add the document of inference library compiled on windows (#3688)

docs/demo_guides/cpp_demo.md

@@ -32,14 +32,26 @@ tar zxf mobilenet_v1.tar.gz
 
 ![image](https://paddlelite-data.bj.bcebos.com/doc_images/cxx_demo/3inference_model.png)
 
-（2）下载[opt工具](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.3.0/opt)。放入同一文件夹，终端输入命令转化模型：
+（2）模型转换
 
-```shell
-wget https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.3.0/opt
-chmod +x opt
-./opt --model_dir=./mobilenet_v1 --optimize_out_type=naive_buffer   --optimize_out=./mobilenet_v1_opt
-```
 
+  - v2.6.0版本之前
+
+  下载[opt工具](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.3.0/opt)。放入同一文件夹，终端输入命令转化模型
+
+  ```shell
+  wget https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.3.0/opt
+  chmod +x opt
+  ./opt --model_dir=./mobilenet_v1 --optimize_out_type=naive_buffer   --optimize_out=./mobilenet_v1_opt
+  ```
+  - v2.6.0版本以及后续版本
+
+  安装paddlelite，终端输入命令转化模型
+ 
+  ```shell
+  python -m pip install paddlelite
+  paddle_opt_lite --model_dir=./mobilenet_v1 --optimize_out_type=naive_buffer   --optimize_out=./mobilenet_v1_opt
+  ```
 **结果如下图所示：**
 
 ![image](https://paddlelite-data.bj.bcebos.com/doc_images/cxx_demo/2opt_model.png)

docs/demo_guides/python_demo.md

+# Python Demo
+
+## 1. 下载最新版本python预测库
+
+```shell
+python -m pip install paddlelite
+```
+
+## 2. 转化模型
+
+PaddlePaddle的原生模型需要经过[opt]()工具转化为Paddle-Lite可以支持的naive_buffer格式。
+
+以`mobilenet_v1`模型为例：
+
+（1）下载[mobilenet_v1模型](http://paddle-inference-dist.bj.bcebos.com/mobilenet_v1.tar.gz)后解压：
+
+```shell
+wget http://paddle-inference-dist.bj.bcebos.com/mobilenet_v1.tar.gz
+tar zxf mobilenet_v1.tar.gz
+```
+
+（2）使用opt工具：
+
+ 从磁盘加载模型时，根据模型和参数文件存储方式不同，加载模型和参数的路径有两种形式。
+
+- Linux环境
+  - 非combined形式：模型文件夹model_dir下存在一个模型文件和多个参数文件时，传入模型文件夹路径，模型文件名默认为__model__。
+
+  ```shell
+  paddle_lite_opt --model_dir=./mobilenet_v1  \
+                  --optimize_out=mobilenet_v1_opt \
+                  --optimize_out_type=naive_buffer \
+                  --valid_targets=x86
+  ```
+  - combined形式：模型文件夹model_dir下只有一个模型文件__model__和一个参数文件__params__时，传入模型文件和参数文件路径
+
+  ```shell
+  paddle_lite_opt --model_file=./mobilenet_v1/__model__ \
+                  --param_file=./mobilenet_v1/__params__  \
+                  --optimize_out=mobilenet_v1_opt \
+                  --optimize_out_type=naive_buffer \
+                  --valid_targets=x86
+  ```
+
+- windows环境
+
+windows 暂不支持命令行方式直接运行模型转换器，需要编写python脚本
+
+```python
+import paddlelite.lite as lite
+
+a=lite.Opt()
+# 非combined形式
+a.set_model_dir("D:\\YOU_MODEL_PATH\\mobilenet_v1")
+
+# conmbined形式
+# a.set_model_file("D:\\YOU_MODEL_PATH\\mobilenet_v1\\__model__")
+# a.set_param_file("D:\\YOU_MODEL_PATH\\mobilenet_v1\\__params__")
+
+a.set_optimize_out("mobilenet_v1_opt")
+a.set_valid_places("x86")
+
+a.run()
+```
+
+- MAC 环境
+
+Opt工具使用方式同Linux（MAC环境暂不支持python端预测，下个版本会修复该问题）
+
+## 3. 编写预测程序
+
+准备好预测库和模型，我们便可以编写程序来执行预测。我们提供涵盖图像分类、目标检测等多种应用场景的C++示例demo可供参考，创建文件mobilenetV1_light_api.py，
+python demo 完整代码位于 [demo/python](https://github.com/PaddlePaddle/Paddle-Lite/blob/develop/lite/demo/python/mobilenetv1_light_api.py) 。
+
+(1) 设置config信息
+```python
+from paddlelite.lite import *
+
+config = MobileConfig()
+config.set_model_dir(/YOU_MODEL_PATH/mobilenet_v1_opt.nb)
+```
+
+(2) 创建predictor
+
+```python
+predictor = create_paddle_predictor(config)
+```
+
+(3) 设置输入数据
+```python
+input_tensor = predictor.get_input(0)
+input_tensor.resize([1, 3, 224, 224])
+input_tensor.set_float_data([1.] * 3 * 224 * 224)
+```
+
+(4) 执行预测
+```python
+predictor.run()
+```
+
+(5) 得到输出数据
+```python
+output_tensor = predictor.get_output(0)
+print(output_tensor.shape())
+print(output_tensor.float_data()[:10])
+```
+
+## 4. 运行文件
+```shell
+python mobilenetV1_light_api.py
+```

