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未验证 提交 fe8dc022 编写于 作者: J Jiawei Wang 提交者： GitHub
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Merge pull request #1514 from bjjwwang/compile_doc 

fix docs related to docker
上级 7dac72d5 976ae871
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doc/C++_Serving/ABTest_CN.md
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......@@ -30,7 +30,7 @@ pip install Shapely
### 启动Server端
这里采用[Docker方式](../Run_In_Docker_CN.md)启动Server端服务。
这里采用[Docker方式](../Install_CN.md)启动Server端服务。
首先启动BOW Server，该服务启用`8000`端口：
......
doc/Docker_Images_CN.md
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......@@ -8,10 +8,10 @@
您可以通过两种方式获取镜像。
1. 通过 TAG 直接从 `registry.baidubce.com ` 或 拉取镜像，具体TAG请参见下文的**镜像说明**章节的表格。
1. 通过 TAG 直接从 dockerhub 或 `registry.baidubce.com` 拉取镜像，具体TAG请参见下文的**镜像说明**章节的表格。
```shell
docker pull registry.baidubce.com/paddlepaddle/serving:<TAG> # registry.baidubce.com
docker pull paddlepaddle/serving:<TAG> # 如果连接dockerhub网速不佳可以尝试registry.baidubce.com/paddlepaddle/serving:<TAG>
```
2. 基于 Dockerfile 构建镜像
......@@ -19,27 +19,25 @@
建立新目录，复制对应 Dockerfile 内容到该目录下 Dockerfile 文件。执行
```shell
cd tools
docker build -f ${DOCKERFILE} -t <image-name>:<images-tag> .
docker build -f tools/${DOCKERFILE} -t <image-name>:<images-tag> .
```
## 镜像说明
运行时镜像不能用于开发编译。
若需要基于源代码二次开发编译，请使用后缀为-devel的版本。
**在TAG列，latest也可以替换成对应的版本号，例如0.5.0/0.4.1等，但需要注意的是，部分开发环境随着某个版本迭代才增加，因此并非所有环境都有对应的版本号可以使用。**
**在TAG列，0.7.0也可以替换成对应的版本号，例如0.5.0/0.4.1等，但需要注意的是，部分开发环境随着某个版本迭代才增加，因此并非所有环境都有对应的版本号可以使用。**
**cuda10.1-cudnn7-gcc54环境尚未同步到镜像仓库，如果您需要相关镜像请运行相关dockerfile**
| 镜像选择 | 操作系统 | TAG | Dockerfile |
| :----------------------------------------------------------: | :-----: | :--------------------------: | :----------------------------------------------------------: |
| CPU development | Ubuntu16 | latest-devel | [Dockerfile.devel](../tools/Dockerfile.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development | Ubuntu16 | latest-cuda10.1-cudnn7-gcc54-devel (not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6) development | Ubuntu16 | latest-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
| GPU (cuda10.2-cudnn8-tensorRT7) development | Ubuntu16 | latest-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
| GPU (cuda11.2-cudnn8-tensorRT7) development | Ubuntu18 | latest-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
| CPU development | Ubuntu16 | 0.7.0-devel | [Dockerfile.devel](../tools/Dockerfile.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development | Ubuntu16 | 0.7.0-cuda10.1-cudnn7-gcc54-devel (not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6) development | Ubuntu16 | 0.7.0-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
| GPU (cuda10.2-cudnn7-tensorRT6) development | Ubuntu16 | 0.7.0-cuda10.2-cudnn7-devel | [Dockerfile.cuda10.2-cudnn7.devel](../tools/Dockerfile.cuda10.2-cudnn7.devel) |
| GPU (cuda10.2-cudnn8-tensorRT7) development | Ubuntu16 | 0.7.0-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
| GPU (cuda11.2-cudnn8-tensorRT8) development | Ubuntu16 | 0.7.0-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
**Java镜像：**
```
......@@ -63,38 +61,24 @@ registry.baidubce.com/paddlepaddle/serving:xpu-x86 # for x86 xpu user
# （附录）所有镜像列表
编译镜像：
开发镜像:
| Env | Version | Docker images tag | OS | Gcc Version |
|----------|---------|------------------------------|-----------|-------------|
