_op_en.md.txt
 # How to write a new operator

 - [Background](#background)
- - [Implementing C++ Types](#implementing-c++-types)
-   - [Defining ProtoMaker](#defining-protoMaker)
+ - [Implementing C++ Types](#implementing-c-types)
+   - [Defining ProtoMaker](#defining-protomaker)
   - [Defining Operator](#defining-operator)
   - [Registering Operator](#registering-operator)
   - [Compilation](#compilation)
@@ -41,7 +41,7 @@ Let's take matrix multiplication operator, [MulOp](https://github.com/PaddlePadd
 ## Implementing C++ Types


-### 1. Defining Class ProtoMaker
+### Defining ProtoMaker

 Matrix Multiplication can be written as $Out = X * Y$, meaning that the operation consists of two inputs and pne output.

@@ -98,7 +98,7 @@ There are two changes in this example:
 - `AddAttr<AttrType>("scale", "...").SetDefault(1.0);`  adds `scale`constant as an attribute, and sets the default value to 1.0.


-### 2. Defining Operator
+### Defining Operator

 The following code defines the interface for MulOp:

@@ -147,7 +147,7 @@ MulOp(const std::string &type, const framework::VariableNameMap &inputs,

 Usually `OpProtoMaker` and `Op`'s type definitions are written in `.cc` files, which also include the registration methods introduced later.

-### 3. Defining OpKernel
+### Defining OpKernel

 `MulKernel` inherits `framework::OpKernel`, which includes the following templates:

@@ -188,7 +188,7 @@ This concludes the forward implementation of an operator. Next its operation and

 The definition of its corresponding backward operator, if applicable, is similar to that of an forward operator. **Note that a backward operator does not include a `ProtoMaker`**.

-### 4. Registering Operator
+### Registering Operator

 - In `.cc` files, register forward and backward operator classes and the CPU kernel.

@@ -220,7 +220,7 @@ The definition of its corresponding backward operator, if applicable, is similar
                           ops::MulGradKernel<paddle::platform::CUDADeviceContext, float>);
    ```

-### 5. Compilation
+### Compilation

 Run the following commands to compile.

@@ -284,8 +284,7 @@ A forward operator unit test inherits `unittest.TestCase` and defines metaclass
      def test_check_grad_ingore_y(self):
          self.check_grad(
              ['X'], 'Out', max_relative_error=0.5, no_grad_set=set('Y'))
-
-    ```
+  ```
 Get its output, and compare it with the forward operator's own output.

 The code above first loads required packages. In addition, we have
@@ -294,6 +293,8 @@ The code above first loads required packages. In addition, we have
 - `self.inputs` defines input, with type `numpy.array` and initializes it.
 - `self.outputs` defines output and completes the same operator computation in the Python script, and returns its result from the Python script.

+### Testing Backward Operators
+
 Some key points in checking gradient above include:

 - `test_normal` calls `check_grad` to validate scaling tests' correctness and stability through numeric methods.

