| I installed Whisper (and, I thought all the needed dependencies), and had it running on my M1 Max MacBook Pro with 64 GB ram, but it ran TERRIBLY slowly... taking an hour to do a couple of minutes... I found this thread and wondered if Whisper was accessing all the cores or the gpu, so I've spent a couple of hours trying to get whisper to access the gpu - following the points made in this thread, and googling how to install via brew the various components. Long story short, I keep getting an error message "RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU." or when I set --device to gpu, it get the error:
"RuntimeError: don't know how to restore data location of torch.storage._UntypedStorage (tagged with gpu)" it's been a looong time since I wrote any code (remember basic?), so realise I may be missing a lot here!! does anyone have any pointers? thanks! edit: I'm now trying it one more time after trying to set the cpu using this line: map_location=torch.device('gpu') and I get this message as whisper begins:
~/opt/anaconda3/lib/python3.9/site-packages/whisper/transcribe.py:78: UserWarning: FP16 is not supported on CPU; using FP32 instead
warnings.warn("FP16 is not supported on CPU; using FP32 instead") then I wait for whisper to do it's magic ...tho it looks like it will remain very slow... |