  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.
