torchdyn reference documentation¶
(New release 1.0 is out!)
torchdyn is a Python library entirely dedicated to continuous, implicit neural architectures and the numerical methods that underpin them.
It features a self-contained numerical suite of differential equation and root solvers, including sensitivity methods (continuous backsolve or interpolated adjoints, reverse-mode AD). The library further contains a model zoo and an extensive set of tutorials for researchers and practitioners.
pip install torchdyn
This library is developed and maintained by Michael Poli & Stefano Massaroli, with gracious contributions from the community.
Refer to the links below for a quickstart to core torchdyn features and a description of the library goals and design principles.
A set of extended tutorials, covering everything from models, benchmarks and numerics can be found here.