ubuntolog/vscode-tensorflow-gpu repository overview

⁠About

The image is based on code-server⁠ - an open source project that allows to run VSCode editor on a server. The editor becomes available in a browser: in certain cases it may be very useful. This particular image has been created for my experiments with neural networks. My plan is to train models on a server with a powerful GPU and a fast SSD, while using Mac OS. The server itself has to have NVIDIA drivers and Docker installed. The rest (e.g. CUDA libraries and other dependencies) is handled by the image.

⁠What you need to do to run the image

• Generate a self signed certificate and a key (or real ones, if you want to run code server on a real server): sudo openssl req -x509 -nodes -days 365 -newkey rsa:2048 -keyout /etc/ssl/private/nginx-selfsigned.key -out /etc/ssl/certs/nginx-selfsigned.crt

• Start the image with all the necessary volumes (to keep settings and data) docker run --gpus all -it -p 443:443 -v /home/user/vscode-server/vscode-server-settings/:/root/.local/share/code-server -v /home/user/vscode-server/vscode-server-data/:/root/data -v /etc/ssl/private/nginx-selfsigned.key:/root/cert.key -v /etc/ssl/certs/nginx-selfsigned.crt:/root/cert.crt ubuntolog/vscode-tensorflow-gpu:24.05.2020