GitLab

* add: controlnet sdxl.

* modifications to controlnet.

* run styling.

* add: __init__.pys

* incorporate https://github.com/huggingface/diffusers/pull/4019

 changes.

* run make fix-copies.

* resize the conditioning images.

* remove autocast.

* run styling.

* disable autocast.

* debugging

* device placement.

* back to autocast.

* remove comment.

* save some memory by reusing the vae and unet in the pipeline.

* apply styling.

* Allow low precision sd xl

* finish

* finish

* changes to accommodate the improved VAE.

* modifications to how we handle vae encoding in the training.

* make style

* make existing controlnet fast tests pass.

* change vae checkpoint cli arg.

* fix: vae pretrained paths.

* fix: steps in get_scheduler().

* debugging.

* debugging./

* fix: weight conversion.

* add: docs.

* add: limited tests./

* add: datasets to the requirements.

* update docstrings and incorporate the usage of watermarking.

* incorporate fix from #4083

* fix watermarking dependency handling.

* run make-fix-copies.

* Empty-Commit

* Update requirements_sdxl.txt

* remove vae upcasting part.

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* run make style

* run make fix-copies.

* disable suppot for multicontrolnet.

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* run make fix-copies.

* dtyle/.

* fix-copies.

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

* Add Recent Timestep Scheduling Improvements to DDIM Inverse Scheduler

Roll timesteps by one to reflect origin-destination semantic discrepancy

Restore `set_alpha_to_one` option to handle negative initial timesteps

Remove `set_alpha_to_zero` option not used due to previous truncation

* Bugfix

* Remove unnecessary calls to `detach()`

Use `self.image_processor.preprocess` in DiffEdit pipeline functions

* Preprocess list input for inverted image latents in diffedit pipeline

* Add `timestep_spacing` and `steps_offset` to `DPMSolverMultistepInverseScheduler`

* Update expected test results to account for inverting last forward diffusion step

* Fix inversion progress bar bug

* Add first draft for proper fast tests for DDIMInverseScheduler

* Add deprecated DDIMInverseScheduler kwarg to ConfigMixer registry

* Fix test failure in DPMMultistepInverseScheduler

Invert step specification leads to negative noise variance in SDE-based algs

Add first draft for proper fast tests for DPMMultistepInverseScheduler

* Update expected test results to account for inverting last forward diffusion step

Clean up diffedit fast test

* create general cpu offload & execution device

* Remove boiler plate

* finish

* kp

* Correct offload more pipelines

* up

* Update src/diffusers/pipelines/pipeline_utils.py

* make style

* up

* Quick implementation of t2i-adapter

Load adapter module with from_pretrained

Prototyping generalized adapter framework

Writeup doc string for sideload framework(WIP) + some minor update on implementation

Update adapter models

Remove old adapter optional args in UNet

Add StableDiffusionAdapterPipeline unit test

Handle cpu offload in StableDiffusionAdapterPipeline

Auto correct coding style

Update model repo name to "RzZ/sd-v1-4-adapter-pipeline"

Refactor MultiAdapter to better compatible with config system

Export MultiAdapter

Create pipeline document template from controlnet

Create dummy objects

Supproting new AdapterLight model

Fix StableDiffusionAdapterPipeline common pipeline test

[WIP] Update adapter pipeline document

Handle num_inference_steps in StableDiffusionAdapterPipeline

Update definition of Adapter "channels_in"

Update documents

Apply code style

Fix doc typo and merge error

Update doc string and example

Quality of life improvement

Remove redundant code and file from prototyping

Remove unused pageage

Remove comments

Fix title

Fix typo

Add conditioning scale arg

Bring back old implmentation

Offload sideload

Add supply info on document

Update src/diffusers/models/adapter.py
Co-authored-by: Will Berman <wlbberman@gmail.com>

Update MultiAdapter constructor

Swap out custom checkpoint and update pipeline constructor

Update docment

Apply suggestions from code review
Co-authored-by: Will Berman <wlbberman@gmail.com>

Correcting style

Following single-file policy

Update auto size in image preprocess func

Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_adapter.py
Co-authored-by: Will Berman <wlbberman@gmail.com>

fix copies

Update adapter pipeline behavior

Add adapter_conditioning_scale doc string

Add the missing doc string

Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Fix few bugs from suggestion

