GitLab

* add fast tests for dpm-multi

* add more tests

* style

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

* initial commit

* move modules to import struct

* add dummy objects and _LazyModule

* add lazy import to schedulers

* clean up unused imports

* lazy import on models module

* lazy import for schedulers module

* add lazy import to pipelines module

* lazy import altdiffusion

* lazy import audio diffusion

* lazy import audioldm

* lazy import consistency model

* lazy import controlnet

* lazy import dance diffusion ddim ddpm

* lazy import deepfloyd

* lazy import kandinksy

* lazy imports

* lazy import semantic diffusion

* lazy imports

* lazy import stable diffusion

* move sd output to its own module

* clean up

* lazy import t2iadapter

* lazy import unclip

* lazy import versatile and vq diffsuion

* lazy import vq diffusion

* helper to fetch objects from modules

* lazy import sdxl

* lazy import txt2vid

* lazy import stochastic karras

* fix model imports

* fix bug

* lazy import

* clean up

* clean up

* fixes for tests

* fixes for tests

* clean up

* remove import of torch_utils from utils module

* clean up

* clean up

* fix mistake import statement

* dedicated modules for exporting and loading

* remove testing utils from utils module

* fixes from  merge conflicts

* Update src/diffusers/pipelines/kandinsky2_2/__init__.py

* fix docs

* fix alt diffusion copied from

* fix check dummies

* fix more docs

* remove accelerate import from utils module

* add type checking

* make style

* fix check dummies

* remove torch import from xformers check

* clean up error message

* fixes after upstream merges

* dummy objects fix

* fix tests

* remove unused module import

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

add self.step_index

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

[Pipeline utils] feat: implement push_to_hub for standalone models, schedulers as well as pipelines (#4128)

* feat: implement push_to_hub for standalone models.

* address PR feedback.

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

* remove max_shard_size.

* add: support for scheduler push_to_hub

* enable push_to_hub support for flax schedulers.

* enable push_to_hub for pipelines.

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

* reflect pr feedback.

* address another round of deedback.

* better handling of kwargs.

* add: tests

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

* setting hub staging to False for now.

* incorporate staging test as a separate job.
Co-authored-by: ydshieh <2521628+ydshieh@users.noreply.github.com>

* fix: tokenizer loading.

* fix: json dumping.

* move is_staging_test to a better location.

* better treatment to tokens.

* define repo_id to better handle concurrency

* style

* explicitly set token

* Empty-Commit

* move SUER, TOKEN to test

* collate org_repo_id

* delete repo

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: ydshieh <2521628+ydshieh@users.noreply.github.com>

* 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

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

* 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>

* 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

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

* up

* correct some

* up

* finish