The differentiable programming
proposal being pitched for integration into Swift is scoped only to the reverse mode differentiation. I understand that it makes sense to reduce the breadth because the project is primarily aiming at deep learning applications. And DL almost exclusively uses the reverse mode.
I've used S4TF for physics and simulations and it frequently makes sense to use my personal favorite, the forward mode :) I know it's been a bit less tested and some features implemented for reverse were missing, but in my experience it worked well enough.
Can someone here, please, comment on what is the planned future of the forward mode? Is it going to be included in nightly builds of Swift under experimental _Differentiable import after the proposal is accepted? Or is it part of the tensorflow/swift fork and it's going go into "maintenance" unless someone comes over and picks it up?
PS1: Thanks to the S4TF team at Google and to all contributors. I appreciate Brennan's courage to hold the last meeting and answer all the questions. I feel that most people in the same situation would just post a message on the forums and then bury their head in the sand like the proverbial ostrich. In some ways it is harder you than the community, because you spend a good few years of your life working on it full (over)time.
PS2: I'm still puzzled about the reasons why the project was stopped. But, I guess, the only way to find out this secret is to go work for Google...