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Install Paddle Serving with Docker

(简体中文|English)

Strongly recommend you build Paddle Serving in Docker. For more images, please refer to Docker Image List.

Tip-1: This project only supports Python3.6/3.7/3.8, all subsequent operations related to Python/Pip need to select the correct Python version.

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 to choose other versions.

1. Start the Docker Container

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.

1.1 Serving Dev Images (CPU/GPU 2 choose 1)

CPU:

# 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:

# 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

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

# 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-gpu-cuda10.2-cudnn7
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0-gpu-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

2. Install Paddle Serving stable wheel packages

Install the required pip dependencies

cd Serving
pip3 install -r python/requirements.txt

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

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.

If you need to use the installation package compiled by the develop branch, please download the download address from Latest installation package list, and use the pip install command to install. If you want to compile by yourself, please refer to Paddle Serving Compilation Document.

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 environment please execute
pip3 install paddlepaddle==2.2.0

# 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 Select the URL link of the corresponding GPU environment and install it.

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

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

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-gpu-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-gpu-cuda11.2-cudnn8 Ubuntu 18.04

For Windows 10 users, please refer to the document Paddle Serving Guide for Windows Platform.