GitLab

* Add Support for Z-Image.

* Reformatting with make style, black & isort.

* Remove init, Modify import utils, Merge forward in transformers block, Remove once func in pipeline.

* modified main model forward, freqs_cis left

* refactored to add B dim

* fixed stack issue

* fixed modulation bug

* fixed modulation bug

* fix bug

* remove value_from_time_aware_config

* styling

* Fix neg embed and devide / bug; Reuse pad zero tensor; Turn cat -> repeat; Add hint for attn processor.

* Replace padding with pad_sequence; Add gradient checkpointing.

* Fix flash_attn3 in dispatch attn backend by _flash_attn_forward, replace its origin implement; Add DocString in pipeline for that.

* Fix Docstring and Make Style.

* Revert "Fix flash_attn3 in dispatch attn backend by _flash_attn_forward, replace its origin implement; Add DocString in pipeline for that."

This reverts commit fbf26b7ed11d55146103c97740bad4a5f91744e0.

* update z-image docstring

* Revert attention dispatcher

* update z-image docstring

* styling

* Recover attention_dispatch.py with its origin impl, later would special commit for fa3 compatibility.

* Fix prev bug, and support for prompt_embeds pass in args after prompt pre-encode as List of torch Tensor.

* Remove einop dependency.

* remove redundant imports & make fix-copies

* fix import

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Co-authored-by: liudongyang <liudongyang0114@gmail.com>

* add hunyuanimage2.1


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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add qwen modular

* 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>

update
Co-authored-by: Álvaro Somoza <asomoza@users.noreply.github.com>

* (feat): qwen-image integration

* fix(qwen-image):
- remove unused logics related to controlnet/ip-adapter

* fix(qwen-image):
- compatible with attention dispatcher
- cond cache support

* fix(qwen-image):
- cond cache registry
- attention backend argument
- fix copies

* fix(qwen-image):
- remove local test

* Update src/diffusers/models/transformers/transformer_qwenimage.py

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Co-authored-by: YiYi Xu <yixu310@gmail.com>

* start flux.

* more

* up

* up

* up

* up

* get back the deleted files.

* up

* empathy

* update

* update

* modify flux single blocks to make compatible with cache techniques (without too much model-specific intrusion code)

* remove debug logs

* update

* cache context for different batches of data

* fix hs residual bug for single return outputs; support ltx

* fix controlnet flux

* support flux, ltx i2v, ltx condition

* update

* update

* Update docs/source/en/api/cache.md

* Update src/diffusers/hooks/hooks.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* address review comments pt. 1

* address review comments pt. 2

* cache context refacotr; address review pt. 3

* address review comments

* metadata registration with decorators instead of centralized

* support cogvideox

* support mochi

* fix

* remove unused function

* remove central registry based on review

* update

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Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>