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Torchbearer: A Model Fitting Library for PyTorch (1809.03363v1)

Published 10 Sep 2018 in cs.LG, cs.AI, cs.CV, and stat.ML

Abstract: We introduce torchbearer, a model fitting library for pytorch aimed at researchers working on deep learning or differentiable programming. The torchbearer library provides a high level metric and callback API that can be used for a wide range of applications. We also include a series of built in callbacks that can be used for: model persistence, learning rate decay, logging, data visualization and more. The extensive documentation includes an example library for deep learning and dynamic programming problems and can be found at http://torchbearer.readthedocs.io. The code is licensed under the MIT License and available at https://github.com/ecs-vlc/torchbearer.

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Authors (3)
  1. Ethan Harris (5 papers)
  2. Matthew Painter (3 papers)
  3. Jonathon Hare (32 papers)
Citations (3)

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