GitLab

* up

* correct wording.

* up

* up

* up

* rename photon to prx

* rename photon into prx

* Revert .gitignore to state before commit b7fb0fe9d63bf766bbe3c42ac154a043796dd370

* rename photon to prx

* rename photon into prx

* Revert .gitignore to state before commit b7fb0fe9d63bf766bbe3c42ac154a043796dd370

* make fix-copies

* purge HF_HUB_ENABLE_HF_TRANSFER; promote Xet

* purge HF_HUB_ENABLE_HF_TRANSFER; promote Xet x2

* restrict docker build test to the ones we actually use in CI.

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

* Add Photon model and pipeline support

This commit adds support for the Photon image generation model:
- PhotonTransformer2DModel: Core transformer architecture
- PhotonPipeline: Text-to-image generation pipeline
- Attention processor updates for Photon-specific attention mechanism
- Conversion script for loading Photon checkpoints
- Documentation and tests

* just store the T5Gemma encoder

* enhance_vae_properties if vae is provided only

* remove autocast for text encoder forwad

* BF16 example

* conditioned CFG

* remove enhance vae and use vae.config directly when possible

* move PhotonAttnProcessor2_0 in transformer_photon

* remove einops dependency and now inherits from AttentionMixin

* unify the structure of the forward block

* update doc

* update doc

* fix T5Gemma loading from hub

* fix timestep shift

* remove lora support from doc

* Rename EmbedND for PhotoEmbedND

* remove modulation dataclass

* put _attn_forward and _ffn_forward logic in PhotonBlock's forward

* renam LastLayer for FinalLayer

* remove lora related code

* rename vae_spatial_compression_ratio for vae_scale_factor

* support prompt_embeds in call

* move xattention conditionning out computation out of the denoising loop

* add negative prompts

* Use _import_structure for lazy loading

* make quality + style

* add pipeline test + corresponding fixes

* utility function that determines the default resolution given the VAE

* Refactor PhotonAttention to match Flux pattern

* built-in RMSNorm

* Revert accidental .gitignore change

* parameter names match the standard diffusers conventions

* renaming and remove unecessary attributes setting

* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* quantization example

* added doc to toctree

* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* use dispatch_attention_fn for multiple attention backend support

* naming changes

* make fix copy

* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Add PhotonTransformer2DModel to TYPE_CHECKING imports

* make fix-copies

* Use Tuple instead of tuple
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* restrict the version of transformers
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update tests/pipelines/photon/test_pipeline_photon.py
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update tests/pipelines/photon/test_pipeline_photon.py
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* change | for Optional

* fix nits.

* use typing Dict

---------
Co-authored-by: davidb <davidb@worker-10.soperator-worker-svc.soperator.svc.cluster.local>
Co-authored-by: David Briand <david@photoroom.com>
Co-authored-by: davidb <davidb@worker-8.soperator-worker-svc.soperator.svc.cluster.local>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>

* cleanup of runway model

* quality fixes

* up

* up

* up

* up

* up

* u[

* up

* up

* up

* xfail more incorrect transformer imports.

* xfail more.

* up

* up

* up

fix clapconfig for text backbone in audioldm2

I noticed that the test should be for the option check_compiled="ignore"
but it was using check_compiled="warn". This has been fixed, now the
correct argument is passed.

However, the fact that the test passed means that it was incorrect to
begin with. The way that logs are collected does not collect the
logger.warning call here (not sure why). To amend this, I'm now using
assertNoLogs. With this change, the test correctly fails when the wrong
argument is passed.

xfail failing tests in CI.

* cache non lora pipeline outputs.

* up

* up

* up

* up

* Revert "up"

This reverts commit 772c32e43397f25919c29bbbe8ef9dc7d581cfb8.

* up

* Revert "up"

This reverts commit cca03df7fce55550ed28b59cadec12d1db188283.

* up

* up

* add .

* up

* up

* up

* up

* up

* up

* Allow prerelease when installing transformers from main

* maybe better

* maybe better

* and now?

* just bored

* should be better

* works now

fix xpu ut failures w/ latest pytorch
Signed-off-by: Yao, Matrix <matrix.yao@intel.com>

* update

* update

* update

* update

* update

* feat: support aobaseconfig classes.

* [docs] AOBaseConfig (#12302)

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

* up

* replace with is_torchao_version

* up

* up

---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

u[

* disable installing transformers from main in ci for now.

* up

* u[p

* Support huggingface_hub 0.x and 1.x

* httpx

Signed-off-by: Yao, Matrix <matrix.yao@intel.com>

Signed-off-by: Yao, Matrix <matrix.yao@intel.com>

disable xformer tests for pipelines it isn't popular.

* single scheduler please.

* up

* up

* up

* up

* xfail some tests

* up

* up

xfail some kandinsky tests.

* Convert alphas for embedders for sd-scripts to ai toolkit conversion

* Add kohya embedders conversion test

* Apply style fixes

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* support Wan2.2-VACE-Fun-A14B

* support Wan2.2-VACE-Fun-A14B

* support Wan2.2-VACE-Fun-A14B

* Apply style fixes

* test

---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* allow non list components_to_quantize.

* up

* Apply suggestions from code review

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* [docs] components_to_quantize (#12287)

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

---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* add

* add a test

* feat: support group offloading at the pipeline level.

* add tests

* up

* [docs] Pipeline group offloading (#12286)

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

---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

adjust criteria for XPU
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
Co-authored-by: Aryan <aryan@huggingface.co>

* feat: add a test for aot.

* up

* initial commit

* update

* updates

* update

* update

* update

* update

* update

* update

* addressed PR comments

* update

* addressed PR comments

* update

* update

* update

* update

* update

* update

* updates

* update

* update

* addressed PR comments

* updates

* code formatting

* update

* addressed PR comments

* addressed PR comments

* addressed PR comments

* addressed PR comments

* fix docs and dependencies

* fixed dependency test

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

update

* update

* Apply style fixes

* update

* update

---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* update

* update

* update

* update

* update

* merge main

* Revert "merge main"

This reverts commit 65efbcead58644b31596ed2d714f7cee0e0238d3.

Fix typos and test assertions
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* start removing flax stuff.

* add deprecation warning.

* add warning messages.

* more warnings.

* remove dockerfiles.

* remove more.

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

* up

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

* added test qwen image controlnet

* Apply style fixes

* added test qwenimage multicontrolnet

* Apply style fixes

---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

Signed-off-by: YAO Matrix <matrix.yao@intel.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

---------
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>