| CPU | >=0.5.0 | 0.6.2-devel | Ubuntu 16 | 8.2.0 |
| CPU | >=0.5.0 | 0.7.0-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.4.0-devel | CentOS 7 | 4.8.5 |
| Cuda10.1 | >=0.5.0 | 0.6.2-cuda10.1-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.6.2-cuda10.1-cudnn7-devel | CentOS 7 | 4.8.5 |
| Cuda10.2 | >=0.5.0 | 0.6.2-cuda10.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| Cuda10.1 | >=0.5.0 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.4.0-cuda10.1-cudnn7-devel | CentOS 7 | 4.8.5 |
| Cuda10.2+Cudnn7 | >=0.5.0 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
| Cuda11.0 | >=0.5.0 | 0.6.2-cuda11.0-cudnn8-devel | Ubuntu 18 | 8.2.0 |
| Cuda10.2+Cudnn8 | >=0.5.0 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
| Cuda11.2 | >=0.5.0 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
运行镜像:
运行镜像比开发镜像更加轻量化, 运行镜像提供了serving的whl和bin，但为了运行期更小的镜像体积，没有提供诸如cmake这样但开发工具。 如果您想了解有关信息，请检查文档[在Kubernetes上使用Paddle Serving](./Run_On_Kubernetes_CN.md)。
| ENV | Python Version | Tag |
|------------------------------------------|----------------|-----------------------------|
| cpu | 3.6 | 0.6.2-py36-runtime |
| cpu | 3.7 | 0.6.2-py37-runtime |
| cpu | 3.8 | 0.6.2-py38-runtime |
| cuda-10.1 + cudnn-7.6.5 + tensorrt-6.0.1 | 3.6 | 0.6.2-cuda10.1-py36-runtime |
| cuda-10.1 + cudnn-7.6.5 + tensorrt-6.0.1 | 3.7 | 0.6.2-cuda10.1-py37-runtime |
| cuda-10.1 + cudnn-7.6.5 + tensorrt-6.0.1 | 3.8 | 0.6.2-cuda10.1-py38-runtime |
| cuda-10.2 + cudnn-8.2.0 + tensorrt-7.1.3 | 3.6 | 0.6.2-cuda10.2-py36-runtime |
| cuda-10.2 + cudnn-8.2.0 + tensorrt-7.1.3 | 3.7 | 0.6.2-cuda10.2-py37-runtime |
| cuda-10.2 + cudnn-8.2.0 + tensorrt-7.1.3 | 3.8 | 0.6.2-cuda10.2-py38-runtime |
| cuda-11 + cudnn-8.0.5 + tensorrt-7.1.3 | 3.6 | 0.6.2-cuda11-py36-runtime |
| cuda-11 + cudnn-8.0.5 + tensorrt-7.1.3 | 3.7 | 0.6.2-cuda11-py37-runtime |
| cuda-11 + cudnn-8.0.5 + tensorrt-7.1.3 | 3.8 | 0.6.2-cuda11-py38-runtime |
**注意事项：** 如果您在0.5.0及以上版本需要在一个容器当中同时运行CPU server和GPU server，需要选择Cuda10.1/10.2/11的镜像，因为他们和CPU环境有着相同版本的gcc。
doc/Docker_Images_EN.md
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......@@ -8,10 +8,10 @@ This document maintains a list of docker images provided by Paddle Serving.
You can get images in two ways:
1. Pull image directly from `registry.baidubce.com ` through TAG:
1. Pull image directly from dockerhub or `registry.baidubce.com ` through TAG:
```shell
docker pull registry.baidubce.com/paddlepaddle/serving:<TAG> # registry.baidubce.com
docker pull docker pull paddlepaddle/serving:<TAG> # if it is slow connection to dockerhub, please try registry.baidubce.com
```
2. Building image based on dockerfile
......@@ -19,25 +19,28 @@ You can get images in two ways:
Create a new folder and copy Dockerfile to this folder, and run the following command:
```shell
docker build -f ${DOCKERFILE} -t <image-name>:<images-tag> .
docker build -f tools/${DOCKERFILE} -t <image-name>:<images-tag> .
```
## Image description
Runtime images cannot be used for compilation.
If you want to customize your Serving based on source code, use the version with the suffix - devel.
**cuda10.1-cudnn7-gcc54 image is not ready, you should run from dockerfile if you need it.**
| Description | OS | TAG | Dockerfile |
If you need to develop and compile based on the source code, please use the version with the suffix -devel.
