* 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>
* 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>
* 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
* Add guidance start/stop
* Add guidance start/stop to inpaint class
* Black formatting
* Add support for guidance for multicontrolnet
* Add inclusive end
* Improve design
* correct imports
* Finish
* Finish all
* Correct more
* make style
---------
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>
* added ldm3d pipeline and updated image processor to support depth
* added description
* added paper reference
* added docs
* fixed bug
* added test
* Update tests/pipelines/stable_diffusion/test_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/pipelines/stable_diffusion/test_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* added reference in indexmdx
* reverted changes tto image processor'
* added LDM3DOutput
* Fixes with make style
* fix failing tests for make fix-copies
* aligned with our version
* Update pipeline_stable_diffusion_ldm3d.py
updated the guidance scale
* Fix for failing check_code_quality test
* Code review feedback
* Fix typo in ldm3d_diffusion.mdx
* updated the doc accordnlgy
* copyrights
* fixed test failure
* make style
* added image processor of LDM3D in the documentation:
* added ldm3d doc to toctree
* run make style && make quality
* run make fix-copies
* Update docs/source/en/api/image_processor.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update docs/source/en/api/pipelines/stable_diffusion/ldm3d_diffusion.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update docs/source/en/api/pipelines/stable_diffusion/ldm3d_diffusion.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* updated the safety checker to accept tuple
* make style and make quality
* Update src/diffusers/pipelines/stable_diffusion/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* LDM3D output
* up
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Aflalo <estellea@isl-gpu27.rr.intel.com>
Co-authored-by: Anahita Bhiwandiwalla <anahita.bhiwandiwalla@intel.com>
Co-authored-by: Aflalo <estellea@isl-gpu26.rr.intel.com>
Co-authored-by: Aflalo <estellea@isl-iam1.rr.intel.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Aflalo <estellea@isl-gpu42.rr.intel.com>
Co-authored-by: Aflalo <estellea@isl-gpu43.rr.intel.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 draft for lora text encoder scale
* Improve naming
* fix: training dreambooth lora script.
* Apply suggestions from code review
* Update examples/dreambooth/train_dreambooth_lora.py
* Apply suggestions from code review
* Apply suggestions from code review
* add lora mixin when fit
* add lora mixin when fit
* add lora mixin when fit
* fix more
* fix more
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* support views batch for panorama
* add entry for the new argument
* format entry for the new argument
* add view_batch_size test
* fix batch test and a boundary condition
* add more docstrings
* fix a typos
* fix typos
* add: entry to the doc about view_batch_size.
* Revert "add: entry to the doc about view_batch_size."
This reverts commit a36aeaa9ed.
* add a tip on .
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
VaeImageProcessor.preprocess refactor
* refactored VaeImageProcessor
- allow passing optional height and width argument to resize()
- add convert_to_rgb
* refactored prepare_latents method for img2img pipelines so that if we pass latents directly as image input, it will not encode it again
* added a test in test_pipelines_common.py to test latents as image inputs
* refactored img2img pipelines that accept latents as image:
- controlnet img2img, stable diffusion img2img , instruct_pix2pix
---------
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>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* iterate over unique tokens to avoid duplicate replacements
* added test for multiple references to multi embedding
* adhere to black formatting
* reorder test post-rebase
* add _convert_kohya_lora_to_diffusers
* make style
* add scaffold
* match result: unet attention only
* fix monkey-patch for text_encoder
* with CLIPAttention
While the terrible images are no longer produced,
the results do not match those from the hook ver.
This may be due to not setting the network_alpha value.
* add to support network_alpha
* generate diff image
* fix monkey-patch for text_encoder
* add test_text_encoder_lora_monkey_patch()
* verify that it's okay to release the attn_procs
* fix closure version
* add comment
* Revert "fix monkey-patch for text_encoder"
This reverts commit bb9c61e6fa.
* Fix to reuse utility functions
* make LoRAAttnProcessor targets to self_attn
* fix LoRAAttnProcessor target
* make style
* fix split key
* Update src/diffusers/loaders.py
* remove TEXT_ENCODER_TARGET_MODULES loop
* add print memory usage
* remove test_kohya_loras_scaffold.py
* add: doc on LoRA civitai
* remove print statement and refactor in the doc.
* fix state_dict test for kohya-ss style lora
* Apply suggestions from code review
Co-authored-by: Takuma Mori <takuma104@gmail.com>
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Throw error if strength adjusted num_inference_steps < 1
* Added new fast test to check ValueError raised when num_inference_steps < 1
when strength adjusts the num_inference_steps then the inpainting pipeline should fail
* fix#3487 initial latents are now only scaled by init_noise_sigma when pure noise
updated this commit w.r.t the latest merge here: https://github.com/huggingface/diffusers/pull/3533
* fix
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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