Handle L-mode PIL image as control image

Rename to differentiate adapter resblock

Update src/diffusers/models/adapter.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Fix typo

Update adapter parameter name

Update test case and code style

Fix copies

Fix typo

Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_adapter.py
Co-authored-by: Will Berman <wlbberman@gmail.com>

Update Adapter class name

Add checkpoint converting script

Fix style

Fix-copies

Remove dev script

Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Updates for parameter rename

Fix convert_adapter

remove main

fix diff

more

refactoring

more

more

small fixes

refactor

tests

more slow tests

more tests

Update docs/source/en/api/pipelines/overview.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

add community contributor to docs

Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

fix

remove from_adapters

license

paper link

docs

more url fixes

more docs

fix

fixes

fix

fix

* fix sample inplace add

* additional_kwargs -> additional_residuals

* move t2i adapter pipeline to own module

* preprocess -> _preprocess_adapter_image

* add TencentArc to license

* fix example code links

* add image converter and fix example doc string

* fix links

* clearer additional residual application

---------
Co-authored-by: HimariO <dsfhe49854@gmail.com>

* add noise_sampler to StableDiffusionKDiffusionPipeline

* fix/docs: Fix the broken doc links (#3897)

* fix/docs: Fix the broken doc links
Signed-off-by: GitHub <noreply@github.com>

* Update docs/source/en/using-diffusers/write_own_pipeline.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

---------
Signed-off-by: GitHub <noreply@github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Add video img2img (#3900)

* Add image to image video

* Improve

* better naming

* make fix copies

* add docs

* finish tests

* trigger tests

* make style

* correct

* finish

* Fix more

* make style

* finish

* fix/doc-code: Updating to the latest version parameters (#3924)

fix/doc-code: update to use the new parameter
Signed-off-by: GitHub <noreply@github.com>

* fix/doc: no import torch issue (#3923)

Ffix/doc: no import torch issue
Signed-off-by: GitHub <noreply@github.com>

* Correct controlnet out of list error (#3928)

* Correct controlnet out of list error

* Apply suggestions from code review

* correct tests

* correct tests

* fix

* test all

* Apply suggestions from code review

* test all

* test all

* Apply suggestions from code review

* Apply suggestions from code review

* fix more tests

* Fix more

* Apply suggestions from code review

* finish

* Apply suggestions from code review

* Update src/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py

* finish

* Adding better way to define multiple concepts and also validation capabilities. (#3807)

* - Added validation parameters
- Changed some parameter descriptions to better explain their use.
- Fixed a few typos.
- Added concept_list parameter for better management of multiple subjects
- changed logic for image validation

* - Fixed bad logic for class data root directories

* Defaulting validation_steps to None for an easier logic

* Fixed multiple validation prompts

* Fixed bug on validation negative prompt

* Changed validation logic for tracker.

* Added uuid for validation image labeling

* Fix error when comparing validation prompts and validation negative prompts

* Improved error message when negative prompts for validation are more than the number of prompts

* - Changed image tracking number from epoch to global_step
- Added Typing for functions

* Added some validations more when using concept_list parameter and the regular ones.

* Fixed error message

* Added more validations for validation parameters

* Improved messaging for errors

* Fixed validation error for parameters with default values

* - Added train step to image name for validation
- reformatted code

* - Added train step to image's name for validation
- reformatted code

* Updated README.md file.

* reverted back original script of train_dreambooth.py

* reverted back original script of train_dreambooth.py

* left one blank line at the eof

* reverted back setup.py

* reverted back setup.py

* added same logic for when parameters for prior preservation are used without enabling the flag while using concept_list parameter.

* Ran black formatter.

* fixed a few strings

* fixed import sort with isort and removed fstrings without placeholder

* fixed import order with ruff (since with isort wasn't ok)

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

* [ldm3d] Update code to be functional with the new checkpoints (#3875)

* 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

---------
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>

* Improve memory text to video (#3930)

* Improve memory text to video

* Apply suggestions from code review

* add test

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* finish test setup

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

* revert automatic chunking (#3934)

* revert automatic chunking

* Apply suggestions from code review

* revert automatic chunking

* avoid upcasting by assigning dtype to noise tensor (#3713)

* avoid upcasting by assigning dtype to noise tensor

* make style

* Update train_unconditional.py

* Update train_unconditional.py

* make style

* add unit test for pickle

* revert change

---------
Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

* Fix failing np tests (#3942)

* Fix failing np tests

* Apply suggestions from code review

* Update tests/pipelines/test_pipelines_common.py

* Add `timestep_spacing` and `steps_offset` to schedulers (#3947)

* Add timestep_spacing to DDPM, LMSDiscrete, PNDM.

