Skip to content

Latest commit

 

History

History
46 lines (27 loc) · 1.05 KB

install_EN.md

File metadata and controls

46 lines (27 loc) · 1.05 KB
Raw

AGL Installation Guide

AGL currently primarily provides its functionality through images, encompassing both compilation and runtime environments.

Docker Image

aglimage/agl:agl-ubuntu-gcc9.4.0-py3.8-cuda11.8-pytorch2.0.1-0825

The image contains all the dependencies required to run AGL, including Java, Maven, Spark, Pytorch, PyG, and Cuda. Users no longer need to worry about environment configuration within the Docker container.

Installation Steps:

1. Clone the code

git clone https://github.com/TuGraph-family/TuGraph-AntGraphLearning.git

2. Start Docker

cd docker
bash start_docker_with_image.sh

The script to start the docker container link

3. Compile the Source Code

bash build.sh

By executing this script, a whl package will be compiled based on the current branch and installed in the current Docker, replacing any existing installation. The whl package can be found in the dist directory and is typically named agl-0.0.1-cp38-cp38-linux_x86_64.whl.