PyTorch implementation of reverse-accurate ODE solvers for Neural ODEs
Project description
PyTorch implementation of two papers: (1) Adaptive checkpoint adjoint method for gradient estimation in Neural ODEs (2) MALI: a memory efficient and reverse accurate integrator for Neural ODEs
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
TorchDiffEqPack-1.0.1.tar.gz
(26.1 kB
view hashes)
Built Distribution
Close
Hashes for TorchDiffEqPack-1.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6ce5f9c7aa5e627bc8130172c9b6135460cb03532bf3b1742276541ec4c05311 |
|
MD5 | faa2d6ece1e0d896fdf79bfdc36ee228 |
|
BLAKE2b-256 | fabb31721405fabfffdf5ff2a3f713bcea78d245e081160490f4780fc7959c3b |