* make safetensors default
* set default save method as safetensors
* update tests
* update to support saving safetensors
* update test to account for safetensors default
* update example tests to use safetensors
* update example to support safetensors
* update unet tests for safetensors
* fix failing loader tests
* fix qc issues
* fix pipeline tests
* fix example test
---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* move slow pix2pixzero tests to nightly
* move slow panorama tests to nightly
* move txt2video full test to nightly
* clean up
* remove nightly test from text to video pipeline
* move audioldm tests to nightly
* move kandinsky im2img ddpm test to nightly
* move flax dpm test to nightly
* move diffedit dpm test to nightly
* move fp16 slow tests to nightly
* update expected slice so img2img compile tests pass
* use default attn processor
* use default attn processor and update expected slice value to pass test
* use default attn processor
* set default attn processor and update expected slice
* set default attn processor and change precision for check
* set unet to use default attn processor
* fix_batch_xl
* Fix other pipelines as well
* up
* up
* Update tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_inpaint.py
* sort
* up
* Finish it all up Co-authored-by: Bagheera <bghira@users.github.com>
* Co-authored-by: Bagheera bghira@users.github.com
* Co-authored-by: Bagheera <bghira@users.github.com>
* Finish it all up Co-authored-by: Bagheera <bghira@users.github.com>
* initial
* style
* from ...pipelines -> from ..pipeline_util
* make style
* fix-copies
* fix value_guided_sampling oops
* style
* add test
* Show failing test
* update from_pipe
* fix
* add controlnet, additional test and register unused original config
* update for controlnet
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* store unused config as private attribute and pass if can
* add doc
* kandinsky inpaint pipeline does not work with decoder checkpoint
* update doc
* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* style
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix
* Apply suggestions from code review
---------
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>
* Fix the XL ensemble not working for any kerras scheduler sigmas and having an off by one bug
* Update src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl.py
* make sytle
---------
Co-authored-by: Jimmy <39@🇺🇸.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix bug when no cfg
* style
* fix no cfg for shap-e and cycle
* style
* fix no cfg for sdxl
* fix copies
---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>
* Fix bug in ControlNetPipelines with MultiControlNetModel of length 1
* Add tests for varying number of ControlNet models
* Fix missing indexing for control_guidance_start and control_guidance_end
* Fix code quality
* Separate test for MultiControlNet with one model
* Revert formatting of earlier test
* Add controlnet from single file
* Updates
* make style
* finish
* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* 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
* 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: 36d22d0709/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>
* 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>
