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Contribute to DeepSaki

There are many ways to contribute to DeepSaki and every help is well appreciated!
I especially want to encourage students and those of you eager to learn to code or to advance your skills in the exiting field of deep learning. DeepSaki started as a project to learn and improve my skills and I hope it might help some of you too!

Make youre first contribution

  • Create a feature request
  • Report Issues
  • Write code
  • Add or improve test
  • improve the documentation
  • contribute example notebooks

Install the Dev Environment

The eseaist way is to install the provided docker container, which requires you to have docker installed with nvidia gpu support.

  1. build the image: 

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    $ docker build --build-arg HTTP_PROXY -t deepsaki -f Dockerfile .

  2. Create an container 

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    $ docker container create --gpus all --name deepsaki -p 8888:8888 -v ~/git/sascha-kirch/DeepSaki:/deepsaki -it deepsaki

  3. start container 

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    $ docker container start -i deepsaki

Before you create a PR

  • Review your contribution
  • Run unit test with $> pytest
  • Run the code formater with $> black .
  • check for errors and fix fixable ones with $> ruff check --fix .