CUDA out of memory

[Sycamorers]

Hello,

When I ran the code, I was having this issue:

torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 64.00 MiB (GPU 0; 5.80 GiB total capacity; 4.91 GiB already allocated; 51.38 MiB free; 4.93 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

From nvidia-smi I saw there was still memory to be used ( 867MiB/6138MiB, and my GPU is RTX A2000) and I've also tried checking float size (I believe in default you were using float32), following the error instruction to use setting max_split_size_mb or adding torch.cuda.empty_cache() in run_nerf.py

None of them worked.

Could you please help me identify what problems I have with implementing your code? Or probably I just need a better GPU?

I'd appreciate your help!
Thanks so much! I look forward to your reply.

[Panxuran]

Hi!

A possible solution might be setting a lower chunk, netchunk or N_rand value. Also, if you happened to encounter this issue in the evaluation process, e.g., when generating videos, you can avoid out of memory by disable evaluation during training and use render_only when the whole training process is done.

Hope this may work on your case.