GitLab

* finish

* finish

* docs: initial pt translation

* docs: add pt build to github workflow and fix some missing translations

* fix error reported 'find_unused_parameters' running in mutiple GPUs or NPUs

* fix code check of importing module by its alphabetic order

---------
Co-authored-by: jiaqiw <wangjiaqi50@huawei.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* internal classes api

* add internal class overview

* fix toctree

* disable freeu debug

* debug

* potentially fix.

* finish

* manually remove the spaces

* remove tab

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

* upload custom remote poc

* up

* make style

* finish

* better name

* Apply suggestions from code review

* Update tests/pipelines/test_pipelines.py

* more fixes

* remove ipdb

* more fixes

* fix more

* finish tests

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Optimize test configurations for faster execution

* [Tests] Speed up expert of mixture tests

* make style

* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using.

* Update src/diffusers/models/unet_2d_blocks.py

This changes suggest by maintener.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update src/diffusers/models/unet_2d_blocks.py

Add suggested text
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update unet_2d_blocks.py

I changed the Parameter to Args text.

* Update unet_2d_blocks.py

proper indentation set in this file.

* Update unet_2d_blocks.py

a little bit of change in the act_fun argument line.

* I run the black command to reformat style in the code

* Update unet_2d_blocks.py

similar doc-string add to have in the original diffusion repository.

* I use a lower method in the activation function.

* Replace multiple if-else statements with a dictionary of activation functions, and call one if statement to retrieve the appropriate function.

* I am using black package to reforamted my file

* I defined the ACTIVATION_FUNCTIONS variable outside of the function

* activation function variable convert to lower case

* First, I resolved the conflict issue. Then, I ran the Black package to reformat my file.

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Add from_pt flag to enable model from PT

* Format the file

* Reformat the file

* first draft

* make fix-copies

* add peft section

* manual fix

* make fix-copies again

* manually revert changes to other files

fix wrong parameter

Fix missing punctuation.

* improvement: add typehints and docs to src/diffusers/models/attention_processor.py

* improvement: add typehints and docs to src/diffusers/models/vae.py

* improvement: add missing docs in src/diffusers/models/vq_model.py

* improvement: add typehints and docs to src/diffusers/models/transformer_temporal.py

* improvement: add typehints and docs to src/diffusers/models/t5_film_transformer.py

* improvement: add type hints to src/diffusers/models/unet_1d_blocks.py

* improvement: add missing type hints to src/diffusers/models/unet_2d_blocks.py

* fix: CI error (make fix-copies required)

* fix: CI error (make fix-copies required again)

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Add a new community pipeline

examples/community/latent_consistency_img2img.py

which can be called like this

import torch
from diffusers import DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained(
                "SimianLuo/LCM_Dreamshaper_v7", custom_pipeline="latent_consistency_txt2img", custom_revision="main")

            # To save GPU memory, torch.float16 can be used, but it may compromise image quality.
pipe.to(torch_device="cuda", torch_dtype=torch.float32)

img2img=LatentConsistencyModelPipeline_img2img(
    vae=pipe.vae,
    text_encoder=pipe.text_encoder,
    tokenizer=pipe.tokenizer,
    unet=pipe.unet,
    #scheduler=pipe.scheduler,
    scheduler=None,
    safety_checker=None,
    feature_extractor=pipe.feature_extractor,
    requires_safety_checker=False,
)

img = Image.open("thisismyimage.png")

result = img2img(prompt,img,strength,num_inference_steps=4)

* Apply suggestions from code review

Fix name formatting for scheduler
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* update readme (and run formatter on latent_consistency_img2img.py)

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

* [Schedulers] Fix 2nd order other than heun

* Apply suggestions from code review

* fix

* fix copies

* remove heun from tests

* add back heun and fix the tests to include 2nd order

* fix the other test too

* Apply suggestions from code review

* Apply suggestions from code review

* Apply suggestions from code review

* make style

* add more comments

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

Signed-off-by: AnyISalIn <anyisalin@gmail.com>

Signed-off-by: mymusise <mymusise1@gmail.com>

* initial commit for LatentConsistencyModelPipeline and LCMScheduler based on the community pipeline

* Add callback and freeu support.

