Update the README of how to benchmark Paddle on Android and add the Chinese version

benchmark/tool/C/README.md

@@ -7,45 +7,69 @@ The demo can be run from the command line and can be used to test the inference
 ## Android
 To compile and run this demo in an Android environment, please follow the following steps:
 
-1. Refer to [this document](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_android_en.md) to compile the Android version of PaddlePaddle. After following the mentioned steps, make install will generate an output directory containing three subdirectories: include, lib, and third_party( `libpaddle_capi_shared.so` will be produced in the `lib` directory).
+- **Step 1, build PaddlePaddle for Android.**
+
+  Refer to [this document](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_android_en.md) to compile the Android version of PaddlePaddle. After following the mentioned steps, make install will generate an output directory containing three subdirectories: include, lib, and third_party( `libpaddle_capi_shared.so` will be produced in the `lib` directory).
+
+- **Step 2, build the inference demo.**
+
+  Compile `inference.cc` to an executable program for the Android environment as follows:
 
-2. Compile `inference.cc` to an executable program for the Android environment as follows (run in `Mobile/benchmark/tool/C`):
     - For armeabi-v7a
-    ```
-    mkdir build
-    cd build
 
-    cmake .. \
-    -DANDROID_ABI=armeabi-v7a \
-    -DANDROID_STANDALONE_TOOLCHAIN=your/path/to/arm_standalone_toolchain \
-    -DPADDLE_ROOT=The output path generated in the first step \
-    -DCMAKE_BUILD_TYPE=MinSizeRel
+    ```bash
+    $ git clone https://github.com/PaddlePaddle/Mobile.git
+    $ cd Mobile/benchmark/tool/C/
+    $ mkdir build
+    $ cd build
+
+    $ cmake .. \
+            -DANDROID_ABI=armeabi-v7a \
+            -DANDROID_STANDALONE_TOOLCHAIN=your/path/to/arm_standalone_toolchain \
+            -DPADDLE_ROOT=The output path generated in the first step \
+            -DCMAKE_BUILD_TYPE=MinSizeRel
 
-    make
+    $ make
     ```
+
     - For arm64-v8a
-    ```
-    mkdir build
-    cd build
 
-    cmake .. \
-    -DANDROID_ABI=arm64-v8a \
-    -DANDROID_STANDALONE_TOOLCHAIN=your/path/to/arm64_standalone_toolchain \
-    -DPADDLE_ROOT=The output path generated in the first step \
-    -DCMAKE_BUILD_TYPE=MinSizeRel
+    ```bash
+    $ git clone https://github.com/PaddlePaddle/Mobile.git
+    $ cd Mobile/benchmark/tool/C/
+    $ mkdir build
+    $ cd build
+
+    $ cmake .. \
+            -DANDROID_ABI=arm64-v8a \
+            -DANDROID_STANDALONE_TOOLCHAIN=your/path/to/arm64_standalone_toolchain \
+            -DPADDLE_ROOT=The output path generated in the first step \
+            -DCMAKE_BUILD_TYPE=MinSizeRel
 
-    make
+    $ make
     ```
 
-3. Prepare a merged model:   
-Models config(.py) (eg: [Mobilenet](https://github.com/PaddlePaddle/Mobile/blob/develop/models/mobilenet.py)) contain only the structure of our models. A developer can choose [model config here](https://github.com/PaddlePaddle/Mobile/tree/develop/models) to train their custom models. PaddlePaddle documentation has [several tutorials](https://github.com/PaddlePaddle/models) for building and training models. The model parameter file(.tar.gz) will be generated during the training process. There we need to merge the configuration file(.py) and the parameter file(.tar.gz) into a file. Please refer to the [details.](https://github.com/PaddlePaddle/Mobile/tree/develop/tools/merge_config_parameters)
+- **Step 3, prepare a merged model.**
+
+  Models config(.py) (eg: [Mobilenet](https://github.com/PaddlePaddle/Mobile/blob/develop/models/mobilenet.py)) contain only the structure of our models. A developer can choose [model config here](https://github.com/PaddlePaddle/Mobile/tree/develop/models) to train their custom models. PaddlePaddle documentation has [several tutorials](https://github.com/PaddlePaddle/models) for building and training models. The model parameter file(.tar.gz) will be generated during the training process. There we need to merge the configuration file(.py) and the parameter file(.tar.gz) into a file. Please refer to the [details.](https://github.com/PaddlePaddle/Mobile/tree/develop/tools/merge_config_parameters)
 
