On Wednesday, 24 April 2019 at 10:56:54 UTC, jmh530 wrote:
On Wednesday, 24 April 2019 at 10:51:08 UTC, jmh530 wrote:
On Wednesday, 24 April 2019 at 06:13:13 UTC, Fynn Schröder
wrote:
[snip]
It's an autograd library for dynamic neural networks based on
mir and cuda. See GitHub for more details:
https://github.com/ShigekiKarita/grain
I've tried it and it works great -- although it's far from
feature complete in comparison to e.g. PyTorch.
Cool. Thanks for the summary.
Hmm, it looks like there are comparisons between it and
chainer, pytorch, and tensorflow. It might be interesting to
compare it to some other static autograd libraries. The only
one I can think of off the top of my head is Stan's [1], though
that's designed more for probabilistic programming than neural
networks.
[1] https://github.com/stan-dev/math
I see. I'm interested in Stan that is the best library for
probabilistic models but it lacks of GPU computation. Therefore,
I plan to add some probabilistic programming paradigm into grain
like pytorch (pyro) and tensorflow (tf probability).
