* 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 3f6b435d65.
* add step_index to scale_model_input
* Revert "move the rescale prompt_embeds from prior_transformer to pipeline"
This reverts commit 5b5a8e6be9.
* 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 491bc9f5a6.
* 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.
* add default to unet output to prevent it from being a required arg
* add unit test
* make style
* adjust unit test
* mark as fast test
* adjust assert statement in test
---------
Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
* 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: 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>
* 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>
* - 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>
* 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
* Support for manual CLIP loading in StableDiffusionPipeline - txt2img.
* Update src/diffusers/pipelines/stable_diffusion/convert_from_ckpt.py
* Update variables & according docs to match previous style.
* Updated to match style & quality of 'diffusers'
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
