GitLab

* 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

* Fixed the bug related to saving DeepSpeed models.

* Add information about training SD models using DeepSpeed to the README.

* Apply suggestions from code review

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Co-authored-by: mhh001 <mahonghao1@huawei.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add animatediff img2vid

* fix

* Update examples/community/README.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix code snippet between ip adapter face id and animatediff img2vid

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

* fixes bugs:
1. redundant retraction
2. param clone
3. stopping optimization of text encoder params

* param upscaling

* style

resolve conflicts

* Fixes #6418 Advanced Dreambooth LoRa Training

* change order of import to fix nit

* fix nit, use cast_training_params

* remove torch.compile fix, will move to a new PR

* remove unnecessary import

Enable image resizing to adjust its height and width in StableDiffusionXLInstructPix2PixPipeline (#6581)

* Enable image resizing to adjust its height and width in StableDiffusionXLInstructPix2PixPipeline

* Ensure that validation is performed at every 'validation_step', not at every step

* fix training resume

* update

* update

* Add support for IPAdapter FaceID

* Add docs

* Move subfolder to kwargs

* Fix quality

* Fix image encoder loading

* Fix loading + add test

* Move to community folder

* Fix style

* Revert constant update

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

* fix multicontrolnet support

* update README with multicontrolnet example

* Update train_text_to_image_sdxl.py

* Update train_text_to_image_lora_sdxl.py

update for t2i_adapter

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>

* changes for pix2pix_sdxl

* style fix

* added torch.compile for pix2pix

* required changes

make compile compatible

make compile compatible

* torch compatible

* code quality fix

* ruff style

* ruff format

create a utility for casting the lora params during training.

* fix: training resume from fp16.

* add: comment

* remove residue from another branch.

* remove more residues.

* thanks to Younes; no hacks.

* style.

* clean things a bit and modularize _set_state_dict_into_text_encoder

* add comment about the fix detailed.

* support compile

* make style

* move unwrap_model inside function

* change unwrap call

* run make style

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

* Revert "Update examples/dreambooth/train_dreambooth.py"

This reverts commit 70ab09732e7cfec0b19c497f823ddd1c8259dad0.

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

* added unwrapper

* fiz typo

* update: make controlnet script torch compile compatible
Signed-off-by: Suvaditya Mukherjee <suvadityamuk@gmail.com>

* update: correct earlier mistakes for compilation
Signed-off-by: Suvaditya Mukherjee <suvadityamuk@gmail.com>

* update: fix code style issues
Signed-off-by: Suvaditya Mukherjee <suvadityamuk@gmail.com>

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Signed-off-by: Suvaditya Mukherjee <suvadityamuk@gmail.com>

* make torch.compile compatible

* fix quality

support compile

pass tracker name as argumentw

* add stylealigned sdxl pipeline

* bugfix

* update docs

* remove einops dependency

* update README

* update example docstring

make checkpointing compatible when using torch.compile.

* Fix bug where unet's time_cond_proj_dim is not set correctly if using args.unet_time_cond_proj_dim.

* make style

* 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

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

* make it torch.compile comaptible

* make the text encoder compatible too.

* style

* upload codes and doc

* lint

* lint

* lint

* update code

* remove blank lines

* Fix load url

* enable stable-xl textual inversion

* check if optimizer_2 exists

* check text_encoder_2 before using

* add textual inversion for sdxl in a single file

* fix style

* fix example style

* reset for error changes

* add readme for sdxl

* fix style

* disable autocast as it will cause cast error when weight_dtype=bf16

* fix spelling error

* fix style and readme and 8bit optimizer

* add README_sdxl.md link

* add tracker key on log_validation

* run style

* rm the second center crop

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

* init works

* add gluegen pipeline

* add gluegen code

* add another way to load language adapter

* make style

* Update README.md

* change doc

* 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.

* post release

* style

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

* null-text-inversion-implementation

* edited

* edited

* edited

* edited

* edited

* edit

* makestyle

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