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bootstrap.pytorch is a high-level extension for deep learning projects with PyTorch. It aims at accelerating research projects and prototyping by providing a powerful workflow focused on your dataset and model.

And it is:

Unlike many others, bootstrap.pytorch is not a wrapper over pytorch, but a powerful extension.

Quick tour

To run an experiment (training + evaluation):

python -m bootstrap.run
       -o myproject/options/sgd.yaml

To display parsed options from the yaml file:

python -m bootstrap.run
       -o myproject/options/sgd.yaml
       -h

Running an experiment will create 4 files, here is an example with mnist:

To save the next experiment in a specific directory:

python -m bootstrap.run
       -o myproject/options/sgd.yaml
       --exp.dir logs/custom

To reload an experiment:

python -m bootstrap.run
       -o logs/custom/options.yaml
       --exp.resume last

Documentation

The package reference is available on the documentation website.

It also contains some notes:

Official project modules

Poster

<a href="http://remicadene.com/bootstrap/_static/img/bootstrap_poster.pdf"><img src="http://remicadene.com/bootstrap/_static/img/bootstrap_poster_mini.png" width="20%"/></a>

Contribute

Contributions to this repository are welcome and encouraged. We also have a <a href="https://trello.com/b/ImvwlgId/features">public trello board</a> with prospect features, as well as an indication of those currently being developed. Feel free to contact us with suggestions, or send a pull request.

We use flake8 to perform early semantic checking of submitted code. After installing all the requirements in requirements.txt, please run the following to activate the pre-commit hooks for flake8: pre-commit install

To manually trigger the pre-commit checks for a file without creating a commit, you can run the following command: pre-commit run --files <your_files.py>

bootstrap.pytorch was conceived and is maintained by <a href="http://remicadene.com">Rémi Cadène</a> and <a href="http://micaelcarvalho.com">Micael Carvalho</a>, with helpful discussions and insights from <a href="http://www.thomas-robert.fr/en/">Thomas Robert</a> and <a href="https://twitter.com/labegne">Hedi Ben-Younes</a>. We chose to adopt the [very permissive] BSD-3 license, which allows for commercial and private use, making it compatible with both academy and industry standards.