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Compile doc， install doc, and suffix 1027->102
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TeslaZhao authored Nov 15, 2021
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**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)。

**提示**：目前paddlepaddle 2.1版本的默认GPU环境是Cuda 10.2，因此GPU Docker的示例代码以Cuda 10.2为准。镜像和pip安装包也提供了其余GPU环境，用户如果使用其他环境，需要仔细甄别并选择合适的版本。
**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。

**提示**：本项目仅支持Python3.6/3.7/3.8，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。
**提示-2**：以下示例中GPU环境均为cuda10.2-cudnn7，如果您使用Python Pipeline来部署，并需要Nvidia TensorRT来优化预测性能，请参考[支持的镜像环境和说明](#4支持的镜像环境和说明)来选择其他版本。


## 1.启动开发镜像
<mark>**同时支持使用Serving镜像和Paddle镜像，1.1和1.2章节中的操作2选1即可。**</mark>
### 1.1 Serving开发镜像（CPU/GPU 2选1）
**CPU：**
```
# 启动 CPU Docker
docker pull registry.baidubce.com/paddlepaddle/serving:0.6.2-devel
docker run -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:0.6.2-devel bash
docker pull paddlepaddle/serving:0.7.0-devel
docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.7.0-devel bash
docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```
**GPU：**
```
# 启动 GPU Docker
nvidia-docker pull registry.baidubce.com/paddlepaddle/serving:0.6.2-cuda10.2-cudnn8-devel
nvidia-docker run -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:0.6.2-cuda10.2-cudnn8-devel bash
docker pull paddlepaddle/serving:0.7.0-cuda10.2-cudnn7-devel
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.7.0-cuda10.2-cudnn7-devel bash
nvidia-docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```
### 1.2 Paddle开发镜像（CPU/GPU 2选1）
**CPU：**
```
# 启动 CPU Docker
docker pull paddlepaddle/paddle:2.2.0
docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0 bash
docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
# Paddle开发镜像需要执行以下脚本增加Serving所需依赖项
bash Serving/tools/paddle_env_install.sh
```
**GPU：**
```
# 启动 GPU Docker
docker pull paddlepaddle/paddle:2.2.0-cuda10.2-cudnn7
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0-cuda10.2-cudnn7 bash
nvidia-docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
# Paddle开发镜像需要执行以下脚本增加Serving所需依赖项
bash Serving/tools/paddle_env_install.sh
```
## 2.安装Paddle Serving相关Python库

安装所需的pip依赖
```
Expand All @@ -30,13 +60,13 @@ pip3 install -r python/requirements.txt
```

```shell
pip3 install paddle-serving-client==0.6.2
pip3 install paddle-serving-server==0.6.2 # CPU
pip3 install paddle-serving-app==0.6.2
pip3 install paddle-serving-server-gpu==0.6.2.post102 #GPU with CUDA10.2 + TensorRT7
pip3 install paddle-serving-client==0.7.0
pip3 install paddle-serving-server==0.7.0 # CPU
pip3 install paddle-serving-app==0.7.0
pip3 install paddle-serving-server-gpu==0.7.0.post102 #GPU with CUDA10.2 + TensorRT6
# 其他GPU环境需要确认环境再选择执行哪一条
pip3 install paddle-serving-server-gpu==0.6.2.post101 # GPU with CUDA10.1 + TensorRT6
pip3 install paddle-serving-server-gpu==0.6.2.post11 # GPU with CUDA10.1 + TensorRT7
pip3 install paddle-serving-server-gpu==0.7.0.post101 # GPU with CUDA10.1 + TensorRT6
pip3 install paddle-serving-server-gpu==0.7.0.post112 # GPU with CUDA11.2 + TensorRT8
```

您可能需要使用国内镜像源（例如清华源, 在pip命令中添加`-i https://pypi.tuna.tsinghua.edu.cn/simple`）来加速下载。
Expand All @@ -47,26 +77,28 @@ paddle-serving-server和paddle-serving-server-gpu安装包支持Centos 6/7, Ubun

paddle-serving-client和paddle-serving-app安装包支持Linux和Windows，其中paddle-serving-client仅支持python3.6/3.7/3.8。