docs/demo_guides/x86.md

@@ -4,8 +4,6 @@
 
 Paddle-Lite 支持在Docker或Linux环境编译x86预测库。环境搭建参考[环境准备](../user_guides/source_compile)。
 
-(注意：非docker Linux环境需要是Ubuntu16.04)
-
 ### 编译
 
 1、 下载代码
@@ -20,10 +18,11 @@ git checkout release/v2.6.0
 
 ```bash
 cd Paddle-Lite
-./lite/tools/build.sh x86
+./lite/tools/build.sh --build_python=ON x86
 
 # 其他可选择编译选项
 # --with_log=OFF 关闭LOG信息输出
+# --build_python=OFF 编译python预测库
 ```
 
 ### 编译结果说明
@@ -53,8 +52,17 @@ x86编译结果位于 `build.lite.x86/inference_lite_lib`
 - `mobilenetv1_full` ：使用full_api 执行mobilenet_v1预测的C++ demo
 - `mobilenetv1_light` ：使用light_api 执行mobilenet_v1预测的C++ demo
 
+5、 `demo/python`文件夹：x86预测库的Python 示例demo
+
+- `mobilenetv1_full_api.py` ：使用full_api 执行mobilenet_v1预测的Python demo
+- `mobilenetv1_light_api.py` ：使用light_api 执行mobilenet_v1预测的Python demo
 
+6、 `python`文件夹：包含python的库文件和对应的.whl包
 
+- `install`文件夹：编译成功的.whl包位于`install/dist/*.whl`
+- `lib`文件夹：.whl包依赖的库文件
+
+**(若不需要编译python预测库，则将编译命令替换为`./lite/tools/build.sh x86`)**
 
