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* windows doc * fix comment. test=develop
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doc/fluid/user_guides/howto/inference/windows_cpp_inference.md
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Windows环境模型预测使用说明 | ||
=========================== | ||
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环境部署 | ||
-------- | ||
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### 硬件环境 | ||
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测试环境硬件配置: | ||
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| CPU | I7-8700K | | ||
|----------|:-------------:| | ||
| 内存 | 16G | | ||
| 硬盘 | 1T hdd + 256G ssd | | ||
| 显卡 | GTX1080 8G | | ||
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测试环境操作系统使用win10 Version 18.03 版本。下载地址: | ||
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### 环境配置步骤 | ||
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**一定要严格按照安装步骤顺序,否则会安装失败!** | ||
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**安装vs2015** | ||
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安装vs2015,安装选项中选择安装内容时勾选自定义,把关于c,c++,vc++的功能都安装上。下载地址: | ||
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**安装CUDA8** | ||
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需要去NVIDIA官网[https://www.geforce.cn/drivers](https://www.geforce.cn/drivers) | ||
下载显卡对应的驱动。推荐391版本 | ||
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![](image/image1.png) | ||
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安装时需要勾选自定义,勾选安装全部。 | ||
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验证安装需要进入cmd中,输入nvcc -V查看。 | ||
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![](image/image2.png) | ||
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如果有显卡安装驱动,也可以选择直接安装CUDA8.0,[https://developer.nvidia.com/cuda-80-ga2-download-archive](https://developer.nvidia.com/cuda-80-ga2-download-archive) | ||
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**安装CUDNN** | ||
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安装CUDNN只需要将文件中CUDNN | ||
7下的文件复制到对应的CUDA安装目录下。文件名,cudnn-8.0-windows10-x64-v7.zip。这里提供了cudnn | ||
7 | ||
64位的版本。需要其他版本可在[https://developer.nvidia.com/cudnn](https://developer.nvidia.com/cudnn) | ||
下载。 | ||
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预测demo使用 | ||
------------ | ||
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解压Paddle,Release,fluid\_install\_dir压缩包。 | ||
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进入Paddle/paddle/fluid/inference/api/demo\_ci目录,新建build目录并进入,然后使用cmake生成vs2015的solution文件。 | ||
指令为: | ||
```cmake | ||
cmake .. -G \"Visual Studio 14 2015 Win64\" -DWITH\_GPU=ON | ||
-DWITH\_MKL=OFF -DWITH\_STATIC\_LIB=ON -DCMAKE\_BUILD\_TYPE=Release | ||
-DDEMO\_NAME=simple\_on\_word2vec | ||
-DPADDLE\_LIB=D:\\to\_the\_paddle\_fluid.lib | ||
-DCUDA\_LIB=D:\\CUDA\\v8.0\\lib\\x64 | ||
``` | ||
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注: | ||
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-DDEMO\_NAME 是要编译的文件 | ||
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-DPADDLE\_LIB 是fluid\_install\_dir路径,例如 | ||
-DPADDLE\_LIB=D:\\fluid\_install\_dir | ||
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-DCUDA\_LIB 是CUDA安装目录对应的文件夹 | ||
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Cmake可以在官网进行下载,并添加到环境变量中。[[https://cmake.org/download/]{.underline}](https://cmake.org/download/) | ||
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执行完毕后,build目录如图所示,打开 箭头指向的solution文件: | ||
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![](image/image3.png) | ||
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修改编译属性为/MT: | ||
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![](image/image4.png) | ||
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![](image/image5.png) | ||
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编译生成选项改成Release。 | ||
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![](image/image6.png) | ||
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![](image/image7.png) | ||
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将提供的依赖包中,Release下的openblas和模型文件拷贝到编译生成的Release下。 | ||
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![](image/image8.png) | ||
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通过cmd进到Release目录执行: | ||
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1. 开启GLOG | ||
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set GLOG\_v=3 | ||
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2. 进行预测 | ||
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simple\_on\_word2vec.exe \--dirname=.\\word2vec.inference.model | ||
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![](image/image9.png) | ||
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FAQ: | ||
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路径中尽量不要包含空格,例如发现CUDA\_LIB路径是Program | ||
Files(x86)可能会出错。可以将CUDA拷贝到一个新位置(这里直接拷贝就行) |