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* login

* more logins

* uploads

* missed login

* another missed login

* downloads

* examples and more logins

* fix

* setup

* Apply style fixes

* fix

* Apply style fixes

* update

* fix

* feedback

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

* add resolution changes tests to hotswapping test suite.

* fixes

* docs

* explain duck shapes

* fix

draft

update

* combine

* Update docs/source/en/optimization/fp16.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

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

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

* refactor adapter docs

* ip-adapter

* ip adapter

* fix toctree

* fix toctree

* lora

* images

* controlnet

* feedback

* controlnet

* t2i

* fix typo

* feedback

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

* reformat

* initial

* fin

* review

* inference

* feedback

* feedback

* feedback

* docs: promote the usage of automodel.

* bitsandbytes

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

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

* disable peft input autocast

* use new peft method name; only disable peft input autocast if submodule layerwise casting active

* add test; reference PeftInputAutocastDisableHook in peft docs

* add load_lora_weights test

* casted -> cast

* Update tests/lora/utils.py

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

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

* allow loras to be loaded with low_cpu_mem_usage.

* add flux support but note https://github.com/huggingface/diffusers/pull/9510\#issuecomment-2378316687



* low_cpu_mem_usage.

* fix-copies

* fix-copies again

* tests

* _LOW_CPU_MEM_USAGE_DEFAULT_LORA

* _peft_version default.

* version checks.

* version check.

* version check.

* version check.

* require peft 0.13.1.

* explicitly specify low_cpu_mem_usage=False.

* docs.

* transformers version 4.45.2.

* update

* fix

* empty

* better name initialize_dummy_state_dict.

* doc todos.

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

* style

* fix-copies

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

* [docs] Replace runwayml/stable-diffusion-v1-5 with Lykon/dreamshaper-8

Updated documentation as runwayml/stable-diffusion-v1-5 has been removed from Huggingface.

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

* Replace with stable-diffusion-v1-5/stable-diffusion-v1-5

* Update inpaint.md

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

* fix typo

* Fix typos

* chore: Fix typos

* chore: Update README.md for promptdiffusion example

* Trim trailing white spaces

* Fix a typo

* update number

* chore: update number

* Trim trailing white space

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

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

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

added accelerator based gradient accumulation for basic_example
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* introduce  to promote reusability.

* up

* add more tests

* up

* remove comments.

* fix fuse_nan test

* clarify the scope of fuse_lora and unfuse_lora

* remove space

* rewrite fuse_lora a bit.

* feedback

* copy over load_lora_into_text_encoder.

* address dhruv's feedback.

* fix-copies

* fix issubclass.

* num_fused_loras

* fix

* fix

* remove mapping

* up

* fix

* style

* fix-copies

* change to SD3TransformerLoRALoadersMixin

* Apply suggestions from code review
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* up

* handle wuerstchen

* up

* move lora to lora_pipeline.py

* up

* fix-copies

* fix documentation.

* comment set_adapters().

* fix-copies

* fix set_adapters() at the model level.

* fix?

* fix

* loraloadermixin.

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

Revert "[LoRA] introduce LoraBaseMixin to promote reusability. (#8774)"

This reverts commit 527430d0.

* introduce  to promote reusability.

* up

* add more tests

* up

* remove comments.

* fix fuse_nan test

* clarify the scope of fuse_lora and unfuse_lora

* remove space

* rewrite fuse_lora a bit.

* feedback

* copy over load_lora_into_text_encoder.

* address dhruv's feedback.

* fix-copies

* fix issubclass.

* num_fused_loras

* fix

* fix

* remove mapping

* up

* fix

* style

* fix-copies

* change to SD3TransformerLoRALoadersMixin

* Apply suggestions from code review
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* up

* handle wuerstchen

* up

* move lora to lora_pipeline.py

* up

* fix-copies

* fix documentation.

* comment set_adapters().

* fix-copies

* fix set_adapters() at the model level.

* fix?

* fix

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

added line allowing gradient accumulation to work for basic_training example

* add docs on model sharding

* add entry to _toctree.

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

* simplify wording

* add a note on transformer library handling

* move device placement section

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

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

* add note on caching in fast diffusion

* formatting

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

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

* Trim all the trailing white space in the whole repo

* Remove unnecessary empty places

* make style && make quality

* Trim trailing white space

* trim

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

sampling bug fix in basic_training.md

In the diffusers basic training tutorial, setting the manual seed argument (generator=torch.manual_seed(config.seed)) in the pipeline call inside evaluate() function rewinds the dataloader shuffling, leading to overfitting due to the model seeing same sequence of training examples after every evaluation call. Using generator=torch.Generator(device='cpu').manual_seed(config.seed) avoids this.

* autopipeline

* edits

* feedback

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

* Initial commit

* Implemented block lora

- implemented block lora
- updated docs
- added tests

* Finishing up

* Reverted unrelated changes made by make style

* Fixed typo

* Fixed bug + Made text_encoder_2 scalable

* Integrated some review feedback

* Incorporated review feedback

* Fix tests

* Made every module configurable

* Adapter to new lora test structure

* Final cleanup

* Some more final fixes

- Included examples in `using_peft_for_inference.md`
- Added hint that only attns are scaled
- Removed NoneTypes
- Added test to check mismatching lens of adapter names / weights raise error

* Update using_peft_for_inference.md

* Update using_peft_for_inference.md

* Make style, quality, fix-copies

* Updated tutorial;Warning if scale/adapter mismatch

* floats are forwarded as-is; changed tutorial scale

* make style, quality, fix-copies

* Fixed typo in tutorial

* Moved some warnings into `lora_loader_utils.py`

* Moved scale/lora mismatch warnings back

* Integrated final review suggestions

* Empty commit to trigger CI

* Reverted emoty commit to trigger CI

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

add missing output image

* merge loras

* feedback

* torch.compile

* feedback

more elaborate example for peft torch.compile

* Update using_peft_for_inference.md

* add more explanation

change to 2024

* edits

* fix

* feedback

fix local links

add note on fp16

add details concerning diffusers-specific bits.