 ### x86预测API使用示例
 
@@ -64,7 +72,8 @@ x86编译结果位于 `build.lite.x86/inference_lite_lib`
 mobilenetv1_full/
 |-- CMakeLists.txt
 |-- build.sh
-`-- mobilenet_full_api.cc
+|-- build.bat
+-- mobilenet_full_api.cc
 ```
 
 本demo使用cmake构建`CMakeLists.txt`为cmake脚本，`mobilenet_full_api.cc`是x86示例的源代码、`build.sh`为编译的脚本。
@@ -168,8 +177,8 @@ int main(int argc, char** argv) {
 #### 编译环境需求
 
 - Windows 10 专业版
-  - 目前Windows暂不支持GPU模式
-- *Python 版本 2.7/3.5.1+/3.6/3.7 (64 bit)*
+  - 目前Windows暂不支持GPU编译
+- *Python 版本 2.7/3.5.1+ (64 bit)*
 - *pip 或 pip3 版本 9.0.1+ (64 bit)*
 - *Visual Studio 2015 Update3*
 
@@ -187,15 +196,15 @@ int main(int argc, char** argv) {
 ```bash
 git clone https://github.com/PaddlePaddle/Paddle-Lite.git
 # 切换到release分支
-git checkout release/v2.3
+git checkout release/v2.6.0
 ```
-2、 源码编译
+2、 源码编译(需要按照提示输入对应的参数)
 
-```bash
+```dos
 cd Paddle-Lite
-lite/tools/build_windows.bat with_extra with_python with_profile
+lite\tools\build_windows.bat with_extra with_python with_profile
 ```
-编译脚本`lite/tools/build.bat`，追加参数说明：
+编译脚本`build_windows.bat`，追加参数说明：
 
 |   参数     |     介绍     |     值     |
 |-----------|-------------|-------------|
@@ -203,40 +212,62 @@ lite/tools/build_windows.bat with_extra with_python with_profile
 |  with_python | 可选，是否编译python预测库（默认为OFF） 。 | `ON`、`OFF` |
 |  with_profile | 可选，是否支持分析器模式（默认为OFF） 。 | `ON`、`OFF` |
 
-### 编译结果
+### 编译结果说明
 
 x86编译结果位于 `build.lite.x86/inference_lite_lib`
 **具体内容**说明：
 
-1、 `bin`文件夹：可执行工具文件 `test_model_bin`
-
-2、 `cxx`文件夹：包含c++的库文件与相应的头文件
+1、 `cxx`文件夹：包含c++的库文件与相应的头文件
 
 - `include`  : 头文件
 - `lib` : 库文件
-  - 打包的静态库文件：
+  - 静态库文件：
     - `libpaddle_api_full_bundled.lib`  ：full_api 静态库
     - `libpaddle_api_light_bundled.lib` ：light_api 静态库
 
-3、 `third_party` 文件夹：第三方库文件
+2、 `third_party` 文件夹：依赖的第三方预测库mklml
+
+- mklml : Paddle-Lite预测库依赖的mklml数学库
+
+3、 `demo/cxx`文件夹：x86预测库的C++ 示例demo
+
+- `mobilenetv1_full` ：使用full_api 执行mobilenet_v1预测的C++ demo
+- `mobilenetv1_light` ：使用light_api 执行mobilenet_v1预测的C++ demo
+
+4、 `demo/python`: x86预测库的Python示例demo
+
+- `mobilenetv1_full_api.py`:使用full_api 执行mobilenet_v1预测的Python demo
+- `mobilenetv1_light_api.py`:使用full_api 执行mobilenet_v1预测的Python demo
 
+5、 `python`文件夹：包含python的库文件和对应的.whl包
+
+- `install`文件夹：编译成功的.whl包位于`install/dist/*.whl`
+- `lib`文件夹：.whl包依赖的库文件
 ### x86预测API使用示例
 
-1、我们提供Windows环境下x86 API运行mobilenet_v1的示例：[mobilenet_full_x86demo](https://paddlelite-data.bj.bcebos.com/x86/mobilenet_full_x86demo.zip)。下载解压后内容如下>：
+1、`mobilenetv1_full`目录结构
 
-![](https://paddlelite-data.bj.bcebos.com/x86/x86-doc/demo.png)
+```bash
+mobilenetv1_full/
+|-- CMakeLists.txt
+|-- build.sh
+|-- build.bat
+`-- mobilenet_full_api.cc
+```
 
-`mobilenet_v1`为模型文件、`lib`和`include`分别是Paddle-Lite的预测库和头文件、`third_party`下是编译时依赖的第三方库`mklml`、`mobilenet_full_api.cc`是x86示例的源代码、`build.bat`为编译的脚本。
+本demo使用cmake构建`CMakeLists.txt`为cmake脚本，`mobilenet_full_api.cc`是x86示例的源代码、`build.sh`为Linux x86编译的脚本，`build.bat`为windows x86编译脚本。
 
