lllyasviel / lllyasviel/ControlNet
Multi-gpu training
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- Dominant language
- Python
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- 34.1k
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Description
When I use one gpu for training, the process runs well. But when I use 4 gpus, changing gpus=4, it ran out of memory. How to adjust the code for multi-gpu training?
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
No file, test, or entry point is named. Start by locating the training configuration and the code that handles the gpus setting, then reproduce the one-GPU and four-GPU runs to identify why memory usage exceeds capacity. Done means documented or implemented multi-GPU training that avoids the reported out-of-memory failure.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100