* Remove spurious line.

* More easy schedulers.

* Add `linspace` to DDIM

* Noise sigma for `trailing`.

* Add timestep_spacing to DEISMultistepScheduler.

Not sure the range is the way it was intended.

* Fix: remove line used to debug.

* Support timestep_spacing in DPMSolverMultistep, DPMSolverSDE, UniPC

* Fix: convert to numpy.

* Use sched. defaults when instantiating from_config

For params not present in the original configuration.

This makes it possible to switch pipeline schedulers even if they use
different timestep_spacing (or any other param).

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Missing args in DPMSolverMultistep

* Test: default args not in config

* Style

* Fix scheduler name in test

* Remove duplicated entries

* Add test for solver_type

This test currently fails in main. When switching from DEIS to UniPC,
solver_type is "logrho" (the default value from DEIS), which gets
translated to "bh1" by UniPC. This is different to the default value for
UniPC: "bh2". This is where the translation happens: https://github.com/huggingface/diffusers/blob/36d22d0709dc19776e3016fb3392d0f5578b0ab2/src/diffusers/schedulers/scheduling_unipc_multistep.py#L171



* UniPC: use same default for solver_type

Fixes a bug when switching from UniPC from another scheduler (i.e.,
DEIS) that uses a different solver type. The solver is now the same as
if we had instantiated the scheduler directly.

* do not save use default values

* fix more

* fix all

* fix schedulers

* fix more

* finish for real

* finish for real

* flaky tests

* Update tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py

* Default steps_offset to 0.

* Add missing docstrings

* Apply suggestions from code review

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

* Add Consistency Models Pipeline (#3492)

* initial commit

* Improve consistency models sampling implementation.

* Add CMStochasticIterativeScheduler, which implements the multi-step sampler (stochastic_iterative_sampler) in the original code, and make further improvements to sampling.

* Add Unet blocks for consistency models

* Add conversion script for Unet

* Fix bug in new unet blocks

* Fix attention weight loading

* Make design improvements to ConsistencyModelPipeline and CMStochasticIterativeScheduler and add initial version of tests.

* make style

* Make small random test UNet class conditional and set resnet_time_scale_shift to 'scale_shift' to better match consistency model checkpoints.

* Add support for converting a test UNet and non-class-conditional UNets to the consistency models conversion script.

* make style

* Change num_class_embeds to 1000 to better match the original consistency models implementation.

* Add support for distillation in pipeline_consistency_models.py.

* Improve consistency model tests:
	- Get small testing checkpoints from hub
	- Modify tests to take into account "distillation" parameter of ConsistencyModelPipeline
	- Add onestep, multistep tests for distillation and distillation + class conditional
	- Add expected image slices for onestep tests

* make style

* Improve ConsistencyModelPipeline:
	- Add initial support for class-conditional generation
	- Fix initial sigma for onestep generation
	- Fix some sigma shape issues

* make style

* Improve ConsistencyModelPipeline:
	- add latents __call__ argument and prepare_latents method
	- add check_inputs method
	- add initial docstrings for ConsistencyModelPipeline.__call__

* make style

* Fix bug when randomly generating class labels for class-conditional generation.

* Switch CMStochasticIterativeScheduler to configuring a sigma schedule and make related changes to the pipeline and tests.

* Remove some unused code and make style.

* Fix small bug in CMStochasticIterativeScheduler.

* Add expected slices for multistep sampling tests and make them pass.

* Work on consistency model fast tests:
	- in pipeline, call self.scheduler.scale_model_input before denoising
	- get expected slices for Euler and Heun scheduler tests
	- make Euler test pass
	- mark Heun test as expected fail because it doesn't support prediction_type "sample" yet
	- remove DPM and Euler Ancestral tests because they don't support use_karras_sigmas

* make style

* Refactor conversion script to make it easier to add more model architectures to convert in the future.