-2、demo内容与使用方法
+2、demo使用方法
 
 ``` bash
-# 1、编译(需在vs2015的命令窗口执行该脚本)
+# 1、编译
+cd mobilenetv1_full
 build.bat
+cd build
 ```
-编译结果为当前目录下的 `Release\\mobilenet_full_api.exe`
-``` bash
+编译结果为当前目录下的 `Release\mobilenet_full_api.exe `
+``` dos
 # 2、执行预测
-Release\\mobilenet_full_api.exe ..\mobilenet_v1
+Release\mobilenet_full_api.exe mobilenet_v1
 ```
-`mobilenet_v1`为模型路径，`mobilenet_full_api.exe`为第一步编译出的可执行文件。
+下载并解压模型[`mobilenet_v1`](http://paddle-inference-dist.bj.bcebos.com/mobilenet_v1.tar.gz)到当前`build`目录，执行以上命令进行预测。

docs/index.rst

@@ -47,6 +47,7 @@ Welcome to Paddle-Lite's documentation!
 
   demo_guides/cpp_demo
   demo_guides/java_demo
+  demo_guides/python_demo
   demo_guides/android_app_demo
   demo_guides/ios_app_demo
   demo_guides/x86

docs/user_guides/source_compile.md

@@ -10,11 +10,12 @@ PaddleLite 提供了移动端的一键源码编译脚本 `lite/tools/build.sh`
 
 ## 一、环境准备
 
-目前支持三种编译的环境：
+目前支持四种编译的环境：
 
 1. Docker 容器环境，
 2. Linux（推荐 Ubuntu 16.04）环境，
-3. Mac OS 环境。
+3. Mac OS 环境，
+4. [Windows 环境](../demo_guides/x86.html#windows)
 
 ### 1、 Docker开发环境
 

lite/CMakeLists.txt

@@ -224,11 +224,11 @@ if (LITE_WITH_X86)
         add_dependencies(publish_inference publish_inference_x86_cxx_lib)
 
         add_custom_target(publish_inference_x86_cxx_demos ${TARGET}
-            COMMAND ${CMAKE_COMMAND} -E make_directory "${INFER_LITE_PUBLISH_ROOT}/third_party"
-            COMMAND ${CMAKE_COMMAND} -E copy_directory "${CMAKE_BINARY_DIR}/third_party/install" "${INFER_LITE_PUBLISH_ROOT}/third_party"
-            COMMAND ${CMAKE_COMMAND} -E copy_directory "${CMAKE_BINARY_DIR}/third_party/eigen3" "${INFER_LITE_PUBLISH_ROOT}/third_party"
+            COMMAND ${CMAKE_COMMAND} -E make_directory "${INFER_LITE_PUBLISH_ROOT}/third_party/mklml"
+            COMMAND ${CMAKE_COMMAND} -E copy_directory "${CMAKE_BINARY_DIR}/third_party/install/mklml" "${INFER_LITE_PUBLISH_ROOT}/third_party/mklml"
             COMMAND ${CMAKE_COMMAND} -E make_directory "${INFER_LITE_PUBLISH_ROOT}/demo/cxx"
-            COMMAND ${CMAKE_COMMAND} -E copy_directory "${CMAKE_SOURCE_DIR}/lite/demo/cxx" "${INFER_LITE_PUBLISH_ROOT}/demo/cxx"
+            COMMAND ${CMAKE_COMMAND} -E copy_directory "${CMAKE_SOURCE_DIR}/lite/demo/cxx/x86_mobilenetv1_light_demo" "${INFER_LITE_PUBLISH_ROOT}/demo/cxx/mobilenetv1_light"
+            COMMAND ${CMAKE_COMMAND} -E copy_directory "${CMAKE_SOURCE_DIR}/lite/demo/cxx/x86_mobilenetv1_full_demo" "${INFER_LITE_PUBLISH_ROOT}/demo/cxx/mobilenetv1_full"
         )
         add_dependencies(publish_inference_x86_cxx_lib publish_inference_x86_cxx_demos)
         add_dependencies(publish_inference_x86_cxx_demos paddle_api_full_bundled eigen3)

lite/demo/cxx/x86_mobilenetv1_full_demo/CMakeLists.txt

@@ -6,16 +6,44 @@ set(TARGET mobilenet_full_api)
