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This document maintains a list of docker images provided by Paddle Serving.

Get docker image

You can get images in two ways:

1. Pull image directly from dockerhub or registry.baidubce.com through TAG:

   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

   Create a new folder and copy Dockerfile to this folder, and run the following command:

   docker build -f tools/${DOCKERFILE} -t <image-name>:<images-tag> .
   

Image description

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.

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	0.7.0-devel	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
GPU (cuda10.1-cudnn7-tensorRT6) development	Ubuntu16	0.7.0-cuda10.1-cudnn7-devel	Dockerfile.cuda10.1-cudnn7.devel
GPU (cuda10.2-cudnn7-tensorRT6) development	Ubuntu16	0.7.0-cuda10.2-cudnn7-devel	Dockerfile.cuda10.2-cudnn7.devel
GPU (cuda10.2-cudnn8-tensorRT7) development	Ubuntu16	0.7.0-cuda10.2-cudnn8-devel	Dockerfile.cuda10.2-cudnn8.devel
GPU (cuda11.2-cudnn8-tensorRT8) development	Ubuntu16	0.7.0-cuda11.2-cudnn8-devel	Dockerfile.cuda11.2-cudnn8.devel

Java Client:

registry.baidubce.com/paddlepaddle/serving:latest-java

XPU:

registry.baidubce.com/paddlepaddle/serving:xpu-arm # for arm xpu user
registry.baidubce.com/paddlepaddle/serving:xpu-x86 # for x86 xpu user

Requirements for running CUDA containers

Running a CUDA container requires a machine with at least one CUDA-capable GPU and a driver compatible with the CUDA toolkit version you are using.

The machine running the CUDA container only requires the NVIDIA driver, the CUDA toolkit does not have to be installed.

For the relationship between CUDA toolkit version, Driver version and GPU architecture, please refer to nvidia-docker wiki.

(Attachment) The List of All the Docker images

Develop Images:

Env	Version	Docker images tag	OS	Gcc Version
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	0.7.0-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
Cuda11.2	>=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..