* Add AttentionMixin to WanVACETransformer3DModel
to enable methods like `set_attn_processor()`.
* Import AttentionMixin in transformer_wan_vace.py
Special thanks to @tolgacangoz 🙇♂️
* make modular pipeline work with model_index.json
* up
* style
* up
* up
* style
* up more
* Fix MultiControlNet import (#12118)
fix
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Co-authored-by: Álvaro Somoza <asomoza@users.noreply.github.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* fix: update SkyReels-V2 documentation and moving into attn dispatcher
* Refactors SkyReelsV2's attention implementation
* style
* up
* Fixes formatting in SkyReels-V2 documentation
Wraps the visual demonstration section in a Markdown code block.
This change corrects the rendering of ASCII diagrams and examples, improving the overall readability of the document.
* Docs: Condense example arrays in skyreels_v2 guide
Improves the readability of the `step_matrix` examples by replacing long sequences of repeated numbers with a more compact `value×count` notation.
This change makes the underlying data patterns in the examples easier to understand at a glance.
* Add _repeated_blocks attribute to SkyReelsV2Transformer3DModel
* Refactor rotary embedding calculations in SkyReelsV2 to separate cosine and sine frequencies
* Enhance SkyReels-V2 documentation: update model loading for GPU support and remove outdated notes
* up
* up
* Update model_id in SkyReels-V2 documentation
* up
* refactor: remove device_map parameter for model loading and add pipeline.to("cuda") for GPU allocation
* fix: update copyright year to 2025 in skyreels_v2.md
* docs: enhance parameter examples and formatting in skyreels_v2.md
* docs: update example formatting and add notes on LoRA support in skyreels_v2.md
* refactor: remove copied comments from transformer_wan in SkyReelsV2 classes
* Clean up comments in skyreels_v2.md
Removed comments about acceleration helpers and Flash Attention installation.
* Add deprecation warning for `SkyReelsV2AttnProcessor2_0` class
* Fix PyTorch 2.3.1 compatibility: add version guard for torch.library.custom_op
- Add hasattr() check for torch.library.custom_op and register_fake
- These functions were added in PyTorch 2.4, causing import failures in 2.3.1
- Both decorators and functions are now properly guarded with version checks
- Maintains backward compatibility while preserving functionality
Fixes#12195
* Use dummy decorators approach for PyTorch version compatibility
- Replace hasattr check with version string comparison
- Add no-op decorator functions for PyTorch < 2.4.0
- Follows pattern from #11941 as suggested by reviewer
- Maintains cleaner code structure without indentation changes
* Update src/diffusers/models/attention_dispatch.py
Update all the decorator usages
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
* Update src/diffusers/models/attention_dispatch.py
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
* Update src/diffusers/models/attention_dispatch.py
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
* Update src/diffusers/models/attention_dispatch.py
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
* Move version check to top of file and use private naming as requested
* Apply style fixes
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Co-authored-by: Aryan <contact.aryanvs@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