--- a/develop/doc/howto/dev/new_op_en.html
+++ b/develop/doc/howto/dev/new_op_en.html
@@ -207,8 +207,8 @@
 <span id="how-to-write-a-new-operator"></span><h1>How to write a new operator<a class="headerlink" href="#how-to-write-a-new-operator" title="Permalink to this headline">¶</a></h1>
 <ul class="simple">
 <li><a class="reference external" href="#background">Background</a></li>
-<li><a class="reference external" href="#implementing-c++-types">Implementing C++ Types</a><ul>
-<li><a class="reference external" href="#defining-protoMaker">Defining ProtoMaker</a></li>
+<li><a class="reference external" href="#implementing-c-types">Implementing C++ Types</a><ul>
+<li><a class="reference external" href="#defining-protomaker">Defining ProtoMaker</a></li>
 <li><a class="reference external" href="#defining-operator">Defining Operator</a></li>
 <li><a class="reference external" href="#registering-operator">Registering Operator</a></li>
 <li><a class="reference external" href="#compilation">Compilation</a></li>
@@ -244,8 +244,8 @@ Registering the Op           | Ops are registered in <code class="docutils liter
 </div>
 <div class="section" id="implementing-c-types">
 <span id="implementing-c-types"></span><h2>Implementing C++ Types<a class="headerlink" href="#implementing-c-types" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="defining-class-protomaker">
-<span id="defining-class-protomaker"></span><h3>1. Defining Class ProtoMaker<a class="headerlink" href="#defining-class-protomaker" title="Permalink to this headline">¶</a></h3>
+<div class="section" id="defining-protomaker">
+<span id="defining-protomaker"></span><h3>Defining ProtoMaker<a class="headerlink" href="#defining-protomaker" title="Permalink to this headline">¶</a></h3>
 <p>Matrix Multiplication can be written as $Out = X * Y$, meaning that the operation consists of two inputs and pne output.</p>
 <p>First, define <code class="docutils literal"><span class="pre">ProtoMaker</span></code> to describe the Operator&#8217;s input, output, and additional comments:</p>
 <div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">MulOpMaker</span> <span class="o">:</span> <span class="k">public</span> <span class="n">framework</span><span class="o">::</span><span class="n">OpProtoAndCheckerMaker</span> <span class="p">{</span>
@@ -293,7 +293,7 @@ Registering the Op           | Ops are registered in <code class="docutils liter
 </ul>
 </div>
 <div class="section" id="defining-operator">
-<span id="defining-operator"></span><h3>2. Defining Operator<a class="headerlink" href="#defining-operator" title="Permalink to this headline">¶</a></h3>
+<span id="defining-operator"></span><h3>Defining Operator<a class="headerlink" href="#defining-operator" title="Permalink to this headline">¶</a></h3>
 <p>The following code defines the interface for MulOp:</p>
 <div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">MulOp</span> <span class="o">:</span> <span class="k">public</span> <span class="n">framework</span><span class="o">::</span><span class="n">OperatorWithKernel</span> <span class="p">{</span>
 <span class="k">public</span><span class="o">:</span>
@@ -336,7 +336,7 @@ Registering the Op           | Ops are registered in <code class="docutils liter
 <p>Usually <code class="docutils literal"><span class="pre">OpProtoMaker</span></code> and <code class="docutils literal"><span class="pre">Op</span></code>&#8216;s type definitions are written in <code class="docutils literal"><span class="pre">.cc</span></code> files, which also include the registration methods introduced later.</p>
 </div>
 <div class="section" id="defining-opkernel">
-<span id="defining-opkernel"></span><h3>3. Defining OpKernel<a class="headerlink" href="#defining-opkernel" title="Permalink to this headline">¶</a></h3>
+<span id="defining-opkernel"></span><h3>Defining OpKernel<a class="headerlink" href="#defining-opkernel" title="Permalink to this headline">¶</a></h3>
 <p><code class="docutils literal"><span class="pre">MulKernel</span></code> inherits <code class="docutils literal"><span class="pre">framework::OpKernel</span></code>, which includes the following templates:</p>
 <ul class="simple">
 <li><code class="docutils literal"><span class="pre">typename</span> <span class="pre">DeviceContext</span></code> denotes device context type. When different devices, namely the CPUDeviceContext and the CUDADeviceContext, share the same kernel, this template needs to be added. If they don&#8217;t share kernels, this must not be added. An example of a non-sharing kernel is <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>.</li>
@@ -370,7 +370,7 @@ Registering the Op           | Ops are registered in <code class="docutils liter
 <p>The definition of its corresponding backward operator, if applicable, is similar to that of an forward operator. <strong>Note that a backward operator does not include a <code class="docutils literal"><span class="pre">ProtoMaker</span></code></strong>.</p>
 </div>
 <div class="section" id="registering-operator">
-<span id="registering-operator"></span><h3>4. Registering Operator<a class="headerlink" href="#registering-operator" title="Permalink to this headline">¶</a></h3>
+<span id="registering-operator"></span><h3>Registering Operator<a class="headerlink" href="#registering-operator" title="Permalink to this headline">¶</a></h3>
 <ul>
 <li><p class="first">In <code class="docutils literal"><span class="pre">.cc</span></code> files, register forward and backward operator classes and the CPU kernel.</p>
 <div class="highlight-cpp"><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>
@@ -406,7 +406,7 @@ Registering the Op           | Ops are registered in <code class="docutils liter
 </ul>
 </div>
 <div class="section" id="compilation">
-<span id="compilation"></span><h3>5. Compilation<a class="headerlink" href="#compilation" title="Permalink to this headline">¶</a></h3>
+<span id="compilation"></span><h3>Compilation<a class="headerlink" href="#compilation" title="Permalink to this headline">¶</a></h3>
 <p>Run the following commands to compile.</p>
 <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">make</span> <span class="n">mul_op</span>
 </pre></div>
@@ -462,7 +462,6 @@ Registering the Op           | Ops are registered in <code class="docutils liter
    <span class="k">def</span> <span class="nf">test_check_grad_ingore_y</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_grad</span><span class="p">(</span>
            <span class="p">[</span><span class="s1">&#39;X&#39;</span><span class="p">],</span> <span class="s1">&#39;Out&#39;</span><span class="p">,</span> <span class="n">max_relative_error</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">no_grad_set</span><span class="o">=</span><span class="nb">set</span><span class="p">(</span><span class="s1">&#39;Y&#39;</span><span class="p">))</span>
-
 </pre></div>
 </div>
 <p>Get its output, and compare it with the forward operator&#8217;s own output.</p>
@@ -472,6 +471,9 @@ Registering the Op           | Ops are registered in <code class="docutils liter
 <li><code class="docutils literal"><span class="pre">self.inputs</span></code> defines input, with type <code class="docutils literal"><span class="pre">numpy.array</span></code> and initializes it.</li>
 <li><code class="docutils literal"><span class="pre">self.outputs</span></code> defines output and completes the same operator computation in the Python script, and returns its result from the Python script.</li>
 </ul>
+</div>
+<div class="section" id="testing-backward-operators">
+<span id="testing-backward-operators"></span><h3>Testing Backward Operators<a class="headerlink" href="#testing-backward-operators" title="Permalink to this headline">¶</a></h3>
 <p>Some key points in checking gradient above include:</p>
 <ul class="simple">
 <li><code class="docutils literal"><span class="pre">test_normal</span></code> calls <code class="docutils literal"><span class="pre">check_grad</span></code> to validate scaling tests&#8217; correctness and stability through numeric methods.<ul>

