GitLab

* 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>

* 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

---------
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

---------
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>

* 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

* 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

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 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>

* 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 WebUI format support to Advanced Training Script

* style

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

* 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>

* add to dreambooth lora.

* add: t2i lora.

* add: sdxl t2i lora.

* style

* lcm lora sdxl.

* unwrap

* fix: enable_adapters().

fix keys for lora format on advanced training scripts

* Fix ProdigyOPT in SDXL Dreambooth script

* style

* style

* Add PEFT to Advanced Training Script

* style

* style

* ✨ style ✨



* change order for logic operation

* add lora alpha

* style

* Align PEFT to new format

* Update train_dreambooth_lora_sdxl_advanced.py

Apply #6355 fix

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

* fix

* style fix

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

Fix bug when creating the guidance embeddings using multiple GPUs.
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>

* spit diffusers-native format from the get go.

* rejig the peft_to_diffusers mapping.

* amused update links to new repo

* lint

Replace the link for wandb log with the correct run

* add: script to train lcm lora for sdxl with 🤗

 datasets

* suit up the args.

* remove comments.

* fix num_update_steps

* fix batch unmarshalling

* fix num_update_steps_per_epoch

* fix; dataloading.

* fix microconditions.

* unconditional predictions debug

* fix batch size.

* no need to use use_auth_token

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* make vae encoding batch size an arg

* final serialization in kohya

* style

* state dict rejigging

* feat: no separate teacher unet.

* debug

* fix state dict serialization

* debug

* debug

* debug

* remove prints.

* remove kohya utility and make style

* fix serialization

* fix

* add test

* add peft dependency.

* add: peft

* remove peft

* autocast device determination from accelerator

* autocast

* reduce lora rank.

* remove unneeded space

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* style

* remove prompt dropout.

* also save in native diffusers ckpt format.

* debug

* debug

* debug

* better formation of the null embeddings.

* remove space.

* autocast fixes.

* autocast fix.

* hacky

* remove lora_sayak

* Apply suggestions from code review
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* style

* make log validation leaner.

* move back enabled in.

* fix: log_validation call.

* add: checkpointing tests

* taking my chances to see if disabling autocasting has any effect?

* start debugging

* name

* name

* name

* more debug

* more debug

* index

* remove index.

* print length

* print length

* print length

* move unet.train() after add_adapter()

* disable some prints.

* enable_adapters() manually.

* remove prints.

* some changes.

* fix params_to_optimize

* more fixes

* debug

* debug

* remove print

* disable grad for certain contexts.

* Add support for IPAdapterFull (#5911)

* Add support for IPAdapterFull
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

---------
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix a bug in `add_noise` function  (#6085)

* fix

* copies

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

* [Advanced Diffusion Script] Add Widget default text (#6100)

add widget

* [Advanced Training Script] Fix pipe example (#6106)

* IP-Adapter for StableDiffusionControlNetImg2ImgPipeline (#5901)

* adapter for StableDiffusionControlNetImg2ImgPipeline

* fix-copies

* fix-copies

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

* IP adapter support for most pipelines (#5900)

* support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py

* support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py

* support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_instruct_pix2pix.py

* update tests

* support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_panorama.py

* support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py

* support ip-adapter in src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py

* support ip-adapter in src/diffusers/pipelines/latent_consistency_models/pipeline_latent_consistency_text2img.py

* support ip-adapter in src/diffusers/pipelines/latent_consistency_models/pipeline_latent_consistency_img2img.py

* support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py

* revert changes to sd_attend_and_excite and sd_upscale

* make style

* fix broken tests

* update ip-adapter implementation to latest

* apply suggestions from review

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

* fix: lora_alpha

* make vae casting conditional/

* param upcasting

* propagate comments from https://github.com/huggingface/diffusers/pull/6145

Co-authored-by: dg845 <dgu8957@gmail.com>

* [Peft] fix saving / loading when unet is not "unet" (#6046)

* [Peft] fix saving / loading when unet is not "unet"

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

* undo stablediffusion-xl changes

* use unet_name to get unet for lora helpers

* use unet_name

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

* [Wuerstchen] fix fp16 training and correct lora args (#6245)

fix fp16 training
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* [docs] fix: animatediff docs (#6339)

fix: animatediff docs

* add: note about the new script in readme_sdxl.

