* 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>
This commit relaxes divisibility constraint for single-frame
conditionings. For single frames, the index can be arbitrary, while
multi-frame conditionings (>= 9 frames) must still be aligned to 8
frames.
Co-authored-by: Andrew Kvochko <a.kvochko@lightricks.com>
- Wan and Cosmos prompt upsamplers
- Fixed torch.compile issues
- Known models added
- Cosmos, Wan and Hunyuan Video resolutions now supported by Fit Image
to Diffusion Size.
- Better error messages for Ampere and Triton interactions
This patch fixes a bug in LTXVCropGuides when the latent has no
keyframes. Additionally, the first frame is always added as a keyframe.
Co-authored-by: Andrew Kvochko <a.kvochko@lightricks.com>
- Cosmos now fully tested
- Preliminary support for essential Cosmos prompt "upsampler"
- Lumina tests
- Tweaks to language and image resizing nodes
- Fix for #31 all the samplers are now present again
The frontend part isn't done yet so there is no video preview on the node
or dragging the webm on the interface to load the workflow yet.
This uses a new dependency: PyAV.
- export_custom_nodes() finds all the classes that inherit from
CustomNode and exports them correctly for custom node discovery to
find
- regular expressions
- additional string formatting and parsing nodes
- fix#29 str(model) no longer raises exceptions like with
HyVideoModelLoader
- don't try to format CUDA tensors because that can sometimes raise
exceptions
- cudaAllocAsync has been disabled for now due to 2.6.0 bugs
- improve florence2 support
- add support for paligemma 2. This requires the fix for transformers
that is currently staged in another repo, install with
`uv pip install --no-deps "transformers@git+https://github.com/zucchini-nlp/transformers.git#branch=paligemma-fix-kwargs"`
- triton has been updated
- fix missing __init__.py files
* Add 'sigmas' to transformer_options so that downstream code can know about the full scope of current sampling run, fix Hook Keyframes' guarantee_steps=1 inconsistent behavior with sampling split across different Sampling nodes/sampling runs by referencing 'sigmas'
* Cleaned up hooks.py, refactored Hook.should_register and add_hook_patches to use target_dict instead of target so that more information can be provided about the current execution environment if needed
* Refactor WrapperHook into TransformerOptionsHook, as there is no need to separate out Wrappers/Callbacks/Patches into different hook types (all affect transformer_options)
* Refactored HookGroup to also store a dictionary of hooks separated by hook_type, modified necessary code to no longer need to manually separate out hooks by hook_type
* In inner_sample, change "sigmas" to "sampler_sigmas" in transformer_options to not conflict with the "sigmas" that will overwrite "sigmas" in _calc_cond_batch
* Refactored 'registered' to be HookGroup instead of a list of Hooks, made AddModelsHook operational and compliant with should_register result, moved TransformerOptionsHook handling out of ModelPatcher.register_all_hook_patches, support patches in TransformerOptionsHook properly by casting any patches/wrappers/hooks to proper device at sample time
* Made hook clone code sane, made clear ObjectPatchHook and SetInjectionsHook are not yet operational
* Fix performance of hooks when hooks are appended via Cond Pair Set Props nodes by properly caching between positive and negative conds, make hook_patches_backup behave as intended (in the case that something pre-registers WeightHooks on the ModelPatcher instead of registering it at sample time)
* Filter only registered hooks on self.conds in CFGGuider.sample
* Make hook_scope functional for TransformerOptionsHook
* removed 4 whitespace lines to satisfy Ruff,
* Add a get_injections function to ModelPatcher
* Made TransformerOptionsHook contribute to registered hooks properly, added some doc strings and removed a so-far unused variable
* Rename AddModelsHooks to AdditionalModelsHook, rename SetInjectionsHook to InjectionsHook (not yet implemented, but at least getting the naming figured out)
* Clean up a typehint