* Work on ConsistencyModelPipeline tests:
	- Fix device bug when handling class labels in ConsistencyModelPipeline.__call__
	- Add slow tests for onestep and multistep sampling and make them pass
	- Refactor fast tests
	- Refactor ConsistencyModelPipeline.__init__

* make style

* Remove the add_noise and add_noise_to_input methods from CMStochasticIterativeScheduler for now.

* Run python utils/check_copies.py --fix_and_overwrite
python utils/check_dummies.py --fix_and_overwrite to make dummy objects for new pipeline and scheduler.

* Make fast tests from PipelineTesterMixin pass.

* make style

* Refactor consistency models pipeline and scheduler:
	- Remove support for Karras schedulers (only support CMStochasticIterativeScheduler)
	- Move sigma manipulation, input scaling, denoising from pipeline to scheduler
	- Make corresponding changes to tests and ensure they pass

* make style

* Add docstrings and further refactor pipeline and scheduler.

* make style

* Add initial version of the consistency models documentation.

* Refactor custom timesteps logic following DDPMScheduler/IFPipeline and temporarily add torch 2.0 SDPA kernel selection logic for debugging.

* make style

* Convert current slow tests to use fp16 and flash attention.

* make style

* Add slow tests for normal attention on cuda device.

* make style

* Fix attention weights loading

* Update consistency model fast tests for new test checkpoints with attention fix.

* make style

* apply suggestions

* Add add_noise method to CMStochasticIterativeScheduler (copied from EulerDiscreteScheduler).

* Conversion script now outputs pipeline instead of UNet and add support for LSUN-256 models and different schedulers.

* When both timesteps and num_inference_steps are supplied, raise warning instead of error (timesteps take precedence).

* make style

* Add remaining diffusers model checkpoints for models in the original consistency model release and update usage example.

* apply suggestions from review

* make style

* fix attention naming

* Add tests for CMStochasticIterativeScheduler.

* make style

* Make CMStochasticIterativeScheduler tests pass.

* make style

* Override test_step_shape in CMStochasticIterativeSchedulerTest instead of modifying it in SchedulerCommonTest.

* make style

* rename some models

* Improve API

* rename some models

* Remove duplicated block

* Add docstring and make torch compile work

* More fixes

* Fixes

* Apply suggestions from code review

* Apply suggestions from code review

* add more docstring

* update consistency conversion script

---------
Co-authored-by: ayushmangal <ayushmangal@microsoft.com>
Co-authored-by: Ayush Mangal <43698245+ayushtues@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add test case for StableDiffusionKDiffusionPipeline noise_sampler

---------
Signed-off-by: GitHub <noreply@github.com>
Co-authored-by: Aisuko <urakiny@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Andrés Mauricio Repetto Ferrero <amd.repetto@gmail.com>
Co-authored-by: estelleafl <estelle.aflalo@intel.com>
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>
Co-authored-by: Prathik Rao <prathikr@usc.edu>
Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
Co-authored-by: ayushmangal <ayushmangal@microsoft.com>
Co-authored-by: Ayush Mangal <43698245+ayushtues@users.noreply.github.com>

* Make accelerate optional

* make accelerate optional

Fix dtype inpaint

* Add more

* more

* up

* Get ensemble of expert denoisers working

* Fix code

* add tests

* up

* Allow low precision sd xl

* finish

* finish

* make style

force accelerate to be installed

* Finish

* make style

* Add circular padding option

* Fix style with black

* Fix corner case with small image size

* Add circular padding test cases

* Fix docstring

* Improve docstring for circular padding, remove slow test case

* Update docs for circular padding argument

* Add images comparison for circular padding

* diffusers#4003 - initial implementation of max_inference_steps

* diffusers#4003 - initial implementation of max_inference_steps and first_inference_step for img2img

* diffusers#4003 - use first_inference_step as an input arg for get_timestamps in img2img

* diffusers#4003 Do not add noise during img2img when we have a defined first timestep

* diffusers#4003 Mild updates after revert

* diffusers#4003 Missing change

* Show implementation with denoising_start and end

* Apply suggestions from code review

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

* move to 0.19.0dev

* Apply suggestions from code review

* add exhaustive tests

* add docs

* finish

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* make style

---------
Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Fixed parameter descriptions

typo fix in example docstring in audioldm pipeline

* start improving single file load

* Fix more

* start improving single file load

* Fix sd 2.1

* further improve from_single_file

FIX force_download in download utils

* add dreambooth lora script for SDXL incorporating latest changes.

