x-and-ai/tfhub-cuda

A nvidia-docker image for using TensorFlow on Linux servers with JupyterHub support

xandai/tfhub-cuda

Docker Hub Link

GitHub Link

Description

This is a nvidia-docker image for using TensorFlow on Linux servers with JupyterHub support.

This image also contains following Python modules:

NumPy (for low-level math operations) pandas (for data manipulation) scikit-learn (for evaluation metrics) imageio (for read and write images) Matplotlib (for data visualization) Seaborn (for heatmaps)

Tags and Versions

tag	tensorflow	jupyterhub	node	python	cuda
0.1.0	1.13.1	0.9.4	10.15.3	3.6.7	10.0-cudnn7-devel

Usage

1. Make sure you have following mountable directories

   • one for all jupyterhub files
   • one for all user files

2. To start a container

docker run --runtime=nvidia -d -t \
    -p <port>:8000 \
    -v <hub-files-dir>:/opt/jupyterhub \
    -v <user-files-dir>:/home \
    --name <container-name> \
    xandai/tfhub-cuda:0.1.0

1. To add a user

docker exec -it <container-name> bash -c "adduser <user-name>"

1. To start jupyterhub

docker exec -t -d <container-name> bash -c "jupyterhub &>> jupyterhub.log"

1. To enter terminal

docker exec -it <container-name> bash