* Revert "[Peft] fix saving / loading when unet is not "unet" (#6046)"

This reverts commit 4c7e983bb5929320bab08d70333eeb93f047de40.

* Revert "[Wuerstchen] fix fp16 training and correct lora args (#6245)"

This reverts commit 0bb9cf0216e501632677895de6574532092282b5.

* Revert "[docs] fix: animatediff docs (#6339)"

This reverts commit 11659a6f74b5187f601eeeeeb6f824dda73d0627.

* remove tokenize_prompt().

* assistive comments around enable_adapters() and diable_adapters().

---------
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Fabio Rigano <57982783+fabiorigano@users.noreply.github.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: apolinário <joaopaulo.passos@gmail.com>
Co-authored-by: Charchit Sharma <charchitsharma11@gmail.com>
Co-authored-by: Aryan V S <contact.aryanvs@gmail.com>
Co-authored-by: dg845 <dgu8957@gmail.com>
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>

fix fp16 training
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Change README LCM-LoRA example learning rates to 1e-4.

fix: set guidance_scale

* remove validation args from textual onverson tests

* reduce number of train steps in textual inversion tests

* fix: directories.

* debig

* fix: directories.

* remove validation tests from textual onversion

* try reducing the time of test_text_to_image_checkpointing_use_ema

* fix: directories

* speed up test_text_to_image_checkpointing

* speed up test_text_to_image_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints

* fix

* speed up test_instruct_pix2pix_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints

* set checkpoints_total_limit to 2.

* test_text_to_image_lora_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints speed up

* speed up test_unconditional_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints

* debug

* fix: directories.

* speed up test_instruct_pix2pix_checkpointing_checkpoints_total_limit

* speed up: test_controlnet_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints

* speed up test_controlnet_sdxl

* speed up dreambooth tests

* speed up test_dreambooth_lora_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints

* speed up test_custom_diffusion_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints

* speed up test_text_to_image_lora_sdxl_text_encoder_checkpointing_checkpoints_total_limit

* speed up # checkpoint-2 should have been deleted

* speed up examples/text_to_image/test_text_to_image.py::TextToImage::test_text_to_image_checkpointing_checkpoints_total_limit

* additional speed ups

* style

fix RuntimeError: Input type (float) and bias type (c10::Half) should be the same in train_text_to_image_lora.py (#6259)

* fix RuntimeError: Input type (float) and bias type (c10::Half) should be the same

* format source code

* format code

* remove the autocast blocks within the pipeline

* add autocast blocks to pipeline caller in train_text_to_image_lora.py

* initialize alpha too.

* add: test

* remove config parsing

* store rank

* debug

* remove faulty test

* Fix ProdigyOPT in SDXL Dreambooth script

* style

* style

* [Community Pipeline] Add Marigold Monocular Depth Estimation

- add single-file pipeline
- update README

* fix format - add one blank line

* format script with ruff

* use direct image link in example code

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

amused

rename

Update docs/source/en/api/pipelines/amused.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

AdaLayerNormContinuous default values

custom micro conditioning

micro conditioning docs

put lookup from codebook in constructor

fix conversion script

remove manual fused flash attn kernel

add training script

temp remove training script

add dummy gradient checkpointing func

clarify temperatures is an instance variable by setting it

remove additional SkipFF block args

hardcode norm args

rename tests folder

fix paths and samples

fix tests

add training script

training readme

lora saving and loading

non-lora saving/loading

some readme fixes

guards

Update docs/source/en/api/pipelines/amused.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Update examples/amused/README.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Update examples/amused/train_amused.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

vae upcasting

add fp16 integration tests

use tuple for micro cond

copyrights

remove casts

delegate to torch.nn.LayerNorm

move temperature to pipeline call

upsampling/downsampling changes