ai2ys/tensorflow repository overview

⁠TensorFlow docker images using JupyterLab instead of plain jupyter

The here available docker images were created using the dockerfiles from the following fork of the TensorFlow project⁠: https://github.com/ai2ys/tensorflow⁠.
I followed the instruction of the TensorFlow authors and added the file corresponding partial file for JupyterLab⁠ and edited the spec.yml and followed their instructions for building the images.
Thanks to the TensorFlow authors for making this possible.

The original docker images from the TensorFlow team are available here : tensorflow/tensorflow⁠.

⁠Tag names available in this repository

Check out the available tags on the 'Tags' tab⁠. Multiple versions are available and images with and without gpu support.

All here available docker images use pyton3 and jupyterlab. I only build docker images with the following options:

• <version>-gpu-py3-jupyterlab
• <version>-py3-jupyterlab

⁠Tag name example 2.0.0-py3-jupyterlab

docker pull ai2ys/tensorflow:2.0.0-py3-jupyterlab

This image was build using the options:

• TensorFlow version 2.0.0
• CPU only (without GPU support)
• Python3
• JupyterLab

The only difference compared to the docker image with tag tensorflow/tensorflow:2.0.0-py3-jupyter from the the TensorFlow team⁠ is that it makes use of JupyterLab instead of plain jupyter.

$ docker run -it --rm -v $(realpath ~/notebooks):/tf/notebooks -p 8888:8888 ai2ys/tensorflow:2.0.0-py3-jupyterlab

⁠Tag name example 2.0.0-gpu-py3-jupyterlab

docker pull ai2ys/tensorflow:2.0.0-gpu-py3-jupyterlab

This image was build using the options:

• TensorFlow version 2.0.0
• GPU support
• Python3
• JupyterLab

The only difference compared to the docker image with tag tensorflow/tensorflow:2.0.0-gpu-py3-jupyter from the the TensorFlow team⁠ is that it makes use of JupyterLab instead of plain jupyter.

$ docker run -it --rm --gpus all -v $(realpath ~/notebooks):/tf/notebooks -p 8888:8888 ai2ys/tensorflow:2.0.0-gpu-py3-jupyterlab

Remark: In case you want to make use of the GPU support, do not forget to check if you followed the instruction of the NVIDA team for nvidia-docker on GitHub⁠.