**最新的0.6.2的版本，已经不支持Cuda 9.0和Cuda 10.0，Python已不支持2.7和3.5。**

推荐安装2.1.0及以上版本的paddle

## 3.安装Paddle相关Python库
**当您使用`paddle_serving_client.convert`命令或者`Python Pipeline框架`时才需要安装。**
```
# CPU环境请执行
pip3 install paddlepaddle==2.1.0
pip3 install paddlepaddle==2.2.0
# GPU Cuda10.2环境请执行
pip3 install paddlepaddle-gpu==2.1.0
pip3 install paddlepaddle-gpu==2.2.0
```
**注意**： 如果您的Cuda版本不是10.2，请勿直接执行上述命令，需要参考[Paddle-Inference官方文档-下载安装Linux预测库](https://paddleinference.paddlepaddle.org.cn/master/user_guides/download_lib.html#python)选择相应的GPU环境的url链接并进行安装。

**注意**： 如果您的Cuda版本不是10.2，请勿直接执行上述命令，需要参考[Paddle官方文档-多版本whl包列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-release)

选择相应的GPU环境的url链接并进行安装，例如Cuda 10.1的Python3.6用户，请选择表格当中的`cp36-cp36m`和`cuda10.1-cudnn7-mkl-gcc8.2-avx-trt6.0.1.5`对应的url，复制下来并执行
例如Cuda 10.1的Python3.6用户，请选择表格当中的`cp36-cp36m`和`linux-cuda10.1-cudnn7.6-trt6-gcc8.2`对应的url，复制下来并执行
```
pip3 install https://paddle-wheel.bj.bcebos.com/with-trt/2.1.0-gpu-cuda10.1-cudnn7-mkl-gcc8.2/paddlepaddle_gpu-2.1.0.post101-cp36-cp36m-linux_x86_64.whl
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.0.post101-cp36-cp36m-linux_x86_64.whl
```
由于默认的`paddlepaddle-gpu==2.1.0`是Cuda 10.2，并没有联编TensorRT，因此如果需要和在`paddlepaddle-gpu`上使用TensorRT，需要在上述多版本whl包列表当中，找到`cuda10.2-cudnn8.0-trt7.1.3`，下载对应的Python版本

如果是其他环境和Python版本，请在表格中找到对应的链接并用pip安装。
## 4.支持的镜像环境和说明
| 环境 | Serving开发镜像Tag | 操作系统 | Paddle开发镜像Tag | 操作系统 |
| :--------------------------: | :-------------------------------: | :-------------: | :-------------------: | :----------------: |
| CPU | 0.7.0-devel | Ubuntu 16.04 | 2.2.0 | Ubuntu 18.04. |
| Cuda10.1+Cudnn7 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda10.2+Cudnn7 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.0-cuda10.2-cudnn7 | Ubuntu 16.04 |
| Cuda10.2+Cudnn8 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda11.2+Cudnn8 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.0-cuda11.2-cudnn8 | Ubuntu 18.04 |

对于**Windows 10 用户**，请参考文档[Windows平台使用Paddle Serving指导](Windows_Tutorial_CN.md)。
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([简体中文](./Install_CN.md)|English)

We **highly recommend** you to **run Paddle Serving in Docker**, please visit [Run in Docker](Run_In_Docker_EN.md). See the [document](./Docker_Images_EN.md) for more docker images.
**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).

**Attention:**: Currently, the default GPU environment of paddlepaddle 2.1 is Cuda 10.2, so the sample code of GPU Docker is based on Cuda 10.2. We also provides docker images and whl packages for other GPU environments. If users use other environments, they need to carefully check and select the appropriate version.
**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.

**Attention:** the following so-called 'python' or 'pip' stands for one of Python 3.6/3.7/3.8.
**Tip-2**: The GPU environments in the following examples are all cuda10.2-cudnn7. If you use Python Pipeline to deploy and need Nvidia TensorRT to optimize prediction performance, please refer to [Supported Mirroring Environment and Instructions](#4.-Supported-Docker-Images-and-Instruction) to choose other versions.

