Similar goes for quirks of Tensorflow that weren't taken advantage of. That's largely the work that is on-going in the OSX and M1 forks.
(base) stable-diffusion git:(main) conda env create -f environment.yaml
Collecting package metadata (repodata.json): done
Solving environment: failed
ResolvePackageNotFound:
- cudatoolkit=11.3
oh i was following the github fork readme, there is a special macos blog postSo, yeah PyTorch is correctly serving as a 'glue'.
https://github.com/CompVis/stable-diffusion/commit/0763d366e...
These just cover the neural net though, and there is lots of surrounding code and pre-/post-processing that isn't covered by these systems.
For models on Replicate, we use Docker, packaged with Cog for this stuff.[2] Unfortunately Docker doesn't run natively on Mac, so if we want to use the Mac's GPU, we can't use Docker.
I wish there was a good container system for Mac. Even better if it were something that spanned both Mac and Linux. (Not as far-fetched as it seems... I used to work at Docker and spent a bit of time looking into this...)
[0] https://tvm.apache.org/ [1] https://onnx.ai/ [2] https://github.com/replicate/cog
I mean, are we going to see X on M1 Mac, for any X now in the future?
Also, weren't torch and tensorflow supposed to be this glue?