* remove use_auth_token=True.

* add: documentation

* remove unneeded cli.

* increase the number of training steps in the readme.

* add LoraLoaderMixin to the subclassing mix.

* add sdxl lora dreambooth test.

* add: inference code sample.

* add: refiner output.

* add LoraLoaderMixin to the mix of classes of StableDiffusionXLImg2ImgPipeline.

* change default resolution of DreamBoothDataset.

* better sdxl report path.

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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

* improve loading subcomponents

* Add test for logging

* improve loading subcomponents

* make style

* make style

* fix

* finish

Remove remaining `not` in upscale pipeline.

* Update pipeline_stable_diffusion_xl.py

fix a bug

* Update pipeline_stable_diffusion_xl_img2img.py

* Update pipeline_stable_diffusion_xl_img2img.py

* Update pipeline_stable_diffusion_upscale.py

* style

---------
Co-authored-by: Hu Ye <xiaohuzc@gmail.com>

* Deprecate variant nicely

* make style

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Fix all sequential offload

* make style

* make style

Update pipeline_dance_diffusion.py

* Add sdxl prompt embeddings

* Fix more

* fix some slow tests

fix some slow tests

* Update pipeline_utils.py

typo in safetensors (safetenstors)

* Update loaders.py

typo in safetensors (safetenstors)

* Update modeling_utils.py

typo in safetensors (safetenstors)

* improve sd xl

* correct more

* finish

* make style

* fix more

* disable num attenion heads

* finish

* refactor prior_transformer

adding conversion script

add pipeline

add step_index from pipeline, + remove permute

add zero pad token

remove copy from statement for betas_for_alpha_bar function

* add

* add

* update conversion script for renderer model

* refactor camera a little bit

* clean up

* style

* fix copies

* Update src/diffusers/schedulers/scheduling_heun_discrete.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* alpha_transform_type

* remove step_index argument

* remove get_sigmas_karras

* remove _yiyi_sigma_to_t

* move the rescale prompt_embeds from prior_transformer to pipeline

* replace baddbmm with einsum to match origial repo

* Revert "replace baddbmm with einsum to match origial repo"

This reverts commit 3f6b435d65dad3e5514cad2f5dd9e4419ca78e0b.

* add step_index to scale_model_input

* Revert "move the rescale prompt_embeds from prior_transformer to pipeline"

This reverts commit 5b5a8e6be918fefd114a2945ed89d8e8fa8be21b.

* move rescale from prior_transformer to pipeline

* correct step_index in scale_model_input

* remove print lines

* refactor prior - reduce arguments

* make style

* add prior_image

* arg embedding_proj_norm -> norm_embedding_proj

* add pre-norm for proj_embedding

* move rescale prompt from pipeline to _encode_prompt

* add img2img pipeline

* style

* copies

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py

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

* Update src/diffusers/models/prior_transformer.py

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

* Update src/diffusers/models/prior_transformer.py

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

* Update src/diffusers/models/prior_transformer.py

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

* Update src/diffusers/models/prior_transformer.py

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

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* finish refactor prior_tranformer

* make style

* refactor renderer

* fix

* make style

* refactor img2img

* remove params_proj

* add test

* add upcast_softmax to prior_transformer

* enable num_images_per_prompt, add save_gif utility

* add

* add fast test

* make style

* add slow test

* style

* add test for img2img

* refactor

* enable batching

* style

* refactor scheduler

* update test

* style

* attempt to solve batch related tests timeout

* add doc

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e_img2img.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* hardcode rendering related config

* update betas_for_alpha_bar on ddpm_scheduler

* fix copies

* fix

* export_to_gif

* style

* second attempt to speed up batching tests

* add doc page to index

* Remove intermediate clipping

* 3rd attempt to speed up batching tests

* Remvoe time index

* simplify scheduler

* Fix more

* Fix more

* fix more

* make style

* fix schedulers

* fix some more tests

* finish

* add one more test

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* style

* apply feedbacks

* style

* fix copies

* add one example

* style

* add example for img2img

* fix doc

* fix more doc strings

* size -> frame_size

* style

* update doc

* style

* fix on doc

* update repo name

* improve the usage example in shap-e img2img

* add usage examples in the shap-e docs.

