* Update autoencoder_kl_wan.py
When using the Wan2.2 VAE, the spatial compression ratio calculated here is incorrect. It should be 16 instead of 8. Pass it in directly via the config to ensure it’s correct here.
* Update autoencoder_kl_wan.py
* support Wan2.2-VACE-Fun-A14B
* support Wan2.2-VACE-Fun-A14B
* support Wan2.2-VACE-Fun-A14B
* Apply style fixes
* test
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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
* Use SDP on BF16 in GPU/HPU migration
Signed-off-by: Daniel Socek <daniel.socek@intel.com>
* Formatting fix for enabling SDP with BF16 precision on HPU
Signed-off-by: Daniel Socek <daniel.socek@intel.com>
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Signed-off-by: Daniel Socek <daniel.socek@intel.com>
* 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* Enhance SkyReels-V2 documentation: update model loading for GPU support and remove outdated notes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>
* Add Bria model and pipeline to diffusers
- Introduced `BriaTransformer2DModel` and `BriaPipeline` for enhanced image generation capabilities.
- Updated import structures across various modules to include the new Bria components.
- Added utility functions and output classes specific to the Bria pipeline.
- Implemented tests for the Bria pipeline to ensure functionality and output integrity.
* with working tests
* style and quality pass
* adding docs
* add to overview
* fixes from "make fix-copies"
* Refactor transformer_bria.py and pipeline_bria.py: Introduce new EmbedND class for rotary position embedding, and enhance Timestep and TimestepProjEmbeddings classes. Add utility functions for handling negative prompts and generating original sigmas in pipeline_bria.py.
* remove redundent and duplicates tests and fix bf16
slow test
* style fixes
* small doc update
* Enhance Bria 3.2 documentation and implementation
- Updated the GitHub repository link for Bria 3.2.
- Added usage instructions for the gated model access.
- Introduced the BriaTransformerBlock and BriaAttention classes to the model architecture.
- Refactored existing classes to integrate Bria-specific components, including BriaEmbedND and BriaPipeline.
- Updated the pipeline output class to reflect Bria-specific functionality.
- Adjusted test cases to align with the new Bria model structure.
* Refactor Bria model components and update documentation
- Removed outdated inference example from Bria 3.2 documentation.
- Introduced the BriaTransformerBlock class to enhance model architecture.
- Updated attention handling to use `attention_kwargs` instead of `joint_attention_kwargs`.
- Improved import structure in the Bria pipeline to handle optional dependencies.
- Adjusted test cases to reflect changes in model dtype assertions.
* Update Bria model reference in documentation to reflect new file naming convention
* Update docs/source/en/_toctree.yml
* Refactor BriaPipeline to inherit from DiffusionPipeline instead of FluxPipeline, updating imports accordingly.
* move the __call__ func to the end of file
* Update BriaPipeline example to use bfloat16 for precision sensitivity for better result
* make style && make quality && make fix-copiessource
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Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
