GitLab

* 7879 - adjust documentation to use naruto dataset, since pokemon is now gated

* replace references to pokemon in docs

* more references to pokemon replaced

* Japanese translation update

---------
Co-authored-by: bghira <bghira@users.github.com>

* toctree

* optim

* feedback

* improve overview

update

* CheckIn - created DownSubBlocks

* Added extra channels, implemented subblock fwd

* Fixed connection sizes

* checkin

* Removed iter, next in forward

* Models for SD21 & SDXL run through

* Added back pipelines, cleared up connections

* Cleaned up connection creation

* added debug logs

* updated logs

* logs: added input loading

* Update umer_debug_logger.py

* log: Loading hint

* Update umer_debug_logger.py

* added logs

* Changed debug logging

* debug: added more logs

* Fixed num_norm_groups

* Debug: Logging all of SDXL input

* Update umer_debug_logger.py

* debug: updated logs

* checkim

* Readded tests

* Removed debug logs

* Fixed Slow Tests

* Added value ckecks | Updated model_cpu_offload_seq

* accelerate-offloading works ; fast tests work

* Made unet & addon explicit in controlnet

* Updated slow tests

* Added dtype/device to ControlNetXS

* Filled in test model paths

* Added image_encoder/feature_extractor to XL pipe

* Fixed fast tests

* Added comments and docstrings

* Fixed copies

* Added docs ; Updates slow tests

* Moved changes to UNetMidBlock2DCrossAttn

* tiny cleanups

* Removed stray prints

* Removed ip adapters + freeU

- Removed ip adapters + freeU as they don't make sense for ControlNet-XS
- Fixed imports of UNet components

* Fixed test_save_load_float16

* Make style, quality, fix-copies

* Changed loading/saving API for ControlNetXS

- Changed loading/saving API for ControlNetXS
- other small fixes

* Removed ControlNet-XS from research examples

* Make style, quality, fix-copies

* Small fixes

- deleted ControlNetXSModel.init_original
- added time_embedding_mix to StableDiffusionControlNetXSPipeline .from_pretrained / StableDiffusionXLControlNetXSPipeline.from_pretrained
- fixed copy hints

* checkin May 11 '23

* CheckIn Mar 12 '24

* Fixed tests for SD

* Added tests for UNetControlNetXSModel

* Fixed SDXL tests

* cleanup

* Delete Pipfile

* CheckIn Mar 20

Started replacing sub blocks  by `ControlNetXSCrossAttnDownBlock2D` and `ControlNetXSCrossAttnUplock2D`

* check-in Mar 23

* checkin 24 Mar

* Created init for UNetCnxs and CnxsAddon

* CheckIn

* Made from_modules, from_unet and no_control work

* make style,quality,fix-copies & small changes

* Fixed freezing

* Added gradient ckpt'ing; fixed tests

* Fix slow tests(+compile) ; clear naming confusion

* Don't create UNet in init ; removed class_emb

* Incorporated review feedback

- Deleted get_base_pipeline /  get_controlnet_addon for pipes
- Pipes inherit from StableDiffusionXLPipeline
- Made module dicts for cnxs-addon's down/mid/up classes
- Added support for qkv fusion and freeU

* Make style, quality, fix-copies

* Implemented review feedback

* Removed compatibility check for vae/ctrl embedding

* make style, quality, fix-copies

* Delete Pipfile

* Integrated review feedback

- Importing ControlNetConditioningEmbedding now
- get_down/mid/up_block_addon now outside class
- renamed `do_control` to `apply_control`

* Reduced size of test tensors

For this, added `norm_num_groups` as parameter everywhere

* Renamed cnxs-`Addon` to cnxs-`Adapter`

- `ControlNetXSAddon` -> `ControlNetXSAdapter`
- `ControlNetXSAddonDownBlockComponents` -> `DownBlockControlNetXSAdapter`, and similarly for mid/up
- `get_mid_block_addon` -> `get_mid_block_adapter`, and similarly for mid/up

* Fixed save_pretrained/from_pretrained bug

* Removed redundant code

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

* add scheduled pseudo-huber loss training scripts

See #7488

* add reduction modes to huber loss

* [DB Lora] *2 multiplier to huber loss cause of 1/2 a^2 conv.

