state&lt;-

Code lifted from a internal function of madgrad package.
Set 'state' attribute of an object.

internal

Optimizers for 'torch' deep learning library. These
functions include recent results published in the literature and are
not part of the optimizers offered in 'torch'. Prospective users
should test these optimizers with their data, since performance
depends on the specific problem being solved. The packages includes
the following optimizers: (a) 'adabelief' by Zhuang et al (2020),
<arXiv:2010.07468>; (b) 'adabound' by Luo et al.(2019),
<arXiv:1902.09843>; (c) 'adahessian' by Yao et al.(2021)
<arXiv:2006.00719>; (d) 'adamw' by Loshchilov & Hutter (2019),
<arXiv:1711.05101>; (e) 'madgrad' by Defazio and Jelassi (2021),
<arXiv:2101.11075>; (f) 'nadam' by Dozat (2019),
<https://openreview.net/pdf/OM0jvwB8jIp57ZJjtNEZ.pdf>; (g) 'qhadam' by
Ma and Yarats(2019), <arXiv:1810.06801>; (h) 'radam' by Liu et al.
(2019), <arXiv:1908.03265>; (i) 'swats' by Shekar and Sochee (2018),
<arXiv:1712.07628>; (j) 'yogi' by Zaheer et al.(2019),
<https://papers.nips.cc/paper/8186-adaptive-methods-for-nonconvex-optimization>.

Gilberto Camara

torchopt

Advanced Optimizers for Torch

Rolf Simoes

Daniel Falbel

Felipe Souza

state&lt;- function

Daniel Falbel, <a href="/link/dfalbel%40gmail.com?package=torchopt&version=0.1.4" data-mini-rdoc="torchopt::dfalbel@gmail.com">dfalbel@gmail.com</a>

Author

Imported function — state&lt;-

Daniel Falbel, <a href='mailto:dfalbel@gmail.com'>dfalbel@gmail.com</a>

state<-: Imported function

Description

Usage

Arguments

Author