 set(LITE_DIR "${PROJECT_SOURCE_DIR}/../../../cxx")
 set(MKLML_DIR "${PROJECT_SOURCE_DIR}/../../../third_party/mklml/")
 
+if (WIN32)
+  add_definitions("/DGOOGLE_GLOG_DLL_DECL=")
+  option(MSVC_STATIC_CRT "use static C Runtime library by default" ON)
+  if (MSVC_STATIC_CRT)
+    set(CMAKE_C_FLAGS_DEBUG   "${CMAKE_C_FLAGS_DEBUG} /bigobj /MTd")
+    set(CMAKE_C_FLAGS_RELEASE  "${CMAKE_C_FLAGS_RELEASE} /bigobj /MT")
+    set(CMAKE_CXX_FLAGS_DEBUG  "${CMAKE_CXX_FLAGS_DEBUG} /bigobj /MTd")
+    set(CMAKE_CXX_FLAGS_RELEASE   "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT")
+  endif()
+endif()
+
 # 2. link mklml and Paddle-Lite directory
 link_directories(${LITE_DIR}/lib ${MKLML_DIR}/lib)
 include_directories(${LITE_DIR}/include/ ${MKLML_DIR}/include)
 
 # 3. compile options 
-add_definitions(-std=c++11 -g -O3 -pthread)
-set(EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR})
+if (NOT WIN32)
+  add_definitions(-std=c++11 -g -O3 -pthread)
+  set(EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR})
+endif()
 
 # 4.add executable output
 add_executable(${TARGET} ${TARGET}.cc)
-target_link_libraries(${TARGET} -lpaddle_full_api_shared)
-target_link_libraries(${TARGET} -liomp5)
-target_link_libraries(${TARGET} -ldl)
+if (WIN32)
+  set(MATH_LIB ${MKLML_DIR}/lib/mklml${CMAKE_STATIC_LIBRARY_SUFFIX}
+      ${MKLML_DIR}/lib/libiomp5md${CMAKE_STATIC_LIBRARY_SUFFIX})
+
+
+  target_link_libraries(${TARGET} libpaddle_api_full_bundled.lib)
+  target_link_libraries(${TARGET} shlwapi.lib)
+  target_link_libraries(${TARGET} ${MATH_LIB})
+
+   add_custom_command(TARGET ${TARGET} POST_BUILD
+       COMMAND ${CMAKE_COMMAND} -E copy ${MKLML_DIR}/lib/mklml.dll ${CMAKE_BINARY_DIR}/Release
+       COMMAND ${CMAKE_COMMAND} -E copy ${MKLML_DIR}/lib/libiomp5md.dll ${CMAKE_BINARY_DIR}/Release
+   )
+else()
+    target_link_libraries(${TARGET} -lpaddle_full_api_shared)
+    target_link_libraries(${TARGET} -liomp5)
+    target_link_libraries(${TARGET} -ldl)
+endif()

lite/demo/cxx/x86_mobilenetv1_full_demo/build.bat

+@echo off
+setlocal
+setlocal enabledelayedexpansion
+
+set source_path=%~dp0
+
+set build_directory=%source_path%\build
+
+if EXIST "%build_directory%" (
+    call:rm_rebuild_dir "%build_directory%"
+) 
+
+md "%build_directory%"
+set vcvarsall_dir=C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\vcvarsall.bat
+
+IF NOT EXIST "%vcvarsall_dir%" (
+  goto set_vcvarsall_dir
+) else (
+  goto cmake
+)
+
+:set_vcvarsall_dir
+SET /P vcvarsall_dir="Please input the path of visual studio command Prompt, such as C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\vcvarsall.bat   =======>"
+set tmp_var=!vcvarsall_dir!
+call:remove_space
+set vcvarsall_dir=!tmp_var!   
+IF NOT EXIST "!vcvarsall_dir!" (