**In the TAG column, 0.7.0 can also be replaced with the corresponding version number, such as 0.5.0/0.4.1, etc., but it should be noted that some development environments only increase with a certain version iteration, so not all environments All have the corresponding version number can be used.**
| Description | OS | TAG | Dockerfile |
| :----------------------------------------------------------: | :-----: | :--------------------------: | :----------------------------------------------------------: |
| CPU development | Ubuntu16 | latest-devel | [Dockerfile.devel](../tools/Dockerfile.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development | Ubuntu16 | latest-cuda10.1-cudnn7-gcc54-devel(not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6) development | Ubuntu16 | latest-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
| GPU (cuda10.2-cudnn8-tensorRT7) development | Ubuntu16 | latest-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
| GPU (cuda11.2-cudnn8-tensorRT7) development | Ubuntu18 | latest-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
| CPU development | Ubuntu16 | 0.7.0-devel | [Dockerfile.devel](../tools/Dockerfile.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development | Ubuntu16 | 0.7.0-cuda10.1-cudnn7-gcc54-devel (not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6) development | Ubuntu16 | 0.7.0-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
| GPU (cuda10.2-cudnn7-tensorRT6) development | Ubuntu16 | 0.7.0-cuda10.2-cudnn7-devel | [Dockerfile.cuda10.2-cudnn7.devel](../tools/Dockerfile.cuda10.2-cudnn7.devel) |
| GPU (cuda10.2-cudnn8-tensorRT7) development | Ubuntu16 | 0.7.0-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
| GPU (cuda11.2-cudnn8-tensorRT8) development | Ubuntu16 | 0.7.0-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
**Java Client:**
```
......@@ -64,34 +67,20 @@ Develop Images:
| Env | Version | Docker images tag | OS | Gcc Version |
|----------|---------|------------------------------|-----------|-------------|
| CPU | >=0.5.0 | 0.6.2-devel | Ubuntu 16 | 8.2.0 |
| CPU | >=0.5.0 | 0.7.0-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.4.0-devel | CentOS 7 | 4.8.5 |
| Cuda10.1 | >=0.5.0 | 0.6.2-cuda10.1-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | 0.6.2 | 0.6.2-cuda10.1-cudnn7-gcc54-devel(not ready) | Ubuntu 16 | 5.4.0 |
| | <=0.4.0 | 0.6.2-cuda10.1-cudnn7-devel | CentOS 7 | 4.8.5 |
| Cuda10.2 | >=0.5.0 | 0.6.2-cuda10.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| Cuda10.1 | >=0.5.0 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.4.0-cuda10.1-cudnn7-devel | CentOS 7 | 4.8.5 |
| Cuda10.2+Cudnn7 | >=0.5.0 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
| Cuda10.2+Cudnn8 | >=0.5.0 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
| Cuda11.0 | >=0.5.0 | 0.6.2-cuda11.0-cudnn8-devel | Ubuntu 18 | 8.2.0 |
| Cuda11.2 | >=0.5.0 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
Running Images:
Running Images is lighter than Develop Images, and Running Images are made up with serving whl and bin, but without develop tools like cmake because of lower image size. If you want to know about it, plese check the document [Paddle Serving on Kubernetes.](./Run_On_Kubernetes_CN.md).
| ENV | Python Version | Tag |
|------------------------------------------|----------------|-----------------------------|
| cpu | 3.6 | 0.6.2-py36-runtime |
| cpu | 3.7 | 0.6.2-py37-runtime |
| cpu | 3.8 | 0.6.2-py38-runtime |
| cuda-10.1 + cudnn-7.6.5 + tensorrt-6.0.1 | 3.6 | 0.6.2-cuda10.1-py36-runtime |
| cuda-10.1 + cudnn-7.6.5 + tensorrt-6.0.1 | 3.7 | 0.6.2-cuda10.1-py37-runtime |
| cuda-10.1 + cudnn-7.6.5 + tensorrt-6.0.1 | 3.8 | 0.6.2-cuda10.1-py38-runtime |
| cuda-10.2 + cudnn-8.2.0 + tensorrt-7.1.3 | 3.6 | 0.6.2-cuda10.2-py36-runtime |
| cuda-10.2 + cudnn-8.2.0 + tensorrt-7.1.3 | 3.7 | 0.6.2-cuda10.2-py37-runtime |
| cuda-10.2 + cudnn-8.2.0 + tensorrt-7.1.3 | 3.8 | 0.6.2-cuda10.2-py38-runtime |
| cuda-11 + cudnn-8.0.5 + tensorrt-7.1.3 | 3.6 | 0.6.2-cuda11-py36-runtime |
| cuda-11 + cudnn-8.0.5 + tensorrt-7.1.3 | 3.7 | 0.6.2-cuda11-py37-runtime |
| cuda-11 + cudnn-8.0.5 + tensorrt-7.1.3 | 3.8 | 0.6.2-cuda11-py38-runtime |
**Tips:** If you want to use CPU server and GPU server (version>=0.5.0) at the same time, you should check the gcc version, only Cuda10.1/10.2/11 can run with CPU server owing to the same gcc version(8.2).
