> TensorFlow 1.1.0 will be the last time we release a binary with Mac GPU support. Going forward, we will stop testing on Mac GPU systems. We continue to welcome patches that maintain Mac GPU support, and we will try to keep the Mac GPU build working.
Sounds like a lack of external contributors maintaining it to me, are there really that many users? Everyone I know on macOS uses docker (or some other virtualisation) to run linux for small jobs and then connects remotely to linux boxes when they need more computing power.
Officially, there shouldn't be very many people for whom it's relevant. The last Macs with Nvidia GPUs were sold around 2011 if I remember correctly.
Unofficially, there may be some people using Hackitoshs with rather beefy GPUs for machine learning.
There's a lot you can do easily on a $500 GPU that should take too long on CPU. And I prefer the shorter write/run/debug loop of working locally. It's the same niche other machine learning workstations fill, only with the preferred desktop OS.
There will also be external GPUs for Macs soon(ish), and those would be perfect for tensorflow. I'm not sure at that point they'll want it running on Macs again, and discontinuing support now may be the wrong decision.
Doing a little binary search on Everymac, it seems that the last new MBP model with Nvidia graphics was mid-2014. Both offerings with discrete graphics from mid-2015 had AMD cards. I'm also fairly sure you could still buy those mid-2014 MBPs well into 2015; I distinctly remember seeing both AMD and Nvidia MBPs available in the online store around that time.
It just means OSX users (like me) have to compile from source - no different from PyTorch. Happy to provide compiled binaries for 10.12, though it's a bit of a chore to get Xcode clang and CUDA to play nice together.
For now–I've thought about getting involved in keeping that going, even trying to set up a travis build. But bazel, I, and C++, we simply don't enjoy the time we spend together.
FWIW, 1.2 does still build on MacOS. But you have to build it yourself. I did run into a fair amount of problems, but ultimately I'm not sure if those weren't of my own making.
I think because now they have AMD GPUs for some years.
I have a MacBook Pro from 2013 and I think it was the one before the last to have a Nvidia GPU.
Also, it's always an headache for me to get CUDA to work with Python/R libraries anytime I update the system and I have yet to find a straightforward guide that tells me exactly the steps to take... they all fail at some place.
Sounds like a lack of external contributors maintaining it to me, are there really that many users? Everyone I know on macOS uses docker (or some other virtualisation) to run linux for small jobs and then connects remotely to linux boxes when they need more computing power.