GitLab

* introduce integrations module.

* remove duplicate methods.

* better imports.

* move to loaders.py

* remove peftadaptermixin from modelmixin.

* add: peftadaptermixin selectively.

* add: entry to _toctree

* Empty-Commit

Correctly handle creating model index json files when setting compiled modules in pipelines.  (#6436)

update

* 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.

* introduce unload_lora.

* fix-copies

* post release

* style

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

* null-text-inversion-implementation

* edited

* edited

* edited

* edited

* edited

* edit

* makestyle

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

* edebug

* debug

* more debug

* more more debug

* remove tests for LoRAAttnProcessors.

* rename

* unwrap text encoder when saving hook only for full text encoder tuning

* unwrap text encoder when saving hook only for full text encoder tuning

* save embeddings in each checkpoint as well

* save embeddings in each checkpoint as well

* save embeddings in each checkpoint as well

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

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

* Intel Gen 4 Xeon and later support bf16

* fix bf16 notes

* add documentation for DeepCache

* fix typo

* add wandb url for DeepCache

* fix some typos

* add item in _toctree.yml

* update formats for arguments

* Update deepcache.md

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

* add StableDiffusionXLPipeline in doc

* Separate SDPipeline and SDXLPipeline

* Add the paper link of ablation experiments for hyper-parameters

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

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

* Make WDS pipeline interpolation type configurable.

* Make the VAE encoding batch size configurable.

* Make lora_alpha and lora_dropout configurable for LCM LoRA scripts.

* Generalize scalings_for_boundary_conditions function and make the timestep scaling configurable.

* Make LoRA target modules configurable for LCM-LoRA scripts.

* Move resolve_interpolation_mode to src/diffusers/training_utils.py and make interpolation type configurable in non-WDS script.

* apply suggestions from review

fix local links

* Respect offline mode when loading model

* default to local entry if connectionerror

* debug

* debug test_with_different_scales_fusion_equivalence

* use the right method.

* place it right.

* let's see.

* let's see again

* alright then.

* add a comment.

This reverts commit 7715e6c3.

This reverts commit fb4aec0c.

* disable running peft non-peft lora test in the peft env.

* Empty-Commit

* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using.

* Update src/diffusers/models/unet_2d_blocks.py

This changes suggest by maintener.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update src/diffusers/models/unet_2d_blocks.py

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

* Update unet_2d_blocks.py

I changed the Parameter to Args text.

* Update unet_2d_blocks.py

proper indentation set in this file.

* Update unet_2d_blocks.py

a little bit of change in the act_fun argument line.

* I run the black command to reformat style in the code

* Update unet_2d_blocks.py

similar doc-string add to have in the original diffusion repository.

* Batter way to write binarize function

* Solve check_code_quality error

* My mistake to run pull request but not reformated file

* Update image_processor.py

* remove extra variable and space

* Update image_processor.py

* Run ruff libarary to reformat my file

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

Update README_sdxl.md

* 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

* add: test to check if peft loras are loadable in non-peft envs.

* add torch_device approrpiately.

* fix: get_dummy_inputs().

* test logits.

* rename

* debug

* debug

* fix: generator

* new assertion values after fixing the seed.

* shape

* remove print statements and settle this.

* to update values.

* change values when lora config is initialized under a fixed seed.

* update colab link

* update notebook link

* sanity restored by getting the exact same values without peft.

add doc
Co-authored-by: yiyixuxu <yixu310@gmail,com>

correct reading variables

* add clip_skip, freeu, qkv

* fix

* add ip-adapter support

* callback on step end

* update

* fix NoneType bug

* fix

* add guidance scale embedding

* add textual inversion

[bug fix] using snr gamma and prior preservation loss in the dreambooth lora sdxl training scripts (#6356)

* change timesteps used to calculate snr when --with_prior_preservation is enabled

* change timesteps used to calculate snr when --with_prior_preservation is enabled (canonical script)

* style

* revert canonical script to before snr gamma change

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

* add StableDiffusionXLControlNetInpaintPipeline to auto pipeline

* fixed style

* Add unload_ip_adapter method

* Update attn_processors with original layers

* Add test

* Use set_default_attn_processor

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

* start deprecating loraattn.

* fix

* wrap into unet_lora_state_dict

* utilize text_encoder_lora_params

* utilize text_encoder_attn_modules

* debug

* debug

* remove print

* don't use text encoder for test_stable_diffusion_lora

* load the procs.

* set_default_attn_processor

* fix: set_default_attn_processor call.

* fix: lora_components[unet_lora_params]

* checking for 3d.

* 3d.

* more fixes.

* debug

* debug

* debug

* debug

* more debug

* more debug

* more debug

* more debug

* more debug

* more debug

* hack.

* remove comments and prep for a PR.

* appropriate set_lora_weights()

* fix

* fix: test_unload_lora_sd

* fix: test_unload_lora_sd

* use dfault attebtion processors.

* debu

* debug nan

* debug nan

* debug nan

* use NaN instead of inf

* remove comments.

* fix: test_text_encoder_lora_state_dict_unchanged

* attention processor default

* default attention processors.

* default

* style

* Update value_guided_sampling.py

Fix #6409

* Comply code style

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

* Fix gradient-checkpointing option is ignored in SDXL+LoRA training. (#6388)

* Fix gradient-checkpointing option is ignored in SD+LoRA training.

* Fix gradient checkpoint is not applied to text encoders. (SDXL+LoRA)

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

* Add new state_dict_utils to __init__ utils

* style

---------
Co-authored-by: multimodalart <joaopaulo.passos+multimodal@gmail.com>