doc/FAQ_CN.md
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......@@ -142,7 +142,7 @@ make: *** [all] Error 2
#### Q：使用过程中出现CXXABI错误。
这个问题出现的原因是Python使用的gcc版本和Serving所需的gcc版本对不上。对于Docker用户，推荐使用[Docker容器](./Run_In_Docker_CN.md)，由于Docker容器内的Python版本与Serving在发布前都做过适配，这样就不会出现类似的错误。如果是其他开发环境，首先需要确保开发环境中具备GCC 8.2，如果没有gcc 8.2，参考安装方式
这个问题出现的原因是Python使用的gcc版本和Serving所需的gcc版本对不上。对于Docker用户，推荐使用[Docker容器](https://github.com/PaddlePaddle/Serving/blob/develop/doc/Docker_Images_CN.md)，由于Docker容器内的Python版本与Serving在发布前都做过适配，这样就不会出现类似的错误。如果是其他开发环境，首先需要确保开发环境中具备GCC 8.2，如果没有gcc 8.2，参考安装方式
```bash
wget -q https://paddle-ci.gz.bcebos.com/gcc-8.2.0.tar.xz
......@@ -236,7 +236,7 @@ InvalidArgumentError: Device id must be less than GPU count, but received id is:
#### Q: python编译的GCC版本与serving的版本不匹配
**A:**:1)使用[GPU docker](https://github.com/PaddlePaddle/Serving/blob/develop/doc/Run_In_Docker_CN.md#gpunvidia-docker)解决环境问题；2)修改anaconda的虚拟环境下安装的python的gcc版本[改变python的GCC编译环境](https://www.jianshu.com/p/c498b3d86f77)
**A:**:1)使用GPU Dockers, [这里是Docker镜像列表](https://github.com/PaddlePaddle/Serving/blob/develop/doc/Docker_Images_CN.md)解决环境问题；2)修改anaconda的虚拟环境下安装的python的gcc版本[改变python的GCC编译环境](https://www.jianshu.com/p/c498b3d86f77)
#### Q: paddle-serving是否支持本地离线安装
......
doc/Install_CN.md
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......@@ -2,7 +2,7 @@
(简体中文|[English](./Install_EN.md))
**强烈建议**您在**Docker内构建**Paddle Serving，请查看[如何在Docker中运行PaddleServing](Run_In_Docker_CN.md)。更多镜像请查看[Docker镜像列表](Docker_Images_CN.md)。
**强烈建议**您在**Docker内构建**Paddle Serving，更多镜像请查看[Docker镜像列表](Docker_Images_CN.md)。
**提示-1**：本项目仅支持<mark>**Python3.6/3.7/3.8**</mark>，接下来所有的与Python/Pip相关的操作都需要选择正确的Python版本。
......
doc/Install_EN.md
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......@@ -2,7 +2,7 @@
([简体中文](./Install_CN.md)|English)
**Strongly recommend** you build **Paddle Serving** in Docker, please check [How to run PaddleServing in Docker](Run_In_Docker_CN.md). For more images, please refer to [Docker Image List](Docker_Images_CN.md).
**Strongly recommend** you build **Paddle Serving** in Docker. For more images, please refer to [Docker Image List](Docker_Images_CN.md).
**Tip-1**: This project only supports <mark>**Python3.6/3.7/3.8**</mark>, all subsequent operations related to Python/Pip need to select the correct Python version.
......
