update_book_commitid

doc/fluid/advanced_usage/development/new_op/new_op.md

@@ -120,7 +120,7 @@ $$Out = scale*X$$
 这个例子有`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。
 
 ### 定义GradProtoMaker类
-每个Op的必须有一个对应的GraProtoMaker，若未定制对应前向Op的GradProtoMaker，fluid提供了DefaultGradProtoMaker，默认注册会使用全部输入输出，包括Input, Output, Output@Grad等，使用不需要的变量的会造成显存浪费。
+每个Op的必须有一个对应的GradProtoMaker，若未定制对应前向Op的GradProtoMaker，fluid提供了DefaultGradProtoMaker，默认注册会使用全部输入输出，包括Input, Output, Output@Grad等，使用不需要的变量的会造成显存浪费。
 下面示例定义了ScaleOp的GradProtoMaker。
 
 ```cpp
@@ -230,7 +230,7 @@ Op的输入和输出可分别通过`ExecutionContext::Input<T>()`和`ExecutionCo
 
 `MulOp`的CPU、CUDA实现共享同一个`Kernel`。`OpKernel`不共享的例子可以参考：[`OnehotCrossEntropyOpKernel`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/cross_entropy_op.h#L43)。
 
-为了使`OpKernel`的计算过程书写更加简单，并且CPU、CUDA的代码可以复用，我们通常借助 Eigen unsupported Tensor模块来实现`Compute`接口。关于在PaddlePaddle中如何使用Eigen库，请参考[使用文档](https://github.com/PaddlePaddle/FluidDoc/blob/develop/doc/fluid/dev/use_eigen_cn.md)。
+为了使`OpKernel`的计算过程书写更加简单，并且CPU、CUDA的代码可以复用，我们通常借助 Eigen unsupported Tensor模块来实现`Compute`接口。关于在PaddlePaddle中如何使用Eigen库，请参考[使用文档](https://github.com/PaddlePaddle/FluidDoc/blob/release/1.2/doc/fluid/dev/use_eigen_cn.md)。
 
 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`**。

doc/fluid/advanced_usage/development/new_op/new_op_en.md

@@ -103,7 +103,7 @@ The equation is: Out = X * Y
 
 The constructor utilizes `AddInput` to add input parameter, `AddOutput` to add output parameter, and `AddComment` to add comments for the Op, so that the corresponding information will be added to `OpProto`.
 
-The code above adds two inputs `X` and `Y` to `MulOp`, an output `Out`, and their corresponding descriptions. Names are given in accordance to Paddle's [naming convention](https://github.com/PaddlePaddle/FluidDoc/blob/develop/doc/fluid/dev/name_convention.md).
+The code above adds two inputs `X` and `Y` to `MulOp`, an output `Out`, and their corresponding descriptions. Names are given in accordance to Paddle's [naming convention](https://github.com/PaddlePaddle/FluidDoc/blob/release/1.2/doc/fluid/dev/name_convention.md).
 
 
 An additional example [`ScaleOp`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/scale_op.cc#L38-L55) is implemented as follows:
@@ -134,7 +134,7 @@ Note `AddAttr<AttrType>("scale", "...").SetDefault(1.0);` adds `scale`constant a
 <a name="Defining the GradProtoMaker class"></a>
 ### Defining the GradProtoMaker class
 
-Each Op must have a corresponding GraProtoMaker. If GradProtoMaker corresponding to the forward Op is not customized, Fluid provides DefaultGradProtoMaker. The default registration will use all input and output, including Input, Output, Output@Grad and so on. Using unnecessary variables will cause waste of memory.
+Each Op must have a corresponding GradProtoMaker. If GradProtoMaker corresponding to the forward Op is not customized, Fluid provides DefaultGradProtoMaker. The default registration will use all input and output, including Input, Output, Output@Grad and so on. Using unnecessary variables will cause waste of memory.
 The following example defines ScaleOp's GradProtoMaker.
 
 ```cpp
@@ -244,7 +244,7 @@ Note that **different devices (CPU, CUDA)share one Op definition; whether or not
 
 `MulOp`'s CPU and CUDA share the same `Kernel`. A non-sharing  `OpKernel` example can be seen in [`OnehotCrossEntropyOpKernel`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/cross_entropy_op.cc).
 
-To ease the writing of `OpKernel` compute, and for reusing code cross-device, [`Eigen-unsupported Tensor`](https://bitbucket.org/eigen/eigen/src/default/unsupported/Eigen/CXX11/src/Tensor/README.md?fileviewer=file-view-default) module is used to implement `Compute` interface. To learn about how the Eigen library is used in PaddlePaddle, please see [usage document](https://github.com/PaddlePaddle/FluidDoc/blob/develop/doc/fluid/dev/use_eigen_en.md).
+To ease the writing of `OpKernel` compute, and for reusing code cross-device, [`Eigen-unsupported Tensor`](https://bitbucket.org/eigen/eigen/src/default/unsupported/Eigen/CXX11/src/Tensor/README.md?fileviewer=file-view-default) module is used to implement `Compute` interface. To learn about how the Eigen library is used in PaddlePaddle, please see [usage document](https://github.com/PaddlePaddle/FluidDoc/blob/release/1.2/doc/fluid/dev/use_eigen_cn.md).
 
 
 This concludes the forward implementation of an operator. Next its operation and kernel need to be registered in a `.cc` file.
@@ -460,7 +460,7 @@ If it is not necessary or concise description is enough to clearly express the a
 
 2.Using developer-defined variable abbreviations in error messages is not easy to understand.
 
-  Example of the problem:  
+  Example of the problem:
   ```
   PADDLE_ENFORCE(forward_pd != nullptr,
   "Fail to find eltwise_fwd_pd in device context"); //eltwise_fwd_pduser may not be understood
@@ -481,7 +481,7 @@ If it is not necessary or concise description is enough to clearly express the a
 
 
 <a name="Special instructions for OP InferShape check message"></a>
-#### Special Instructions for OP InferShape Check Message 
+#### Special Instructions for OP InferShape Check Message
 
 - Check input and output variables, please follow the following format
 `Input(variable name) of OP name operator should not be null.`

doc/fluid/user_guides/howto/configure_simple_model/index.rst

@@ -25,7 +25,7 @@
 | 优化算法       | 随机梯度下降                                 |
 +----------------+----------------------------------------------+
 
-使用PaddlePadle建模
+使用PaddlePaddle建模
 ###################
 
 从逻辑层面明确了输入数据格式、模型结构、损失函数以及优化算法后，需要使用PaddlePaddle提供的API及算子来实现模型逻辑。一个典型的模型主要包含4个部分，分别是：输入数据格式定义，模型前向计算逻辑，损失函数以及优化算法。