lllyasviel / lllyasviel/FramePack
FramePack triggers CUDA OOM (>30GB allocation) on 8GB GPU, even with minimal inputs
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- Dominant language
- Python
- Stars
- 17.3k
- Forks
- 1.7k
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Description
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 30.26 GiB. GPU 0 has a total capacity of 8.00 GiB of which 3.90 GiB is free. Of the allocated memory 2.62 GiB is allocated by PyTorch, and 446.42 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)
Unloaded DynamicSwap_LlamaModel as complete.
Unloaded CLIPTextModel as complete.
Unloaded SiglipVisionModel as complete.
Unloaded AutoencoderKLHunyuanVideo as complete.
Unloaded DynamicSwap_HunyuanVideoTransformer3DModelPacked as complete.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No source file, test, or entry point is named in the report; start by reproducing the minimal-input run and tracing the CUDA allocation that requests 30.26 GiB. Done should include a confirmed explanation and a regression check or documented hardware requirement for 8GB GPUs.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100