Skip to content

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

License

Notifications You must be signed in to change notification settings

x-and-ai/tfhub-cuda

Repository files navigation

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

About

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

Resources

License

Stars

Watchers

Forks

Packages

No packages published