--- a/develop/doc/operators.json
+++ b/develop/doc/operators.json
--- a/develop/doc/searchindex.js
+++ b/develop/doc/searchindex.js
--- a/develop/doc_cn/_sources/howto/dev/new_op_cn.md.txt
+++ b/develop/doc_cn/_sources/howto/dev/new_op_cn.md.txt
 # 如何写新的Operator

 - [概念简介](#概念简介)
- - [实现C++类](#实现C++类)
-   - [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Operator](#注册Operator)
+ - [实现C++类](#实现c类)
+   - [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Operator](#注册operator)
   - [编译](#编译)
- - [绑定Python](#绑定Python)
+ - [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)
+   - [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)
+ - [注意事项](#注意事项)


 ## 概念简介
@@ -43,7 +44,7 @@ Kernel实现       | CPU、CUDA共享Kernel实现在`.h`文件中，否则，CPU
 ## 实现C++类


-### 1. 定义ProtoMaker类
+### 定义ProtoMaker类

 矩阵乘法的公式：$Out = X * Y$, 可见该计算由两个输入，一个输出组成。

@@ -100,7 +101,7 @@ The equation is: Out = scale*X
 - `AddAttr<AttrType>("scale", "...").SetDefault(1.0);` : 增加`scale`系数，作为参数属性，并且设置默认值为1.0。