## 1. Start the Docker Container
<mark>**Both Serving Dev Image and Paddle Dev Image are supported at the same time. You can choose 1 from the operation 2 in chapters 1.1 and 1.2.**</mark>

### 1.1 Serving Dev Images (CPU/GPU 2 choose 1)
**CPU:**
```
# Run CPU Docker
docker pull registry.baidubce.com/paddlepaddle/serving:0.6.0-devel
docker run -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:0.6.0-devel bash
# Start CPU Docker Container
docker pull paddlepaddle/serving:0.7.0-devel
docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.7.0-devel bash
docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```
**GPU:**
```
# Run GPU Docker
nvidia-docker pull registry.baidubce.com/paddlepaddle/serving:0.6.0-cuda10.2-cudnn8-devel
nvidia-docker run -p 9292:9292 --name test -dit registry.baidubce.com/paddlepaddle/serving:0.6.0-cuda10.2-cudnn8-devel bash
# Start GPU Docker Container
docker pull paddlepaddle/serving:0.7.0-cuda10.2-cudnn7-devel
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.7.0-cuda10.2-cudnn7-devel bash
nvidia-docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```
install python dependencies
```
cd Serving
pip install -r python/requirements.txt
### 1.2 Paddle Dev Images (choose any codeblock of CPU/GPU)
**CPU:**
```
# Start CPU Docker Container
docker pull paddlepaddle/paddle:2.2.0
docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0 bash
docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```shell
pip install paddle-serving-client==0.6.0
pip install paddle-serving-server==0.6.0 # CPU
pip install paddle-serving-app==0.6.0
pip install paddle-serving-server-gpu==0.6.0.post102 #GPU with CUDA10.2 + TensorRT7
# DO NOT RUN ALL COMMANDS! check your GPU env and select the right one
pip install paddle-serving-server-gpu==0.6.0.post101 # GPU with CUDA10.1 + TensorRT6
pip install paddle-serving-server-gpu==0.6.0.post11 # GPU with CUDA10.1 + TensorRT7
# Paddle dev image needs to run the following script to increase the dependencies required by Serving
bash Serving/tools/paddle_env_install.sh
```
**GPU:**
```
# Start GPU Docker
docker pull paddlepaddle/paddle:2.2.0-cuda10.2-cudnn7
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0-cuda10.2-cudnn7 bash
nvidia-docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
# Paddle development image needs to execute the following script to increase the dependencies required by Serving
bash Serving/tools/paddle_env_install.sh
```

You may need to use a domestic mirror source (in China, you can use the Tsinghua mirror source, add `-i https://pypi.tuna.tsinghua.edu.cn/simple` to pip command) to speed up the download.
## 2. Install Paddle Serving related whl Packages

If you need install modules compiled with develop branch, please download packages from [latest packages list](./Latest_Packages_CN.md) and install with `pip install` command. If you want to compile by yourself, please refer to [How to compile Paddle Serving?](Compile_EN.md)
Install the required pip dependencies
```
cd Serving
pip3 install -r python/requirements.txt
```

Packages of paddle-serving-server and paddle-serving-server-gpu support Centos 6/7, Ubuntu 16/18, Windows 10.
```shell
pip3 install paddle-serving-client==0.7.0
pip3 install paddle-serving-server==0.7.0 # CPU
pip3 install paddle-serving-app==0.7.0
pip3 install paddle-serving-server-gpu==0.7.0.post102 #GPU with CUDA10.2 + TensorRT6
# Other GPU environments need to confirm the environment before choosing which one to execute
pip3 install paddle-serving-server-gpu==0.7.0.post101 # GPU with CUDA10.1 + TensorRT6
pip3 install paddle-serving-server-gpu==0.7.0.post112 # GPU with CUDA11.2 + TensorRT8
```

Packages of paddle-serving-client and paddle-serving-app support Linux and Windows, but paddle-serving-client only support python3.6/3.7/3.8.
If you are in China, You may need to use a chinese mirror source (such as Tsinghua source, add `-i https://pypi.tuna.tsinghua.edu.cn/simple` to the pip command) to speed up the download.

**For latest version, Cuda 9.0 or Cuda 10.0 are no longer supported, Python2.7/3.5 is no longer supported.**
If you need to use the installation package compiled by the develop branch, please download the download address from [Latest installation package list](./Latest_Packages_CN.md), and use the `pip install` command to install. If you want to compile by yourself, please refer to [Paddle Serving Compilation Document](./Compile_CN.md).

Recommended to install paddle >= 2.1.0
The paddle-serving-server and paddle-serving-server-gpu installation packages support Centos 6/7, Ubuntu 16/18 and Windows 10.

