lllyasviel / lllyasviel/stable-diffusion-webui-forge
Patching LoRAs for KModel slow with Automatic (fp16 LoRA).
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- Dominant language
- Python
- Stars
- 13k
- Forks
- 1.7k
- PR merge metrics
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Description
```
Patching LoRA by precomputing model weights.
Patching LoRAs for KModel: 94%|█████████████████████████████████████████████████▊ | 286/304 [01:16<00:02, 6.48it/s]ERROR lora diffusion_model.single_blocks.32.linear1.weight Allocation on device
Patching LoRA weights failed. Retrying by offloading models.
Patching LoRAs for KModel: 100%|█████████████████████████████████████████████████████| 304/304 [01:58<00:00, 2.56it/s]
LoRA patching has taken 118.75 seconds
Moving model(s) has taken 130.87 seconds
```
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
Start by reproducing Automatic's fp16 LoRA path using the reported KModel patching output. Investigate the allocation failure and the fallback to offloading, then compare the patching and model-moving timings against the reported 118.75 and 130.87 seconds. Done means the reported slow path is addressed and the relevant timings no longer show the excessive delay.
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
- 35/100