GitLab

* clean scheduler mixin

* up to dpmsolvermultistep

* finish cleaning

* first draft

* fix overview table

* apply feedback

* update reference code

* 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

* 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>

* 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 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>

* 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

* fix sde typo

* fix code style

* add paradigms parallel sampling pipeline

* linting

* ran make fix-copies

* add paradigms parallel sampling pipeline

* linting

* ran make fix-copies

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

* changes based on review

* add docs for paradigms

* update docs with paradigms abstract

* improve documentation, and add tests for ddim/ddpm batch_step_no_noise

* fix docs and run make fix-copies

* minor changes to docs.

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

* move parallel scheduler to new classes for DDPMParallelScheduler and DDIMParallelScheduler

* remove changes for scheduling_ddim, adjust licenses, credits, and commented code

* fix tensor type that is breaking tests

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

* Implement option for rescaling betas to zero terminal SNR

* Implement rescale classifier free guidance in pipeline_stable_diffusion.py

* focus on DDIM

* make style

* make style

* make style

* make style

* Apply suggestions from Peter Lin

* Apply suggestions from Peter Lin

* make style

* Apply suggestions from code review

* Apply suggestions from code review

* make style

* make style

---------
Co-authored-by: MaxWe00 <gitlab.9v1lq@slmail.me>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add use_karras_sigmas

* add karras test

* add doc

* Fix DPM single

* add test

* fix one more bug

* Apply suggestions from code review
Co-authored-by: StAlKeR7779 <stalkek7779@yandex.ru>

---------
Co-authored-by: StAlKeR7779 <stalkek7779@yandex.ru>

* Add DPM-Solver Multistep Inverse Scheduler

* Add draft tests for DiffEdit

* Add inverse sde-dpmsolver steps to tune image diversity from inverted latents

* Fix tests

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

* Add `sigmoid` beta scheduler to `DDPMScheduler` docstring

* Add `sigmoid` beta scheduler to `RePaintScheduler` docstring

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

* add karras sigma to lms discrete scheduler

* add test for lms_scheduler karras

* reformat test lms

* add SDE variant of DPM-Solver and DPM-Solver++

* add test

* fix typo

* fix typo

* fix multistep dpmsolver for cosine schedule (deepfloy-if)

* fix a typo

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

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

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

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

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

* update all dpmsolver (singlestep, multistep, dpm, dpm++) for cosine noise schedule

* add test, fix style

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

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* Review comments

* [Review comment]: Add is_torchsde_available()

* [Review comment]: Test and docs

* [Review comment]

* [Review comment]

* [Review comment]

* [Review comment]

* [Review comment]

---------
Co-authored-by: njindal <njindal@adobe.com>

* Add karras pattern to discrete heun scheduler

* Add integration test

* Fix failing CI on pytorch test on M1 (mps)

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

* Better deprecation message

* Better deprecation message

* Better doc string

* Fixes

* fix more

* fix more

* Improve __getattr__

* correct more

* fix more

* fix

* Improve more

* more improvements

* fix more

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

* make style

* Fix all rest & add tests & remove old deprecation fns

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

add custom timesteps test

add custom timesteps descending order check

docs

timesteps -> custom_timesteps

can only pass one of num_inference_steps and timesteps

* [2737]: Add Karras DPMSolverMultistepScheduler

* [2737]: Add Karras DPMSolverMultistepScheduler

* Add test

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

* fix: repo consistency.

* remove Copied from statement from the set_timestep method.

* fix: test

* Empty commit.
Co-authored-by: njindal <njindal@adobe.com>

---------
Co-authored-by: njindal <njindal@adobe.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* [Config] Fix config prints and save, load

* Only use potential nn.Modules for dtype and device

* Correct vae image processor

* make sure in_channels is not accessed directly

* make sure in channels is only accessed via config

* Make sure schedulers only access config attributes

* Make sure to access config in SAG

* Fix vae processor and make style

* add tests

* uP

* make style

* Fix more naming issues

* Final fix with vae config

* change more

dynamic threshold sampling bug fix and docs

Co-authored-by: wangguan <dizhipeng.dzp@alibaba-inc.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* [2905]: Add Karras pattern to discrete euler

* [2905]: Add Karras pattern to discrete euler

* Review comments

* Review comments

* Review comments

* Review comments

---------
Co-authored-by: njindal <njindal@adobe.com>

* Add support for different model prediction types in DDIMInverseScheduler
Resolve alpha_prod_t_prev index issue for final step of inversion

* Fix old bug introduced when prediction type is "sample"

* Add support for sample clipping for numerical stability and deprecate old kwarg

* Detach sample, alphas, betas

Derive predicted noise from model output before dist. regularization

Style cleanup

* Log loss for debugging

* Revert "Log loss for debugging"

This reverts commit 76ea9c856f99f4c8eca45a0b1801593bb982584b.

* Add comments

* Add inversion equivalence test

* Add expected data for Pix2PixZero pipeline tests with SD 2

* Update tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py

* Remove cruft and add more explanatory comments

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

* [From pretrained] Speed-up loading from cache

* up

* Fix more

* fix one more bug

* make style

* bigger refactor

* factor out function

* Improve more

* better

* deprecate return cache folder

* clean up

* improve tests

* up

* upload

* add nice tests

* simplify

* finish

* correct

* fix version

* rename

* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>

* rename

* correct doc string

* correct more

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

* apply code suggestions

* finish

---------
Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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

* [Schedulers] Correct config changing

* uP

* add tests

* Improve dynamic threshold

* Update code

* Add dynamic threshold to ddim and ddpm

* Encapsulate and leverage code copy mechanism

Update style

* Clean up DDPM/DDIM constructor arguments

* add test

* also add to unipc

---------
Co-authored-by: Peter Lin <peterlin9863@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>