* 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 (#7331)
* Add backend primitive nodes (#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 (#7343)
* Native LotusD Implementation (#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 (#7290)
* [nit] Format error strings (#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 (#7416)
Cherry-pick the fix: https://github.com/Comfy-Org/ComfyUI_frontend/pull/3252
* Don't error if wan concat image has extra channels.
* ltxv: fix preprocessing exception when compression is 0. (#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 (#7461)
* User missing (#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 (#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 (#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>
* fix attention OOM in xformers
* allow passing attention mask in flux attention
* allow an attn_mask in flux
* attn masks can be done using replace patches instead of a separate dict
* fix return types
* fix return order
* enumerate
* patch the right keys
* arg names
* fix a silly bug
* fix xformers masks
* replace match with if, elif, else
* mask with image_ref_size
* remove unused import
* remove unused import 2
* fix pytorch/xformers attention
This corrects a weird inconsistency with skip_reshape.
It also allows masks of various shapes to be passed, which will be
automtically expanded (in a memory-efficient way) to a size that is
compatible with xformers or pytorch sdpa respectively.
* fix mask shapes
Use a simple CLIP model implementation instead of the one from
transformers.
This will allow some interesting things that would too hackish to implement
using the transformers implementation.