The paddle-serving-client and paddle-serving-app installation packages support Linux and Windows, and paddle-serving-client only supports python3.6/3.7/3.8.

## 3. Install Paddle related Python libraries
**You only need to install it when you use the `paddle_serving_client.convert` command or the `Python Pipeline framework`. **
```
# CPU users, please run
pip install paddlepaddle==2.1.0
# CPU environment please execute
pip3 install paddlepaddle==2.2.0
# GPU Cuda10.2 please run
pip install paddlepaddle-gpu==2.1.0
# GPU Cuda10.2 environment please execute
pip3 install paddlepaddle-gpu==2.2.0
```
**Note**: If your Cuda version is not 10.2, please do not execute the above commands directly, you need to refer to [Paddle-Inference official document-download and install the Linux prediction library](https://paddleinference.paddlepaddle.org.cn/master/user_guides/download_lib.html#python) Select the URL link of the corresponding GPU environment and install it.

**Note**: If your Cuda version is not 10.2, please do not execute the above commands directly, you need to refer to [Paddle official documentation-multi-version whl package list
](https://www.paddlepaddle.org.cn/documentation/docs/en/install/Tables_en.html#multi-version-whl-package-list-release)
Select the url link of the corresponding GPU environment and install it. For example, for Python3.6 users of Cuda 10.1, please select `cp36-cp36m` and
The url corresponding to `cuda10.1-cudnn7-mkl-gcc8.2-avx-trt6.0.1.5`, copy it and run
For example, for Python3.6 users of Cuda 10.1, please select the URL corresponding to `cp36-cp36m` and `linux-cuda10.1-cudnn7.6-trt6-gcc8.2` in the table, copy it and execute
```
pip install https://paddle-wheel.bj.bcebos.com/with-trt/2.1.0-gpu-cuda10.1-cudnn7-mkl-gcc8.2/paddlepaddle_gpu-2.1.0.post101-cp36-cp36m-linux_x86_64.whl
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.0.post101 -cp36-cp36m-linux_x86_64.whl
```
## 4. Supported Docker Images and Instruction

the default `paddlepaddle-gpu==2.1.0` is Cuda 10.2 with no TensorRT. If you want to install PaddlePaddle with TensorRT. please also check the documentation-multi-version whl package list and find key word `cuda10.2-cudnn8.0-trt7.1.3`.
If it is other environment and Python version, please find the corresponding link in the table and install it with pip.
For **Windows Users**, please read the document [Paddle Serving for Windows Users](Windows_Tutorial_EN.md)

<h2 align="center">Quick Start Example</h2>
| Environment | Serving Development Image Tag | Operating System | Paddle Development Image Tag | Operating System |
| :--------------------------: | :-------------------------------: | :-------------: | :-------------------: | :----------------: |
| CPU | 0.7.0-devel | Ubuntu 16.04 | 2.2.0 | Ubuntu 18.04. |
| Cuda10.1+Cudnn7 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda10.2+Cudnn7 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.0-cuda10.2-cudnn7 | Ubuntu 16.04 |
| Cuda10.2+Cudnn8 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda11.2+Cudnn8 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.0-cuda11.2-cudnn8 | Ubuntu 18.04 |

This quick start example is mainly for those users who already have a model to deploy, and we also provide a model that can be used for deployment. in case if you want to know how to complete the process from offline training to online service, please refer to the AiStudio tutorial above.
For **Windows 10 users**, please refer to the document [Paddle Serving Guide for Windows Platform](Windows_Tutorial_CN.md).
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进入到Serving的git目录下，进入到`fit_a_line`例子
``` shell
cd Serving/python/examples/fit_a_line
cd Serving/examples/C++/fit_a_line
sh get_data.sh
```

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Expand Up @@ -73,7 +73,7 @@ if (SERVER)
set(VERSION_SUFFIX 101)
elseif(CUDA_VERSION EQUAL 10.2)
if(CUDNN_MAJOR_VERSION EQUAL 7)
set(VERSION_SUFFIX 1027)
set(VERSION_SUFFIX 102)
elseif(CUDNN_MAJOR_VERSION EQUAL 8)
set(VERSION_SUFFIX 1028)
endif()
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2 changes: 1 addition & 1 deletion python/paddle_serving_server/server.py
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Expand Up @@ -429,7 +429,7 @@ def get_serving_bin_name(self):
if device_type == "0":
device_version = self.get_device_version()
elif device_type == "1":
if version_suffix == "101" or version_suffix == "1027" or version_suffix == "1028" or version_suffix == "112":
if version_suffix == "101" or version_suffix == "102" or version_suffix == "1028" or version_suffix == "112":
device_version = "gpu-" + version_suffix
else:
device_version = "gpu-cuda" + version_suffix
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