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fix diffedit code mistake

typo fix in example docstring in audioldm pipeline

Signed-off-by: Raphael <oOraph@users.noreply.github.com>
Co-authored-by: Raphael <oOraph@users.noreply.github.com>

* start improving single file load

* Fix more

* start improving single file load

* Fix sd 2.1

* further improve from_single_file

FIX force_download in download utils

* feat: add a cli util for fp16 and safetensors format.

* fix: commit_description.

* add: usage example.

* add dreambooth lora script for SDXL incorporating latest changes.

* remove use_auth_token=True.

* add: documentation

* remove unneeded cli.

* increase the number of training steps in the readme.

* add LoraLoaderMixin to the subclassing mix.

* add sdxl lora dreambooth test.

* add: inference code sample.

* add: refiner output.

* add LoraLoaderMixin to the mix of classes of StableDiffusionXLImg2ImgPipeline.

* change default resolution of DreamBoothDataset.

* better sdxl report path.

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

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

Update CONTRIBUTING.md

* fix

* correct link

* Fix typo

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

* improve loading subcomponents

* Add test for logging

* improve loading subcomponents

* make style

* make style

* fix

* finish

Remove remaining `not` in upscale pipeline.

* minor improvements to the SDXL doc.

* use_refiner variable.

* fix: typo.

* Update pipeline_stable_diffusion_xl.py

fix a bug

* Update pipeline_stable_diffusion_xl_img2img.py

* Update pipeline_stable_diffusion_xl_img2img.py

* Update pipeline_stable_diffusion_upscale.py

* style

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Co-authored-by: Hu Ye <xiaohuzc@gmail.com>

* Deprecate variant nicely

* make style

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

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

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Fix all sequential offload

* make style

* make style

Update pipeline_dance_diffusion.py

* refactor to support patching LoRA into T5

instantiate the lora linear layer on the same device as the regular linear layer

get lora rank from state dict

tests

fmt

can create lora layer in float32 even when rest of model is float16

fix loading model hook

remove load_lora_weights_ and T5 dispatching

remove Unet#attn_processors_state_dict

docstrings

* text encoder monkeypatch class method

* fix test

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

* Add sdxl prompt embeddings

* Fix more

* fix some slow tests

fix some slow tests

* feat: add Dropout to Flax UNet

* feat: add @compact decorator

* fix: drop nn.compact

* Update pipeline_utils.py

typo in safetensors (safetenstors)

* Update loaders.py

typo in safetensors (safetenstors)

* Update modeling_utils.py

typo in safetensors (safetenstors)

* finish sd xl docs

* make style

* Apply suggestions from code review

* uP

* uP

* Correct

Signed-off-by: GitHub <noreply@github.com>

* improve sd xl

* correct more

* finish

* make style

* fix more

* disable num attenion heads

* finish

* 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 "repla...

* 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

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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.

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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 491bc9f5a640bbf46a97a8e52d6eff7e70eb8e4b.

* 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

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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.

correct checkpoint url.

* 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

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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_consisten...

* 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>