Use torch.svd_lowrank for large matrices in resize_lora.py
#2240
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Thank you, this is really nice! I'd like to merge this sooner. I'm a little busy so please wait a moment. |
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This hugely reduces the time to prune a LoRA, without visible quality loss compared to the full SVD. The time is reduced from 3 hours (Wan) and 1 hour (Qwen-Image) to a few seconds on my laptop.
See https://docs.pytorch.org/docs/stable/generated/torch.svd_lowrank.html for details. Maybe we can increase
niterfor even better quality but I think the defaultniter=2already gives good enough quality. Kijai'sLoraExtractKJnode usesniter=7by default, see https://github.com/kijai/ComfyUI-KJNodes/blob/bb205d809b467307b8ec3bb1a22680a4873187f8/nodes/lora_nodes.py#L30 (but they don't yet do adaptive rank after svd_lowrank)