+    echo "------------!vcvarsall_dir! not exist------------"
+    goto set_vcvarsall_dir
+)
+
+:cmake
+D:
+cd "%build_directory%"
+
+cmake ..   -G "Visual Studio 14 2015 Win64" -T host=x64
+
+call "%vcvarsall_dir%" amd64
+
+msbuild /maxcpucount:8 /p:Configuration=Release  mobilenet_full_api.vcxproj
+
+goto:eof
+
+:rm_rebuild_dir
+    del /f /s /q "%~1\*.*"  >nul 2>&1
+    rd /s /q  "%~1" >nul 2>&1
+goto:eof
+
+:remove_space
+:remove_left_space
+if "%tmp_var:~0,1%"==" " (
+    set "tmp_var=%tmp_var:~1%"
+    goto remove_left_space
+)
+
+:remove_right_space
+if "%tmp_var:~-1%"==" " (
+    set "tmp_var=%tmp_var:~0,-1%"
+    goto remove_left_space
+)
+goto:eof

lite/demo/cxx/x86_mobilenetv1_full_demo/mobilenet_full_api.cc

@@ -16,6 +16,11 @@
 #include <vector>
 #include "paddle_api.h"  // NOLINT
 
+#ifdef _WIN32
+#include "paddle_use_kernels.h"  // NOLINT
+#include "paddle_use_ops.h"      // NOLINT
+#endif
+
 using namespace paddle::lite_api;  // NOLINT
 
 int64_t ShapeProduction(const shape_t& shape) {

lite/demo/cxx/x86_mobilenetv1_light_demo/CMakeLists.txt

@@ -6,16 +6,44 @@ set(TARGET mobilenet_light_api)
 set(LITE_DIR "${PROJECT_SOURCE_DIR}/../../../cxx")
 set(MKLML_DIR "${PROJECT_SOURCE_DIR}/../../../third_party/mklml/")
 
+if (WIN32)
+  add_definitions("/DGOOGLE_GLOG_DLL_DECL=")
+  option(MSVC_STATIC_CRT "use static C Runtime library by default" ON)
+  if (MSVC_STATIC_CRT)
+    set(CMAKE_C_FLAGS_DEBUG   "${CMAKE_C_FLAGS_DEBUG} /bigobj /MTd")
+    set(CMAKE_C_FLAGS_RELEASE  "${CMAKE_C_FLAGS_RELEASE} /bigobj /MT")
+    set(CMAKE_CXX_FLAGS_DEBUG  "${CMAKE_CXX_FLAGS_DEBUG} /bigobj /MTd")
+    set(CMAKE_CXX_FLAGS_RELEASE   "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT")
+  endif()
+endif()
+
 # 2. link mklml and Paddle-Lite directory
 link_directories(${LITE_DIR}/lib ${MKLML_DIR}/lib)
 include_directories(${LITE_DIR}/include/ ${MKLML_DIR}/include)
 
 # 3. compile options 
-add_definitions(-std=c++11 -g -O3 -pthread)
-set(EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR})
+if (NOT WIN32)
+  add_definitions(-std=c++11 -g -O3 -pthread)
+  set(EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR})
+endif()
 
 # 4.add executable output
 add_executable(${TARGET} ${TARGET}.cc)
-target_link_libraries(${TARGET} -lpaddle_light_api_shared)
-target_link_libraries(${TARGET} -liomp5)
-target_link_libraries(${TARGET} -ldl)
+if (WIN32)
+  set(MATH_LIB ${MKLML_DIR}/lib/mklml${CMAKE_STATIC_LIBRARY_SUFFIX}
+      ${MKLML_DIR}/lib/libiomp5md${CMAKE_STATIC_LIBRARY_SUFFIX})
+
+
+  target_link_libraries(${TARGET} libpaddle_api_light_bundled.lib)
+  target_link_libraries(${TARGET} shlwapi.lib)
+  target_link_libraries(${TARGET} ${MATH_LIB})
+
+   add_custom_command(TARGET ${TARGET} POST_BUILD
