jlphillips/csci4850 repository overview

⁠This container is out-dated

Please see jlphillips/csci for the new stack: https://hub.docker.com/repository/docker/jlphillips/csci/⁠

⁠CSCI4850

Docker container for CSCI 4850/5850 - Neural Networks (ver. 2023-01-04)

This container is built on top of jupyter/datascience-notebook provided by jupyter/docker-stacks. It provides a JupyterLab environment with several essential (and non-essential) tools used in CSCI4850/5850 - Neural Networks.

The recommended way to obtain the docker image is to pull from DockerHub:

docker pull jlphillips/csci4850:2023-Spring
docker run -it --rm -p 8888:8888 --user root -e JUPYTER_ENABLE_LAB=yes -e GRANT_SUDO=yes -v /home/jphillips:/home/jovyan/work jlphillips/csci4850:2023-Spring

You will need to modify /home/jphillips to instead indicate where your files are located in order to make this work...

If you would like to utilize Nvidia GPUs (drivers/cards supporting CUDA 11.6 or higher only), you will also need to make sure your Docker installation is set up to use the Nvidia container toolkit, as described here⁠, or just sudo apt-get install nvidia-container-toolkit if you are using the Lambda Stack on your host.

docker pull jlphillips/csci4850
docker run -it --rm -p 8888:8888 --user root --gpus all -e NVIDIA_VISIBLE_DEVICES=all -e JUPYTER_ENABLE_LAB=yes -e GRANT_SUDO=yes -v /home/jphillips:/home/jovyan/work jlphillips/csci4850:2023-Spring

However, if you want to build the image yourself, then do the following...

To prep:

git clone https://github.com/jlphillipsphd/CSCI4850.git

To build:

docker build -t csci4850 CSCI4850

To run:

docker run -it --rm -p 8888:8888 --user root -e JUPYTER_ENABLE_LAB=yes -e GRANT_SUDO=yes -v /home/jphillips:/home/jovyan/work csci4850