public:docker
Table of Contents
Last-updated: 2025/02/23 liangz
Docker tutorial
Step 1: Understand docker
- Read https://docs.docker.com/get-started/docker-overview/ and understand (docker) image, container, daemon, client, hub (registry), pull, push.
- Install docker (Linux Mint as example. Information on other OSes are welcome too.)
- $ sudo apt install docker.io
- Add your username to the “docker” group (or by editing /etc/group directly).
- $ sudo usermod -aG docker your_username
- Logout & login to make the change of group into effect, or simply reboot your Linux.
- Run a ubuntu container (docker client will automatically pull a ubuntu image and create a local container.). If you get a console with command prompt “root@xxxxxxxxxxxx:/,” it worked.
- $ docker run -i -t ubuntu /bin/bash
- Exit the container by exit (notice the prompt changed to “#”, showing you are the root)
- # exit
Step 2 (if you have an NVidia GPU): Install Nvidia GPU support
Step 3: Install PyTorch (for development)
- $ docker pull pytorch/pytorch:latest
- $ docker run –rm –gpus all pytorch/pytorch:latest python -c “import torch; print(torch.cuda.is_available())”
- If you see “True”, it worked.
Step 4: Work with PyTorch
- $ docker run -it –gpus all –rm pytorch/pytorch:latest bash
- # nvidia-smi
- If you see the use of your GPU, it worked.
References
- https://github.com/saikhu/Docker-Guide-for-AI-Model-Development-and-Deployment (Chapter 6 is obsolete. See the above Step 2 for the latest information)
public/docker.txt · Last modified: 2025/02/23 23:03 by liang