pairing of https://github.com/kohya-ss/sd-scripts/pull/1228/commits/c6495def1fbbaf2a0233110d50f976ed61620e83

* [DB Lora] add option for smooth l1 (huber / delta)

Pairing of https://github.com/kohya-ss/sd-scripts/pull/1228/commits/dd22958caa56e4db885324f76188c13bdf504569

* [DB Lora] unify huber scheduling

Pairing of https://github.com/kohya-ss/sd-scripts/pull/1228/commits/19a834c3ab448614e8887b07f2bb4e0aaabf0805

* [DB Lora] add snr huber scheduler

Pairing of https://github.com/kohya-ss/sd-scripts/pull/1228/commits/47fb1a68547e76f33cd54a3da8d2c35b9489c56e



* fixup examples link

* use snr schedule by default in DB

* update all huber scripts with snr

* code quality

* huber: make style && make quality

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

* 7529 do not disable autocast for cuda devices

* Remove typecasting error check for non-mps platforms, as a correct autocast implementation makes it a non-issue

* add autocast fix to other training examples

* disable native_amp for dreambooth (sdxl)

* disable native_amp for pix2pix (sdxl)

* remove tests from remaining files

* disable native_amp on huggingface accelerator for every training example that uses it

* convert more usages of autocast to nullcontext, make style fixes

* make style fixes

* style.

* Empty-Commit

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

* Fix typos

* Fix typos

* Fix typos

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

* 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

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

* cleanse and refactor lora testing suite.

* more cleanup.

* make check_if_lora_correctly_set a utility function

* fix: typo

* retrigger ci

* style

* Add properties and `IPAdapterTesterMixin` tests for `StableDiffusionPanoramaPipeline`

* Fix variable name typo and update comments

* Update deprecated `output_type="numpy"` to "np" in test files

* Discard changes to src/diffusers/pipelines/stable_diffusion_panorama/pipeline_stable_diffusion_panorama.py

* Update test_stable_diffusion_panorama.py

* Update numbers in README.md

* Update get_guidance_scale_embedding method to use timesteps instead of w

* Update number of checkpoints in README.md

* Add type hints and fix var name

* Fix PyTorch's convention for inplace functions

* Fix a typo

* Revert "Fix PyTorch's convention for inplace functions"

This reverts commit 74350cf65b2c9aa77f08bec7937d7a8b13edb509.

* Fix typos

* Indent

* Refactor get_guidance_scale_embedding method in LEditsPPPipelineStableDiffusionXL class

switch to logger.warning

* support and example launch for sdxl turbo

* White space fixes

* Trailing whitespace character

* ruff format

* fix guidance_scale and steps for turbo mode

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

* Create promptdiffusioncontrolnet.py

* Update __init__.py

Added PromptDiffusionControlNetModel

* Update __init__.py

Added PromptDiffusionControlNetModel

* Update promptdiffusioncontrolnet.py

* Create pipeline_prompt_diffusion.py

Added Prompt Diffusion pipeline.

* Create convert_original_promptdiffusion_to_diffusers.py

* Update convert_from_ckpt.py

Added download_promptdiffusion_from_original_ckpt, convert_promptdiffusion_checkpoint

* Update promptdiffusioncontrolnet.py

* Update pipeline_prompt_diffusion.py

* Update README.md

* Update pipeline_prompt_diffusion.py

* Delete src/diffusers/models/promptdiffusioncontrolnet.py

* Update __init__.py

* Update __init__.py

* Delete scripts/convert_original_promptdiffusion_to_diffusers.py

* Update convert_from_ckpt.py

* Update README.md

* Delete examples/community/pipeline_prompt_diffusion.py

* Create README.md

* Create promptdiffusioncontrolnet.py

* Create convert_original_promptdiffusion_to_diffusers.py

* Create pipeline_prompt_diffusion.py

* Update README.md

* Update pipeline_prompt_diffusion.py

* Update README.md

* Update pipeline_prompt_diffusion.py

* Update convert_original_promptdiffusion_to_diffusers.py

* Update promptdiffusioncontrolnet.py

* Update README.md

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

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add dora tags for drambooth lora scripts

* style

* move model helper function in pipeline to EfficiencyMixin

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

* Fix words

* Fix

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

change to 2024

add ipo and hinge loss to dpo trainer

* Update train_diffusion_dpo.py

Address #6702

* Update train_diffusion_dpo_sdxl.py

* Empty-Commit

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

* fix minsnr implementation for v-prediction case

* format code

* always compute snr when snr_gamma is specified

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

* initial commit for unconditional/class-conditional consistency training script

* make style

* Add entry for consistency training script in community README.