* consolidate examples.

* minor fix.

* update doc

* Apply suggestions from code review

* Apply suggestions from code review

* remove upcast

* Make sure background is white

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py

* Apply suggestions from code review

* Finish

* Apply suggestions from code review

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py

* Make style

---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Kandinsky2_2

* fix init kandinsky2_2

* kandinsky2_2 fix inpainting

* rename pipelines: remove decoder + 2_2 -> V22

* Update scheduling_unclip.py

* remove text_encoder and tokenizer arguments from doc string

* add test for text2img

* add tests for text2img & img2img

* fix

* add test for inpaint

* add prior tests

* style

* copies

* add controlnet test

* style

* add a test for controlnet_img2img

* update prior_emb2emb api to accept image_embedding or image

* add a test for prior_emb2emb

* style

* remove try except

* example

* fix

* add doc string examples to all kandinsky pipelines

* style

* update doc

* style

* add a top about 2.2

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* vae -> movq

* vae -> movq

* style

* fix the #copied from

* remove decoder from file name

* update doc: add a section for kandinsky 2.2

* fix

* fix-copies

* add coped from

* add copies from for prior

* add copies from for prior emb2emb

* copy from for img2img

* copied from for inpaint

* more copied from

* more copies from

* more copies

* remove the yiyi comments

* Apply suggestions from code review

* Self-contained example, pipeline order

* Import prior output instead of redefining.

* Style

* Make VQModel compatible with model offload.

* Fix copies

---------
Co-authored-by: Shahmatov Arseniy <62886550+cene555@users.noreply.github.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Add new text encoder

* add transformers depth

* More

* Correct conversion script

* Fix more

* Fix more

* Correct more

* correct text encoder

* Finish all

* proof that in works in run local xl

* clean up

* Get refiner to work

* Add red castle

* Fix batch size

* Improve pipelines more

* Finish text2image tests

* Add img2img test

* Fix more

* fix import

* Fix embeddings for classic models (#3888)

Fix embeddings for classic SD models.

* Allow multiple prompts to be passed to the refiner (#3895)

* finish more

* Apply suggestions from code review

* add watermarker

* Model offload (#3889)

* Model offload.

* Model offload for refiner / img2img

* Hardcode encoder offload on img2img vae encode

Saves some GPU RAM in img2img / refiner tasks so it remains below 8 GB.

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

* correct

* fix

* clean print

* Update install warning for `invisible-watermark`

* add: missing docstrings.

* fix and simplify the usage example in img2img.

* fix setup for watermarking.

* Revert "fix setup for watermarking."

This reverts commit 491bc9f5a640bbf46a97a8e52d6eff7e70eb8e4b.

* fix: watermarking setup.

* fix: op.

* run make fix-copies.

* make sure tests pass

* improve convert

* make tests pass

* make tests pass

* better error message

* fiinsh

* finish

* Fix final test

---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* use sample directly instead of the dataclass.

* more usage of directly samples instead of dataclasses

* more usage of directly samples instead of dataclasses

* use direct sample in the pipeline.

* direct usage of sample in the img2img case.

* initial commit

* Improve consistency models sampling implementation.

* Add CMStochasticIterativeScheduler, which implements the multi-step sampler (stochastic_iterative_sampler) in the original code, and make further improvements to sampling.

* Add Unet blocks for consistency models

* Add conversion script for Unet

* Fix bug in new unet blocks

* Fix attention weight loading

* Make design improvements to ConsistencyModelPipeline and CMStochasticIterativeScheduler and add initial version of tests.

* make style

* Make small random test UNet class conditional and set resnet_time_scale_shift to 'scale_shift' to better match consistency model checkpoints.

* Add support for converting a test UNet and non-class-conditional UNets to the consistency models conversion script.

* make style

* Change num_class_embeds to 1000 to better match the original consistency models implementation.

* Add support for distillation in pipeline_consistency_models.py.

