GitLab

* add vae

* Initial commit for Flux 2 Transformer implementation

* add pipeline part

* small edits to the pipeline and conversion

* update conversion script

* fix

* up up

* finish pipeline

* Remove Flux IP Adapter logic for now

* Remove deprecated 3D id logic

* Remove ControlNet logic for now

* Add link to ViT-22B paper as reference for parallel transformer blocks such as the Flux 2 single stream block

* update pipeline

* Don't use biases for input projs and output AdaNorm

* up

* Remove bias for double stream block text QKV projections

* Add script to convert Flux 2 transformer to diffusers

* make style and make quality

* fix a few things.

* allow sft files to go.

* fix image processor

* fix batch

* style a bit

* Fix some bugs in Flux 2 transformer implementation

* Fix dummy input preparation and fix some test bugs

* fix dtype casting in timestep guidance module.

* resolve conflicts.,

* remove ip adapter stuff.

* Fix Flux 2 transformer consistency test

* Fix bug in Flux2TransformerBlock (double stream block)

* Get remaining Flux 2 transformer tests passing

* make style; make quality; make fix-copies

* remove stuff.

* fix type annotaton.

* remove unneeded stuff from tests

* tests

* up

* up

* add sf support

* Remove unused IP Adapter and ControlNet logic from transformer (#9)

* copied from

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: apolinário <joaopaulo.passos@gmail.com>

* up

* up

* up

* up

* up

* Refactor Flux2Attention into separate classes for double stream and single stream attention

* Add _supports_qkv_fusion to AttentionModuleMixin to allow subclasses to disable QKV fusion

* Have Flux2ParallelSelfAttention inherit from AttentionModuleMixin with _supports_qkv_fusion=False

* Log debug message when calling fuse_projections on a AttentionModuleMixin subclass that does not support QKV fusion

* Address review comments

* Update src/diffusers/pipelines/flux2/pipeline_flux2.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* up

* Remove maybe_allow_in_graph decorators for Flux 2 transformer blocks (#12)

* up

* support ostris loras. (#13)

* up

* update schdule

* up

* up (#17)

* add training scripts (#16)

* add training scripts
Co-authored-by: Linoy Tsaban <linoytsaban@gmail.com>

* model cpu offload in validation.

* add flux.2 readme

* add img2img and tests

* cpu offload in log validation

* Apply suggestions from code review

* fix

* up

* fixes

* remove i2i training tests for now.

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Co-authored-by: Linoy Tsaban <linoytsaban@gmail.com>
Co-authored-by: linoytsaban <linoy@huggingface.co>

* up

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Co-authored-by: yiyixuxu <yixu310@gmail.com>
Co-authored-by: Daniel Gu <dgu8957@gmail.com>
Co-authored-by: yiyi@huggingface.co <yiyi@ip-10-53-87-203.ec2.internal>
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: apolinário <joaopaulo.passos@gmail.com>
Co-authored-by: yiyi@huggingface.co <yiyi@ip-26-0-160-103.ec2.internal>
Co-authored-by: Linoy Tsaban <linoytsaban@gmail.com>
Co-authored-by: linoytsaban <linoy@huggingface.co>

* feat: support lora in qwen image and training script

* up

* up

* up

* up

* up

* up

* add lora tests

* fix

* add tests

* fix

* reviewer feedback

* up[

* Apply suggestions from code review
Co-authored-by: Aryan <aryan@huggingface.co>

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Co-authored-by: Aryan <aryan@huggingface.co>

change to 2025 licensing for remaining

* show how metadata stuff should be incorporated in training scripts.

* typing

* fix

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

* make lora target modules configurable and change the default

* style

* make lora target modules configurable and change the default

* fix bug when using prodigy and training te

* fix mixed precision training as  proposed in https://github.com/huggingface/diffusers/pull/9565

 for full dreambooth as well

* add test and notes

* style

* address sayaks comments

* style

* fix test

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

* add ostris trainer to README & add cache latents of vae

* add ostris trainer to README & add cache latents of vae

* style

* readme

* add test for latent caching

* add ostris noise scheduler
https://github.com/ostris/ai-toolkit/blob/9ee1ef2a0a2a9a02b92d114a95f21312e5906e54/toolkit/samplers/custom_flowmatch_sampler.py#L95



* style

* fix import

* style

* fix tests

* style

* --change upcasting of transformer?

* update readme according to main

* keep only latent caching

* add configurable param for final saving of trained layers- --upcast_before_saving

* style

* Update examples/dreambooth/README_flux.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/README_flux.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* use clear_objs_and_retain_memory from utilities

* style

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

* add requirements + fix link to bghira's guide

* text ecnoder training fixes

* text encoder training fixes

* text encoder training fixes

* text encoder training fixes

* style

* add tests

* fix encode_prompt call

* style

* unpack_latents test

* fix lora saving

* remove default val for max_sequenece_length in encode_prompt

* remove default val for max_sequenece_length in encode_prompt

* style

* testing

* style

* testing

* testing

* style

* fix sizing issue

* style

* revert scaling

* style

* style

* scaling test

* style

* scaling test

* remove model pred operation left from pre-conditioning

* remove model pred operation left from pre-conditioning

* fix trainable params

* remove te2 from casting

* transformer to accelerator

* remove prints

* empty commit

* add a test suite for SD3 DreamBooth

* lora suite

* style

* add checkpointing tests for LoRA

* add test to cover train_text_encoder.