+       COMMAND ${CMAKE_COMMAND} -E copy ${MKLML_DIR}/lib/mklml.dll ${CMAKE_BINARY_DIR}/Release
+       COMMAND ${CMAKE_COMMAND} -E copy ${MKLML_DIR}/lib/libiomp5md.dll ${CMAKE_BINARY_DIR}/Release
+   )
+else()
+    target_link_libraries(${TARGET} -lpaddle_light_api_shared)
+    target_link_libraries(${TARGET} -liomp5)
+    target_link_libraries(${TARGET} -ldl)
+endif()

lite/demo/cxx/x86_mobilenetv1_light_demo/build.bat

+@echo off
+setlocal
+setlocal enabledelayedexpansion
+
+set source_path=%~dp0
+
+set build_directory=%source_path%\build
+
+if EXIST "%build_directory%" (
+    call:rm_rebuild_dir "%build_directory%"
+) 
+
+md "%build_directory%"
+set vcvarsall_dir=C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\vcvarsall.bat
+
+IF NOT EXIST "%vcvarsall_dir%" (
+  goto set_vcvarsall_dir
+) else (
+  goto cmake
+)
+
+:set_vcvarsall_dir
+SET /P vcvarsall_dir="Please input the path of visual studio command Prompt, such as C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\vcvarsall.bat   =======>"
+set tmp_var=!vcvarsall_dir!
+call:remove_space
+set vcvarsall_dir=!tmp_var!   
+IF NOT EXIST "!vcvarsall_dir!" (
+    echo "------------!vcvarsall_dir! not exist------------"
+    goto set_vcvarsall_dir
+)
+
+:cmake
+D:
+cd "%build_directory%"
+
+cmake ..   -G "Visual Studio 14 2015 Win64" -T host=x64
+
+call "%vcvarsall_dir%" amd64
+
+msbuild /maxcpucount:8 /p:Configuration=Release  mobilenet_light_api.vcxproj
+
+goto:eof
+
+:rm_rebuild_dir
+    del /f /s /q "%~1\*.*"  >nul 2>&1
+    rd /s /q  "%~1" >nul 2>&1
+goto:eof
+
+:remove_space
+:remove_left_space
+if "%tmp_var:~0,1%"==" " (
+    set "tmp_var=%tmp_var:~1%"
+    goto remove_left_space
+)
+
+:remove_right_space
+if "%tmp_var:~-1%"==" " (
+    set "tmp_var=%tmp_var:~0,-1%"
+    goto remove_left_space
+)
+goto:eof

lite/model_parser/model_parser.cc

@@ -324,7 +324,7 @@ void SaveCombinedParamsPb(const std::string &path,
   std::sort(paramlist.begin(), paramlist.end());
 
   // Load vars
-  std::ofstream file(path);
+  std::ofstream file(path, std::ios::binary);
   CHECK(file.is_open());
   for (size_t i = 0; i < paramlist.size(); ++i) {
     SerializeTensor(file, exec_scope, paramlist[i]);

lite/utils/io.h

@@ -38,9 +38,16 @@ static bool IsFileExists(const std::string& path) {
 // ARM mobile not support mkdir in C++
 static void MkDirRecur(const std::string& path) {
 #ifndef LITE_WITH_ARM
+
+#ifdef _WIN32
+  if (system(string_format("md %s", path.c_str()).c_str()) != 0) {
+    LOG(ERROR) << "Cann't mkdir " << path;
+  }
+#else
   if (system(string_format("mkdir -p %s", path.c_str()).c_str()) != 0) {
     LOG(ERROR) << "Cann't mkdir " << path;
   }
+#endif  // _WIN32
 #else   // On ARM
   CHECK_NE(mkdir(path.c_str(), S_IRWXU), -1) << "Cann't mkdir " << path;
 #endif