-4. Run the demo program by logging into the Android environment via [adb](https://developer.android.google.cn/studio/command-line/adb.html?hl=zh-cn#Enabling) and specifying the PaddlePaddle model from the command line as follows:
-	```
-	adb push inference mobilenet.paddle /sdcard/test_mobilenet
-	adb shell
-	cd /sdcard/test_mobilenet
-	./inference --merged_model ./mobilenet.paddle --input_size 150528
-	```
+- **Step 4, run the demo.**
+
+  Users can run the demo program by logging into the Android environment via [adb](https://developer.android.google.cn/studio/command-line/adb.html?hl=zh-cn#Enabling) and specifying the PaddlePaddle model from the command line as follows:
+
+    ```bash
+    $ adb push inference /data/local/tmp # transfer the executable to Android's memory
+    $ adb push mobilenet_flowers102.paddle /data/local/tmp # transfer the model to Android's memory
+    $ adb shell # login Android device
+    odin:/ $ cd /data/local/tmp # switch to the working directory
+    odin:/data/local/tmp $ ls
+    inference  mobilenet_flowers102.paddle
+    odin:/data/local/tmp $ chmod +x inference
+    odin:/data/local/tmp $ ./inference --merged_model ./mobilenet_flowers102.paddle --input_size 150528 # run the executable
+    I1211 17:12:53.334666  4858 Util.cpp:166] commandline:
+    Time of init paddle 3.4388 ms.
+    Time of create from merged model file 141.045 ms.
+    Time of forward time 398.818 ms.
+    ```
 
-	**Note:** `input_size` is 150528, cause that the input size of the model is `3 * 224 * 224 = 150528`
+    **Note:** `input_size` is 150528, cause that the input size of the model is `3 * 224 * 224 = 150528`

benchmark/tool/C/README_cn.md

@@ -0,0 +1,111 @@
+# 示例程序
+
+这是一个用C++语言编写的简单的示例程序，其中通过调用Paddle的C-API接口，实现对模型的推断。
+
+这个示例程序可在linux或Android手机的命令行下运行，可以用来测试不同模型的性能。
+
+## Android
+用户可按照以下几个步骤，编译出在Android设备上执行的可执行程序。
+
+- **Step 1，编译Android平台上适用的PaddlePaddle库。**
+
+    用户需要按照[Android平台编译指南](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_android_cn.md)，编译Android平台上适用的PaddlePaddle库。在执行`make install`之后，PaddlePaddle库将会安装在`CMAKE_INSTALL_PREFIX`所指定的目录下。该目录包含如下几个子目录：
+    - `include`，其中包含使用PaddlePaddle所需要引入的头文件，通常代码中加入`#include <paddle/capi.h>`即可。
+    - `lib`，其中包含了PaddlePaddle对应架构的库文件。其中包括：
+      - 动态库，`libpaddle_capi_shared.so`。
+      - 静态库，`libpaddle_capi_layers.a`和`libpaddle_capi_engine.a`。
+    - `third_party`，PaddlePaddle所依赖的第三方库。
+
+- **Step 2，编译示例程序。**
+
+    示例程序项目使用CMake管理，可按照以下步骤，编译Android设备上运行的可执行程序。
+     这个步骤中依旧需要用到第一步中配置的**独立工具链**。
+
+    - armeabi-v7a架构
+
+    ```bash
+    $ git clone https://github.com/PaddlePaddle/Mobile.git
+    $ cd Mobile/benchmark/tool/C/
+    $ mkdir build
+    $ cd build
+    $ cmake .. \
+            -DANDROID_ABI=armeabi-v7a \
+            -DANDROID_STANDALONE_TOOLCHAIN=your/path/to/arm_standalone_toolchain \
+            -DPADDLE_ROOT=The output path generated in the first step \
+            -DCMAKE_BUILD_TYPE=MinSizeRel
+
+    $ make
+    ```
+
+    - arm64-v8a架构
+
+    ```bash
+    $ git clone https://github.com/PaddlePaddle/Mobile.git
+    $ cd Mobile/benchmark/tool/C/
+    $ mkdir build
+    $ cd build
+
+    $ cmake .. \
+            -DANDROID_ABI=arm64-v8a \
+            -DANDROID_STANDALONE_TOOLCHAIN=your/path/to/arm64_standalone_toolchain \
+            -DPADDLE_ROOT=The output path generated in the first step \
+            -DCMAKE_BUILD_TYPE=MinSizeRel
+
+    $ make
+    ```
+
+    执行上述命令执行，会在`build`目录下生成目标可执行文件`inference`。
+
+- **Step 3，准备模型。**
+
+    Android设备上推荐使用`merged model`。以Mobilenet为例，要生成`merged model`，首先你需要准备以下文件：
+    - 模型配置文件[mobilenet.py](https://github.com/PaddlePaddle/Mobile/blob/develop/models/mobilenet.py)，它是使用PaddlePaddle的v2 api编写的`Mobilenet`模型的网络结构。用户可在[models](https://github.com/PaddlePaddle/Mobile/tree/develop/models)获取更多PaddlePaddle常用的网络配置，该repo下面同时提供了使用PaddlePaddle训练模型的方法。
+    - 模型参数文件。使用PaddlePaddle v2 api训练得到的参数将会存储成`.tar.gz`文件。比如，我们提供了一个使用[flowers102](http://www.robots.ox.ac.uk/~vgg/data/flowers/102/)数据集训练`Mobilnet`分类模型的参数文件[mobilenet\_flowers102.tar.gz](http://cloud.dlnel.org/filepub/?uuid=4a3fcd7a-719c-479f-96e1-28a4c3f2195e)。你也可以使用以下命令下载该参数文件：
+
+    ```bash
+    wget -C http://cloud.dlnel.org/filepub/?uuid=4a3fcd7a-719c-479f-96e1-28a4c3f2195e -O mobilenet_flowers102.tar.gz
+    ```
+
+    **注意，用来`merge model`的模型配置文件必须只包含`inference`网络**。
+
+    在准备好模型配置文件（.py）和参数文件（.tar.gz）之后，且所在机器已经成功安装了PaddlePaddle的Python包之后，我们可以通过执行以下脚本生成需要的`merged model`。
+
+    ```bash
+    $ cd Mobile/tools/merge_config_parameters
+    $ python merge_model.py
+    ```
+
+    你也可以直接下载[mobilenet\_flowers102.paddle](http://cloud.dlnel.org/filepub/?uuid=d3b95cf9-4dc3-476f-bdc7-98ac410c4f71)试用。命令行下载方式：
+
+    ```
+    wget -C http://cloud.dlnel.org/filepub/?uuid=d3b95cf9-4dc3-476f-bdc7-98ac410c4f71 -O mobilenet_flowers102.paddle
+    ```
+
+    更多有关于生成`merged model`的详情，请参考[merge\_config\_parameters](https://github.com/PaddlePaddle/Mobile/tree/develop/tools/merge_config_parameters)。
+
+- **Step 4，在Android设备上测试。**
+
+     这是一个可以在Android设备上运行的命令行测试程序。你可以通过桌面终端，借助于[adb](https://developer.android.google.cn/studio/command-line/adb.html?hl=zh-cn#Enabling)工具，传输数据到Android设备上，并且登陆Android设备，运行可执行程序进行测试。
+
+    ```bash
+    $ adb push inference /data/local/tmp # 将可执行程序传输到Android设备上
+    $ adb push mobilenet_flowers102.paddle /data/local/tmp # 将模型文件传输到Android设备上
+    $ adb shell # 登陆Android设备
+    odin:/ $ cd /data/local/tmp # 进入工作目录
+    odin:/data/local/tmp $ ls
+    inference  mobilenet_flowers102.paddle
+    odin:/data/local/tmp $ chmod +x inference
+    odin:/data/local/tmp $ ./inference --merged_model ./mobilenet_flowers102.paddle --input_size 150528 # 执行测试程序
+    I1211 17:12:53.334666  4858 Util.cpp:166] commandline:
+    Time of init paddle 3.4388 ms.
+    Time of create from merged model file 141.045 ms.
+    Time of forward time 398.818 ms.
+    ```
+
+    `inference`可执行程序需要设置两个运行时参数：
+    - `--merged_model`，模型的路径。
+    - `--input_size`，模型输入数据的长度。由于`mobilenet`使用`3 x 224 x 224`图像数据作为输入，因此设置`--input_size 150528`。
+
+## 注意
+
+该示例程序只是用来简单地测试Android设备上，模型的推断速度。因为使用随机数据作为模型的输入，若要测试和验证模型的正确性，请根据实际的需求进行修改。

