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ayaanzhaque / instruct-nerf2nerf

Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions (ICCV 2023)
https://instruct-nerf2nerf.github.io/
MIT License
800 stars 72 forks source link

Any chance to decrease GPU momory allocation? #78

Closed iceiilin closed 11 months ago

iceiilin commented 11 months ago

Hi, I ran this model with a 24G GPU memory, and got the error msg:

torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 320.00 MiB. GPU 0 has a total capacty of 23.69 GiB of which 148.81 MiB is free. Including non-PyTorch memory, this process has 23.48 GiB memory in use. Of the allocated memory 21.73 GiB is allocated by PyTorch, and 731.58 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation.

Is there any chance to decrease GPU momory allocation? Could you please share your thoughts? Thanks.

iceiilin commented 11 months ago

Close as I will do further practice according to notes on Readme