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# 如何在Docker中运行PaddleServing
(简体中文|[English](Run_In_Docker_EN.md))
Docker最大的好处之一就是可移植性，可在多种操作系统和主流的云计算平台部署。使用Paddle Serving Docker镜像可在Linux、Mac和Windows平台部署。
## 环境要求
Docker（GPU版本需要在GPU机器上安装nvidia-docker）
该文档以Python2为例展示如何在Docker中运行Paddle Serving，您也可以通过将`python`更换成`python3`来用Python3运行相关命令。
## CPU版本
### 获取镜像
参考[该文档](Docker_Images_CN.md)获取镜像：
以CPU编译镜像为例
```shell
docker pull registry.baidubce.com/paddlepaddle/serving:latest-devel
```
### 创建容器并进入
```bash
docker run -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:latest-devel
docker exec -it test bash
```
`-p`选项是为了将容器的`9292`端口映射到宿主机的`9292`端口。
### 安装PaddleServing
镜像里自带对应镜像tag版本的`paddle_serving_server`，`paddle_serving_client`，`paddle_serving_app`，如果用户不需要更改版本，可以直接使用，适用于没有外网服务的环境。
如果需要更换版本，请参照首页的指导，下载对应版本的pip包。
## GPU 版本
```shell
docker pull registry.baidubce.com/paddlepaddle/serving:latest-cuda10.2-cudnn8-devel
```
### 创建容器并进入
```bash
nvidia-docker run -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:latest-cuda10.2-cudnn8-devel
nvidia-docker exec -it test bash
```
或者
```bash
docker run --gpus all -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:latest-cuda10.2-cudnn8-devel
docker exec -it test bash
```
`-p`选项是为了将容器的`9292`端口映射到宿主机的`9292`端口。
### 安装PaddleServing
请参照首页的指导，下载对应版本的pip包。[最新安装包合集](Latest_Packages_CN.md)
## 注意事项
- 运行时镜像不能用于开发编译。如果想要从源码编译，请查看[如何编译PaddleServing](Compile_CN.md)。
- 由于Cuda10和Cuda9的环境受限于GCC版本，无法同时运行CPU版本的`paddle_serving_server`，因此如果想要在GPU环境中同时使用CPU版本的`paddle_serving_server`，请选择Cuda10.1，Cuda10.2和Cuda11版本的镜像。
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# How to run PaddleServing in Docker
([简体中文](Run_In_Docker_CN.md)|English)
One of the biggest benefits of Docker is portability, which can be deployed on multiple operating systems and mainstream cloud computing platforms. The Paddle Serving Docker image can be deployed on Linux, Mac and Windows platforms.
## Requirements
Docker (GPU version requires nvidia-docker to be installed on the GPU machine)
This document takes Python2 as an example to show how to run Paddle Serving in docker. You can also use Python3 to run related commands by replacing `python` with `python3`.
## CPU
### Get docker image
Refer to [this document](Docker_Images_EN.md) for a docker image:
```shell
docker pull registry.baidubce.com/paddlepaddle/serving:latest-devel
```
### Create container
```bash
docker run -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:latest-devel
docker exec -it test bash
```
The `-p` option is to map the `9292` port of the container to the `9292` port of the host.
### Install PaddleServing
Please refer to the instructions on the homepage to download the pip package of the corresponding version.
## GPU
The GPU version is basically the same as the CPU version, with only some differences in interface naming (GPU version requires nvidia-docker to be installed on the GPU machine).
### Get docker image
Refer to [this document](Docker_Images_EN.md) for a docker image, the following is an example of an `cuda9.0-cudnn7` image:
```shell
docker pull registry.baidubce.com/paddlepaddle/serving:latest-cuda10.2-cudnn8-devel
```
### Create container
```bash
nvidia-docker run -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:latest-cuda10.2-cudnn8-devel
nvidia-docker exec -it test bash
```
or
```bash
docker run --gpus all -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:latest-cuda10.2-cudnn8-devel
docker exec -it test bash
```
The `-p` option is to map the `9292` port of the container to the `9292` port of the host.
### Install PaddleServing
The mirror comes with `paddle_serving_server_gpu`, `paddle_serving_client`, and `paddle_serving_app` corresponding to the mirror tag version. If users don’t need to change the version, they can use it directly, which is suitable for environments without extranet services.
If you need to change the version, please refer to the instructions on the homepage to download the pip package of the corresponding version. [LATEST_PACKAGES](./Latest_Packages_CN.md)
## Precautious
- Runtime images cannot be used for compilation. If you want to compile from source, refer to [COMPILE](Compile_EN.md).
- If you use Cuda9 and Cuda10 docker images, you cannot use `paddle_serving_server` CPU version at the same time, due to the limitation of gcc version. If you want to use both in one docker image, please choose images of Cuda10.1, Cuda10.2 and Cuda11.
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