lllyasviel / lllyasviel/FramePack
torch.OutOfMemoryError: CUDA out of memory
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- Dominant language
- Python
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Description
"Requirements:
Nvidia GPU in RTX 30XX, 40XX, 50XX series that supports fp16 and bf16. The GTX 10XX/20XX are not tested.
Linux or Windows operating system.
At least 6GB GPU memory."
But at 8 gb 2070 super i get error: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 31.25 GiB. GPU 0 has a total capacity of 8.00 GiB of which 3.66 GiB is free. Of the allocated memory 2.86 GiB is allocated by PyTorch, and 424.57 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
No repository file, test, or entry point is named. Start by reproducing the reported CUDA out-of-memory error on an 8 GB RTX 2070 Super, then read the linked PyTorch CUDA memory-management guidance and compare the documented requirements with the actual allocation; done means the cause and supported memory requirement are established or the issue is resolved.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100