4 ms·

I wonder how performance compares to cupy : https://cupy.chainer.org https://cupy.chainer.org Seems a little limited in terms of supported operations for autog

I wonder how performance compares to cupy : https://cupy.chainer.org https://cupy.chainer.org Seems a little limited in terms of supported operations for autograd compared to Chainer:https://chainer.org https://chainer.org or Flux:http://fluxml.ai http://fluxml.ai Really cool to see though! XLA/TPU support is awesome.

alexbw 8y ago
Actually, advanced autodiff is one of its intended points of, er, differentiation :). The authors wrote the original Autograd package [0], released in 2014, that led to “autograd” becoming used as a generic term in PyTorch and other packages. JAX has all of the autodiff operations that Autograd does, including `grad`, `vjp`, `jvp`, etc. We’re working on the number of supported NumPy ops, which is limited right now, but it’s early days. Try it out, we’re really excited to see what you build with it! 0: https://github.com/hips/autograd https://github.com/hips/autograd