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* [docs] update quick_start and README * [docs] remove ENABLE_PADDLE_FRONTEND flags in win docs * [docs] update supported python version for win * [docs] update windows sdk example docs Co-authored-by: Jason <jiangjiajun@baidu.com>
57 lines
1.9 KiB
Markdown
57 lines
1.9 KiB
Markdown
# FastDeploy 预编译Python Wheel包
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FastDeploy提供了在Windows/Linux/Mac上的预先编译Python Wheel包，开发者可以直接下载后安装，也可以自行编译代码。
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目前各平台支持情况如下
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- Linux 支持Python3.6~3.9
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- Windows 支持Python3.6~3.9
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- Mac 支持Python3.6~3.9
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## 安装 CPU Python 版本
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```bash
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pip install fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
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```
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## 安装 GPU Python 版本
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```bash
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pip install fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
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```
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## Anaconda 快速配置 GPU 环境
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使用Anaconda的用户可在命令运行以下命令，快速配置GPU环境。如果是Windows用户，需要先打开`Anaconda Prompt (anaconda3)`命令行终端。
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- 增加 conda-forge 源
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```bash
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conda config --add channels conda-forge
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# 国内用户可以增加国内的源，如
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conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
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conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
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conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
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```
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- 新建 python 环境
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```bash
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conda create -n py38 python=3.8
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conda activate py38
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```
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- 安装 cudatoolkit 11.x 和 cudnn 8.x
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```bash
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conda install cudatoolkit=11.2 cudnn=8.2
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```
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- 安装 FastDeploy GPU 版本 Python 包
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```bash
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pip install fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
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```
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## 注意事项
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- 不要重复安装`fastdeploy-python`和`fastdeploy-gpu-python`
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- 如已安装CPU版本的`fastdeploy-python`后，在安装GPU版本的`fastdeploy-gpu-python`，请先执行`pip uninstall fastdeploy-python`卸载已有版本
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## 环境依赖
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- cuda >= 11.2
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- cudnn >= 8.0
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## 其它文档
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- [预编译C++部署库](./CPP_prebuilt_libraries.md)
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- [视觉模型C++/Python部署示例](../../examples/vision/)
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