deployment/model/merge_config_parameters/README.md

@@ -1,7 +1,7 @@
 
 # Merge model config and parameters
 
-Integrate the model configuration and model parameters into one file. 
+Integrate the model configuration and model parameters into one file.
 The merged file is used in our capi forward predict program.
 
 ## Demo
@@ -10,23 +10,23 @@ This applies to all PaddlePaddle v2 models, we show a demo of mobilenet.
 
 ### Step 1: Prepartions
 
-**Model Config :** [Mobilenet model config](../../models/mobilenet.py).    
-**Model Parameters:** [Mobilenet model param pretrained on flower102 download](https://pan.baidu.com/s/1geHkrw3) 
+**Model Config :** [Mobilenet model config](../../models/mobilenet.py).  
+**Model Parameters:** [Mobilenet model param pretrained on flower102 download](https://pan.baidu.com/s/1geHkrw3)
 
-### Step2: Merge 
+### Step2: Merge
 
 Run the following code
 
-```
+```python
 from paddle.utils.merge_model import merge_v2_model
 
 # import your network configuration
 from mobilenet import mobile_net
-        
+
 net = mobile_net(3*224*224, 102, 1.0)
 param_file = './mobilenet_flowers102.tar.gz'
 output_file = './output.paddle'
-        
+
 merge_v2_model(net, param_file, output_file)
 
 ```

deployment/model/merge_config_parameters/merge_model.py

@@ -0,0 +1,13 @@
+import paddle.v2 as paddle
+from paddle.utils.merge_model import merge_v2_model
+
+# import network configuration
+from mobilenet import mobile_net
+
+if __name__ == "__main__":
+    image_size = 224
+    num_classes = 102
+    net = mobile_net(3 * image_size * image_size, num_classes, 1.0)
+    param_file = './mobilenet_flowers102.tar.gz'
+    output_file = './mobilenet_flowers102.paddle'
+    merge_v2_model(net, param_file, output_file)