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!
Comments
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