* Move consistency training script from community to research_projects/consistency_training

* Add requirements.txt and README to research_projects/consistency_training directory.

* Manually revert community README changes for consistency training.

* Fix path to script after moving script to research projects.

* Add option to load U-Net weights from pretrained model.

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update pipeline_controlnet_sd_xl.py

* Update pipeline_controlnet_xs_sd_xl.py

* move unets to  module 🦋

* parameterize unet-level import.

* fix flax unet2dcondition model import

* models __init__

* mildly depcrecating models.unet_2d_blocks in favor of models.unets.unet_2d_blocks.

* noqa

* correct depcrecation behaviour

* inherit from the actual classes.

* Empty-Commit

* backwards compatibility for unet_2d.py

* backward compatibility for unet_2d_condition

* bc for unet_1d

* bc for unet_1d_blocks

apply fixes from #6547

Bumps [jinja2](https://github.com/pallets/jinja) from 3.1.2 to 3.1.3.
- [Release notes](https://github.com/pallets/jinja/releases)
- [Changelog](https://github.com/pallets/jinja/blob/main/CHANGES.rst)
- [Commits](https://github.com/pallets/jinja/compare/3.1.2...3.1.3

)

---
updated-dependencies:
- dependency-name: jinja2
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

pass tracker name as argumentw

* base template file - train_instruct_pix2pix.py

* additional import and parser argument requried for lora

* finetune only instructpix2pix model -- no need to include these layers

* inject lora layers

* freeze unet model -- only lora layers are trained

* training modifications to train only lora parameters

* store only lora parameters

* move train script to research project

* run quality and style code checks

* move train script to a new folder

* add README

* update README

* update references in README

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

* add: experimental script for diffusion dpo training.

* random_crop cli.

* fix: caption tokenization.

* fix: pixel_values index.

* fix: grad?

* debug

* fix: reduction.

* fixes in the loss calculation.

* style

* fix: unwrap call.

* fix: validation inference.

* add: initial sdxl script

* debug

* make sure images in the tuple are of same res

* fix model_max_length

* report print

* boom

* fix: numerical issues.

* fix: resolution

* comment about resize.

* change the order of the training transformation.

* save call.

* debug

* remove print

* manually detaching necessary?

* use the same vae for validation.

* add: readme.

* handle rest of the stuff related to deprecated lora stuff.

* fix: copies

* don't modify the uNet in-place.

* fix: temporal autoencoder.

* manually remove lora layers.

* don't copy unet.

* alright

* remove lora attn processors from unet3d

* fix: unet3d.

* styl

* Empty-Commit

* files added

* fixing code quality

* fixing code quality

* fixing code quality

* fixing code quality

* sorted import block

* seperated import wandb

* ruff on script

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

* update

* update

* update

* update

* update

* make style

* remove docs

* update

* move to research folder.

* fix-copies

* remove _toctree entry.

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

Bump transformers in /examples/research_projects/realfill

Bumps [transformers](https://github.com/huggingface/transformers) from 4.34.0 to 4.36.0.
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](https://github.com/huggingface/transformers/compare/v4.34.0...v4.36.0

)

---
updated-dependencies:
- dependency-name: transformers
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

Fix typos and trim trailing whitespaces

* Harmonize HF environment variables + deprecate use_auth_token

* fix import

* fix

* ruff format

* not need to use doc-builder's black styling as the doc is styled in ruff

* make fix-copies

* comment

* use run_ruff

* Set usedforsecurity=False in hashlib methods (FIPS compliance)

* update version dependency

* bump hfh version

* bump hfh version