Pytorch optimizer based on nonlinear conjugate gradient method
Project description
NCG-optimizer is a set of optimizer about nonliear conjugate gradient in Pytorch.
Install
$ pip install ncg_optimizer
Example
from ncg-optimizer import PRP
# model = Your Model
optimizer = PRP(model.parameters())
Supported Optimizers
Basic Methods
The implementation of all basic methods is based on the book “Nonlinear Conjugate Gradient Method” [1].
Linear Conjugate Gradient
The linear conjugate gradient(LCG) method is only applicable to linear equation solving problems. It converts linear equations into quadratic functions, so that the problem can be solved iteratively without inverting the coefficient matrix.
Fletcher-Reeves
Changes
0.0.1 (2023-01-01)
Initial release.
Added support for LCG, FR, .
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
ncg-optimizer-0.0.1b0.tar.gz
(7.6 kB
view hashes)
Built Distribution
Close
Hashes for ncg_optimizer-0.0.1b0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | cecdb0615ef315d44b7eee6e47274e0d63e43255b81c98ebe614f59ac2843e10 |
|
MD5 | 340904c31af23bdf685d3c3ca4a88fa4 |
|
BLAKE2b-256 | c7582a28d19d3555cc0c14ae61594e720979482ea93eec54cc20c170fa4987e8 |