Hi all!
You can check your preset quickly with the following:
print(torch.backends.mps.is_built())
print(torch.backends.mps.is_available())
Also, to use an MPS device, you can pass it as a parameter to a model initiation.
For most cases, it’s enough o run training on the M1.
dls = ImageDataLoaders.from_name_func(
path, get_image_files(path), valid_pct=0.2, seed=42,
label_func=is_cat, item_tfms=Resize(224), device=default_device(1))
But there are still a lot of other problems that I found.
Here is my experience with running the 1st lesson on M1 Max Macbook: FastAI 2022 on Macbook M1 Pro Max (GPU) | by Ivan T | Feb, 2023 | Medium
P.S. You can check that training using GPU by checking Activity Monitoring, and by the training time, of course. CPU takes x10 then GPU.
GPU usage:
