Add OFT/BOFT algorithm in we 8000 ight adapter #7725
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LoRA load/calculate_weight LoHa/LoKr/GLoRA load
For calculate weight I implement a fallback mechnism temporary for dev
* Allow disabling pe in flux code for some other models. * Initial Hunyuan3Dv2 implementation. Supports the multiview, mini, turbo models and VAEs. * Fix orientation of hunyuan 3d model. * A few fixes for the hunyuan3d models. * Update frontend to 1.13 (comfyanonymous#7331) * Add backend primitive nodes (comfyanonymous#7328) * Add backend primitive nodes * Add control after generate to int primitive * Nodes to convert images to YUV and back. Can be used to convert an image to black and white. * Update frontend to 1.14 (comfyanonymous#7343) * Native LotusD Implementation (comfyanonymous#7125) * draft pass at a native comfy implementation of Lotus-D depth and normal est * fix model_sampling kludges * fix ruff --------- Co-authored-by: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com> * Automatically set the right sampling type for lotus. * support output normal and lineart once (comfyanonymous#7290) * [nit] Format error strings (comfyanonymous#7345) * ComfyUI version v0.3.27 * Fallback to pytorch attention if sage attention fails. * Add model merging node for WAN 2.1 * Add Hunyuan3D to readme. * Support more float8 types. * Add CFGZeroStar node. Works on all models that use a negative prompt but is meant for rectified flow models. * Support the WAN 2.1 fun control models. Use the new WanFunControlToVideo node. * Add WanFunInpaintToVideo node for the Wan fun inpaint models. * Update frontend to 1.14.6 (comfyanonymous#7416) Cherry-pick the fix: Comfy-Org/ComfyUI_frontend#3252 * Don't error if wan concat image has extra channels. * ltxv: fix preprocessing exception when compression is 0. (comfyanonymous#7431) * Remove useless code. * Fix latent composite node not working when source has alpha. * Fix alpha channel mismatch on destination in ImageCompositeMasked * Add option to store TE in bf16 (comfyanonymous#7461) * User missing (comfyanonymous#7439) * Ensuring a 401 error is returned when user data is not found in multi-user context. * Returning a 401 error when provided comfy-user does not exists on server side. * Fix comment. This function does not support quads. * MLU memory optimization (comfyanonymous#7470) Co-authored-by: huzhan <huzhan@cambricon.com> * Fix alpha image issue in more nodes. * Fix problem. * Disable partial offloading of audio VAE. * Add activations_shape info in UNet models (comfyanonymous#7482) * Add activations_shape info in UNet models * activations_shape should be a list * Support 512 siglip model. * Show a proper error to the user when a vision model file is invalid. * Support the wan fun reward loras. --------- Co-authored-by: comfyanonymous <comfyanonymous@protonmail.com> Co-authored-by: Chenlei Hu <hcl@comfy.org> Co-authored-by: thot experiment <94414189+thot-experiment@users.noreply.github.com> Co-authored-by: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com> Co-authored-by: Terry Jia <terryjia88@gmail.com> Co-authored-by: Michael Kupchick <michael@lightricks.com> Co-authored-by: BVH <82035780+bvhari@users.noreply.github.com> Co-authored-by: Laurent Erignoux <lerignoux@gmail.com> Co-authored-by: BiologicalExplosion <49753622+BiologicalExplosion@users.noreply.github.com> Co-authored-by: huzhan <huzhan@cambricon.com> Co-authored-by: Raphael Walker <slickytail.mc@gmail.com>
* LoRA/LoHa/LoKr/GLoRA working well * Removed TONS of code in lora.py
This was referenced Apr 27, 2025
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Based on: comfyanonymous/ComfyUI#7727 comfyanonymous/ComfyUI#7725 comfyanonymous/ComfyUI#7540 Backwards compatible support of wd on output Unified weight adapter solution Support for OFT/BOFT
This was referenced May 3, 2025
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reference:
https://github.com/KohakuBlueleaf/LyCORIS/blob/main/lycoris/modules/diag_oft.py
https://github.com/KohakuBlueleaf/LyCORIS/blob/main/lycoris/modules/boft.py
https://arxiv.org/abs/2306.07280
https://arxiv.org/abs/2311.06243
diag-oft can be seen as a special case of boft but I still take them as 2 different algorithm to match other implementation.
Although oft/boft themselves have similar property of the DoRA scale but for better consistency I still keep them.