* Upload files for Chroma Implementation
* Remove trailing whitespace
* trim more trailing whitespace..oops
* remove unused imports
* Add supported_inference_dtypes
* Set min_length to 0 and remove attention_mask=True
* Set min_length to 1
* get_mdulations added from blepping and minor changes
* Add lora conversion if statement in lora.py
* Update supported_models.py
* update model_base.py
* add uptream commits
* set modelType.FLOW, will cause beta scheduler to work properly
* Adjust memory usage factor and remove unnecessary code
* fix mistake
* reduce code duplication
* remove unused imports
* refactor for upstream sync
* sync chroma-support with upstream via syncbranch patch
* Update sd.py
* Add Chroma as option for the OptimalStepsScheduler node
* Add basic support for videos as types
This PR adds support for VIDEO as first-class types. In order to avoid
unnecessary costs, VIDEO outputs must implement the `VideoInput` ABC,
but their implementation details can vary. Included are two
implementations of this type which can be returned by other nodes:
* `VideoFromFile` - Created with either a path on disk (as a string) or
a `io.BytesIO` containing the contents of a file in a supported format
(like .mp4). This implementation won't actually load the video unless
necessary. It will also avoid re-encoding when saving if possible.
* `VideoFromComponents` - Created from an image tensor and an optional
audio tensor.
Currently, only h264 encoded videos in .mp4 containers are supported for
saving, but the plan is to add additional encodings/containers in the
near future (particularly .webm).
* Add optimization to avoid parsing entire video
* Improve type declarations to reduce warnings
* Make sure bytesIO objects can be read many times
* Fix a potential issue when saving long videos
* Fix incorrect type annotation
* Add a `LoadVideo` node to make testing easier
* Refactor new types out of the base comfy folder
I've created a new `comfy_api` top-level module. The intention is that
anything within this folder would be covered by semver-style versioning
that would allow custom nodes to rely on them not introducing breaking
changes.
* Fix linting issue
* 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
