GitLab

* add from_pipe



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Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* add HD-Painter pipeline

* style fixing

* refactor, change doc, fix ruff

* fix docs

* used correct ruff version

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Co-authored-by: Hayk Manukyan <youremail@yourdomain.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

fix

* Fix SVD bug (shape of `time_context`)

* Formatting code

* Formatting src/diffusers/models/transformers/transformer_temporal.py by `make style && make quality`

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Co-authored-by: kevinkhwu <kevinkhwu@tencent.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

update

* add resample option; check denoise_step; update ckpt path

* Add seeding in pipeline to increase reproducibility

* fix typo

* fix typo

* fix ip adapter support

* Update sag pipelines tests, adjust sag pipeline to pass tests

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

* Add `final_sigma_zero` to UniPCMultistep

Effectively the same trick as DDIM's `set_alpha_to_one` and
DPM's `final_sigma_type='zero'`.
Currently False by default but maybe this should be True?

* `final_sigma_zero: bool` -> `final_sigmas_type: str`

Should 1:1 match DPM Multistep now.

* Set `final_sigmas_type='sigma_min'` in UniPC UTs

* pag_initial

* pag_docs

* edit_docs

* custom

* typo

* delete_docs

* whitespace

* make style

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

* initial commit - instantid img2img

* adapting to img2img

* change add_time_ids

* change add_time_ids

* WIP changes

* add strength to timesteps

* check insightface import

* style

* check insightface import changed to warning

* check insightface import changed to warning

* style

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Co-authored-by: apolinário <joaopaulo.passos@gmail.com>

Fixed important typo

* 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

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

* update

* update

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

* speed up test_vae_slicing in animatediff

* speed up test_karras_schedulers_shape for attend and excite.

* style.

* get the static slices out.

* specify torch print options.

* modify

* test run with controlnet

* specify kwarg

* fix: things

* not None

* flatten

* controlnet img2img

* complete controlet sd

* finish more

* finish more

* finish more

* finish more

* finish the final batch

* add cpu check for expected_pipe_slice.

* finish the rest

* remove print

* style

* fix ssd1b controlnet test

* checking ssd1b

* disable the test.

* make the test_ip_adapter_single controlnet test more robust

* fix: simple inpaint

* multi

* disable panorama

* enable again

* panorama is shaky so leave it for now

* remove print

* raise tolerance.

use float16 and add torch.no_grad()

* Bug fix for controlnetpipeline check_image

Bug fix for controlnetpipeline check_image when using multicontrolnet and prompt list

* Update test_inference_multiple_prompt_input function

* Update test_controlnet.py

add test for multiple prompts and multiple image conditioning

* Update test_controlnet.py

Fix format error

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Co-authored-by: Lvkesheng Shen <45848260+Fantast416@users.noreply.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add remove_all_hooks

* a few more fix and tests

* up

* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* split tests

* add

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Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* apple mps: training support for SDXL LoRA

* sdxl: support training lora, dreambooth, t2i, pix2pix, and controlnet on apple mps

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

* flesh out the nightly tests

* address feedback.

import load_model_dict_into_meta only once

Skipping test_lora_fuse_nan on mps
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* make the istructions on fetching all commits clearer.

* Update setup.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

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

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

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

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

diffusers#7426 fix stable diffusion xl inference on MPS when dtypes shift unexpectedly due to pytorch bugs (#7446)

* mps: fix XL pipeline inference at training time due to upstream pytorch bug

* Update src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* apply the safe-guarding logic elsewhere.

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

* Fix typos

* Add docstring to `decode` method in `ConsistencyDecoderVAE`

* Fix tiling

* Enable tiled VAE decoding with customizable tile sample size and overlap factor

* Revert "Enable tiled VAE decoding with customizable tile sample size and overlap factor"

This reverts commit 181049675e83cea7b33ae2bbeba2aff7ae1b1761.

* Add VAE tiling test for `ConsistencyDecoderVAE`

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

* add kohya conversion dict.

* update readme

* typo

* add filename

you cannot specify `type="bool"` and `action="store_true"` at the same time.
remove excessive and buggy `type=bool`.
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>

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

* feat: support dora loras from community

* safe-guard dora operations under peft version.

* pop use_dora when False

* make dora lora from kohya work.

* fix: kohya conversion utils.

* add a fast test for DoRA compatibility..

* add a nightly test.

skip dynamo tests when python is 3.12.

* fixed typo

* updated doc to be consistent in naming

* make style/quality

* preprocessing for 4 channels and not 6

* make style

* test for 4c

* make style/quality

* fixed test on cpu

* fixed doc typo

* changed default ckpt to 4c

* Update pipeline_stable_diffusion_ldm3d.py

* fix bug

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Co-authored-by: Aflalo <estellea@isl-iam1.rr.intel.com>
Co-authored-by: Aflalo <estellea@isl-gpu33.rr.intel.com>
Co-authored-by: Aflalo <estellea@isl-gpu38.rr.intel.com>

* Update test_lora_layers_peft.py

* Update utils.py

* Fix typos

* Fix typos

* Fix typos

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

update

* update

* update

* update

* barebones orpo

* remove reference model.

* full implementation

* change default of beta_orpo

* add a training command.

* fix: dataloading issues.

* interpreting the formulation.

* revert styling

* add: wds full blown version

* fix: per_gpu_batch_siz

* start debuggin

* debugging

* remove print

* fix

* remove filter keys.

* turn on non-blocking calls.

* device_placement

* let's see.

* add bigger training run command

* reinitialize generator for fair repro

* add: detailed readme and requirements

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Co-authored-by: Sayak Paul <sayakpaul@Sayaks-MacBook-Pro-2.local>