-### 2. 定义Operator类
+### 定义Operator类

 下面的点实现了MulOp的定义：

@@ -149,7 +150,7 @@ MulOp(const std::string &type, const framework::VariableNameMap &inputs,

 通常`OpProtoMaker`和`Op`类的定义写在`.cc`文件中，和下面将要介绍的注册函数一起放在`.cc`中

-### 3. 定义OpKernel类
+### 定义OpKernel类

 `MulKernel`继承自`framework::OpKernel`，带有下面两个模板参数:

@@ -177,6 +178,7 @@ MulOp(const std::string &type, const framework::VariableNameMap &inputs,
    math::matmul<DeviceContext, T>(*X, false, *Y, false, 1, Z, 0, device_context);
  }
  };
+  ```

 需要注意：**不同设备(CPU、CUDA)共享一个Op定义，是否则共享同一个`OpKernel`，取决于`Compute`调用的函数是否支持不同设备。**

@@ -188,7 +190,7 @@ MulOp(const std::string &type, const framework::VariableNameMap &inputs,
 到此，前向Op实现完成。接下来，需要在`.cc`文件中注册该op和kernel。
 反向Op类的定义，反向OpKernel的定义与前向Op类似，这里不再赘述。**但需注意反向Op没有`ProtoMaker`**。

-### 4. 注册Operator
+### 注册Operator

 - 在`.cc`文件中注册前向、反向Op类，注册CPU Kernel。

@@ -220,7 +222,7 @@ MulOp(const std::string &type, const framework::VariableNameMap &inputs,
                           ops::MulGradKernel<paddle::platform::CUDADeviceContext, float>);
    ```

-### 5. 编译
+### 编译

 运行下面命令可以进行编译：

@@ -236,6 +238,7 @@ make mul_op

 单测包括对比前向Op不同设备(CPU、CUDA)的实现、对比反向OP不同设备(CPU、CUDA)的实现、反向Op的梯度测试。下面介绍介绍[`MulOp`的单元测试](https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/v2/framework/tests/test_mul_op.py)。

+### 前向Operator单测

 Op单元测试继承自`OpTest`。各项更加具体的单元测试在`TestMulOp`里完成。测试Operator，需要：

@@ -273,8 +276,7 @@ Op单元测试继承自`OpTest`。各项更加具体的单元测试在`TestMulOp
      def test_check_grad_ingore_y(self):
          self.check_grad(
              ['X'], 'Out', max_relative_error=0.5, no_grad_set=set('Y'))
-
-    ```
+  ```

 上面的代码首先导入依赖的包，下面是对`setUp`函数中操作的重要变量的详细解释：

@@ -282,6 +284,8 @@ Op单元测试继承自`OpTest`。各项更加具体的单元测试在`TestMulOp
 - `self.inputs` : 定义输入，类型为`numpy.array`，并初始化。
 - `self.outputs` : 定义输出，并在Python脚本中完成与operator同样的计算逻辑，返回Python端的计算结果。

+### 反向operator单测
+
 而反向测试中：
 - `test_check_grad_normal`中调用`check_grad`使用数值法检测梯度正确性和稳定性。
  - 第一个参数`["X", "Y"]` : 指定对输入变量`X`、`Y`做梯度检测。
@@ -290,7 +294,7 @@ Op单元测试继承自`OpTest`。各项更加具体的单元测试在`TestMulOp
 - `test_check_grad_ingore_x`和`test_check_grad_ingore_y`分支用来测试只需要计算一个输入梯度的情况。


-### 编译和执行单元测试
+### 编译和执行

 `python/paddle/v2/framework/tests` 目录下新增的 `test_*.py` 单元测试会被自动加入工程进行编译。


--- a/develop/doc_cn/howto/dev/new_op_cn.html
+++ b/develop/doc_cn/howto/dev/new_op_cn.html
--- a/develop/doc_cn/searchindex.js
+++ b/develop/doc_cn/searchindex.js