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With Pytorch and TF both supporting Apple's M1/M2 silicon chips, you should be able to include a device checker and include "mps" capability for GPU processing. If only I had the time to create a branch and show you.
The text was updated successfully, but these errors were encountered:
Thanks for info:) I do not have access to a Mac currently and the optimization here in my repo should only be used for intel xeon cpu. But good to know about the mps device compatibility. Is it fast enough?
Thank you for your quick reply. I can run inference.py using your int8 instructions and --cpu on my MacBook M1 Max Pro but at a rate of ~18s/it (not even 1 it/s). If I get some time, I might create a fork and see if I can modify your engine to accept device=mps.
With Pytorch and TF both supporting Apple's M1/M2 silicon chips, you should be able to include a device checker and include "mps" capability for GPU processing. If only I had the time to create a branch and show you.
The text was updated successfully, but these errors were encountered: