Kevin Cutler

@mccruz07 Thanks for the report! I have not tried training on apple silicon yet, but it looks like that might be a simple fix. I'll look into it in the...

@mccruz07 Turns out _all_ GPU training was broken due to a recent change I made to fix a bug for CPU training. I fixed it now in cellpose-omni v0.7.3. I...

Update: with torch 1.13.1, training is working on Apple Silicon =D @mccruz07 I am still getting that warning, but no errors. Really rough benchmark on a small (5-image) dataset: Titan...

Thanks @michaels10, good to know. 64 or 128GB of RAM? In addition to the cellose_omni bug which I hope is now fixed for you (it should now download v0.8.0 or...

Ok, try out `omnipose_mac_environment.yml`. I installed it with ``` conda env create --name omnipose --file /Volumes/DataDrive/omnipose_mac_environment.yml conda activate omnipose pip install git+https://github.com/kevinjohncutler/omnipose.git pip install git+https://github.com/kevinjohncutler/cellpose-omni.git ``` To my amazement, it...

Interesting. I'm not sure what to make of that error, but I know from practice that one way to be totally sure your environment is disjoint from base is by...

@michaels10 very nice! If you are using my environment file, I actually do set the evironment variable `PYTORCH_ENABLE_MPS_FALLBACK: '1'`. I use `torch.linalg.norm` in 4 places, and maybe there is a...

Update on GPU performance: got my hands on a Mac Studio (M1 Ultra, 128GB) and it took 115.3s for the same 100 epoch test I ran earlier. I ran it...

@su2804 Sorry I never saw there was activity on this thread. Are you still experiencing that training issue?

Thanks for reporting this, @Marco-J-K. I will look into this soon - likely a Windows specific specific issue.