* Improve consistency model tests:
	- Get small testing checkpoints from hub
	- Modify tests to take into account "distillation" parameter of ConsistencyModelPipeline
	- Add onestep, multistep tests for distillation and distillation + class conditional
	- Add expected image slices for onestep tests

* make style

* Improve ConsistencyModelPipeline:
	- Add initial support for class-conditional generation
	- Fix initial sigma for onestep generation
	- Fix some sigma shape issues

* make style

* Improve ConsistencyModelPipeline:
	- add latents __call__ argument and prepare_latents method
	- add check_inputs method
	- add initial docstrings for ConsistencyModelPipeline.__call__

* make style

* Fix bug when randomly generating class labels for class-conditional generation.

* Switch CMStochasticIterativeScheduler to configuring a sigma schedule and make related changes to the pipeline and tests.

* Remove some unused code and make style.

* Fix small bug in CMStochasticIterativeScheduler.

* Add expected slices for multistep sampling tests and make them pass.

* Work on consistency model fast tests:
	- in pipeline, call self.scheduler.scale_model_input before denoising
	- get expected slices for Euler and Heun scheduler tests
	- make Euler test pass
	- mark Heun test as expected fail because it doesn't support prediction_type "sample" yet
	- remove DPM and Euler Ancestral tests because they don't support use_karras_sigmas

* make style

* Refactor conversion script to make it easier to add more model architectures to convert in the future.

* Work on ConsistencyModelPipeline tests:
	- Fix device bug when handling class labels in ConsistencyModelPipeline.__call__
	- Add slow tests for onestep and multistep sampling and make them pass
	- Refactor fast tests
	- Refactor ConsistencyModelPipeline.__init__

* make style

* Remove the add_noise and add_noise_to_input methods from CMStochasticIterativeScheduler for now.

* Run python utils/check_copies.py --fix_and_overwrite
python utils/check_dummies.py --fix_and_overwrite to make dummy objects for new pipeline and scheduler.

* Make fast tests from PipelineTesterMixin pass.

* make style

* Refactor consistency models pipeline and scheduler:
	- Remove support for Karras schedulers (only support CMStochasticIterativeScheduler)
	- Move sigma manipulation, input scaling, denoising from pipeline to scheduler
	- Make corresponding changes to tests and ensure they pass

* make style

* Add docstrings and further refactor pipeline and scheduler.

* make style

* Add initial version of the consistency models documentation.

* Refactor custom timesteps logic following DDPMScheduler/IFPipeline and temporarily add torch 2.0 SDPA kernel selection logic for debugging.

* make style

* Convert current slow tests to use fp16 and flash attention.

* make style

* Add slow tests for normal attention on cuda device.

* make style

* Fix attention weights loading

* Update consistency model fast tests for new test checkpoints with attention fix.

* make style

* apply suggestions

* Add add_noise method to CMStochasticIterativeScheduler (copied from EulerDiscreteScheduler).

* Conversion script now outputs pipeline instead of UNet and add support for LSUN-256 models and different schedulers.

* When both timesteps and num_inference_steps are supplied, raise warning instead of error (timesteps take precedence).

* make style

* Add remaining diffusers model checkpoints for models in the original consistency model release and update usage example.

* apply suggestions from review

* make style

* fix attention naming

* Add tests for CMStochasticIterativeScheduler.

* make style

* Make CMStochasticIterativeScheduler tests pass.

* make style

* Override test_step_shape in CMStochasticIterativeSchedulerTest instead of modifying it in SchedulerCommonTest.

* make style

* rename some models

* Improve API

* rename some models

* Remove duplicated block

* Add docstring and make torch compile work

* More fixes

* Fixes

* Apply suggestions from code review

* Apply suggestions from code review

* add more docstring

* update consistency conversion script

---------
Co-authored-by: ayushmangal <ayushmangal@microsoft.com>
Co-authored-by: Ayush Mangal <43698245+ayushtues@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* revert automatic chunking

* Apply suggestions from code review

* revert automatic chunking

* Improve memory text to video

* Apply suggestions from code review

* add test

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* finish test setup

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

* Correct controlnet out of list error

* Apply suggestions from code review

* correct tests

* correct tests

* fix

* test all

* Apply suggestions from code review

* test all

* test all

* Apply suggestions from code review

* Apply suggestions from code review

* fix more tests

* Fix more

* Apply suggestions from code review

* finish

* Apply suggestions from code review

* Update src/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py

* finish