Python port

[srush]

Hi there,

I really love the g9.js demos! I think they convey how gradients work in such a nice and intuitive manner.

Just for fun I was playing with the idea of running a Torch-like library in the browser. I ported over most of the g9 code to python and ran it with AD (as opposed to finite-differences) -> https://srush.github.io/g9py/ . Not sure why this is better, but it might let you run models with tons of parameters. Let me know if this is okay.

Cheers!
Sasha

[bijection]

Very cool! I'd be happy to add a link to this if you like.

It seems at first click that it's a bit less performant for the recursive demos - I haven't read through the code yet, but did you implement the pruning part that uses ctx.pure? Or does that not play nice with AD?

[srush]

Right, yeah I forget why I didn't add that. Need to think about what it means for with torch-style AD.