microsoft / microsoft/TRELLIS.2
Inference vram leak
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- Dominant language
- Python
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- 11.3k
- Forks
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Description
As the number of inference iterations increases, the GPU memory usage continues to grow. May I ask if there are any methods to optimize it?
Contributor guide
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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
The issue names no file, test, or inference entry point. Start by reproducing the increasing GPU memory usage across repeated inference iterations and identify the relevant inference path in the repository. Done means memory usage no longer grows across iterations, with a regression test or documented reproduction confirming the behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100