* apply suggestions from review

* Clean up LCMScheduler

* Remove timeindex argument to LCMScheduler.step.

* Add support for clipping or thresholding the predicted original sample.

* Remove unused methods and arguments in LCMScheduler.

* Improve comment about (lack of) negative prompt support.

* Change input guidance_scale to match the StableDiffusionPipeline (Imagen) CFG formulation.

* Move lcm_origin_steps from pipeline __call__ to LCMScheduler.__init__/config (as origin_steps).

* Fix typo when clipping/thresholding in LCMScheduler.

* Add some initial LCMScheduler tests.

* add type annotations from review

* Fix type annotation bug.

* Override test_add_noise_device in LCMSchedulerTest since hardcoded timesteps doesn't work under default settings.

* Add generator argument pipeline prepare_latents call.

* Cast LCMScheduler.timesteps to long in set_timesteps.

* Add onestep and multistep full loop scheduler tests.

* Set default height/width to None and don't hardcode guidance scale embedding dim.

* Add initial LatentConsistencyPipeline fast and slow tests.

* Add initial documentation for LatentConsistencyModelPipeline and LCMScheduler.

* Make remaining failing fast tests pass.

* make style

* Make original_inference_steps configurable from pipeline __call__ again.

* make style

* Remove guidance_rescale arg from pipeline __call__ since LCM currently doesn't support CFG.

* Make LCMScheduler defaults match config of LCM_Dreamshaper_v7 checkpoint.

* Fix LatentConsistencyPipeline slow tests and add dummy expected slices.

* Add checks for original_steps in LCMScheduler.set_timesteps.

* make fix-copies

* Improve LatentConsistencyModelPipeline docs.

* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>

* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>

* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>

* Update src/diffusers/schedulers/scheduling_lcm.py

* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>

* finish

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Aryan V S <avs050602@gmail.com>

* first draft

* feedback

* feedback

* Finished _toctree.yml and index.md

* Finished installation.md

* Properly finished installation.md and almost finished quicktour

* Finished quicktour

* Finished stable diffusion doc

* Fixed _toctree.yml

* Fixed requests

* Fix country code

* Properly push

* Register BaseOutput subclasses as supported torch.utils._pytree nodes

* lint

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* move out the activations.

* move normalization layers.

* add doc.

* add doc.

* fix: paths

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* style

---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* add

* Update docs/source/en/api/pipelines/controlnet_sdxl.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

fix links

Fix Bugs

fix tests

* fix: controlnet graph?

* fix: sample

* fix:

* remove print

* styling

* fix-copies

* prevent more graph breaks?

* prevent more graph breaks?

* see?

* revert.

* compilation.

* rpopagate changes to controlnet sdxl pipeline too.

* add: clean version checking.

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Right now, only "main" branch has this community pipeline code. So, adding it manually into pipeline

* Update get_dummy_inputs(...) in T2I-Adapter tests to take image height and width as params.

* Update the T2I-Adapter unit tests to run with the standard number of UNet down blocks so that all T2I-Adapter down blocks get exercised.

* Update the T2I-Adapter down blocks to better match the padding behavior of the UNet.

* Revert "Update the T2I-Adapter unit tests to run with the standard number of UNet down blocks so that all T2I-Adapter down blocks get exercised."

This reverts commit 6d4a060a34415ec973a252944216f4fb8b9926cd.

* Create  utility functions for testing the T2I-Adapter downscaling bahevior.

* (minor) Improve readability with an intermediate named variable.

* Statically parameterize  T2I-Adapter test dimensions rather than generating them dynamically.

* Fix static checks.

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* fix scale unscale v1

* final fixes + CI

* fix slow trst

* oops

* fix copies

* oops

* oops

* fix

* style

* fix copies

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>