GitLab

* Fix PyCharm/VSCode static type checking for dummy objects

* Re-add dummies

* Fix AudioDiffusion imports

* fix import

* fix import

* Update utils/check_dummies.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update src/diffusers/utils/import_utils.py

* Update src/diffusers/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/__init__.py

* fix double import
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

add upcast_attention arg

* uP

* uP

* Make cross-attention check more robust.

* Fix copies.

* Do not recompile when guidance_scale changes.

* Remove debug for simplicity.

* make style

* Make guidance_scale an array.

* Make DEBUG a constant to avoid passing it down.

* Add comments for clarification.

upcast attention

Update pipeline_paint_by_example.py

* add paint by example

* mkae loading possibel

* up

* Update src/diffusers/models/attention.py

* up

* finalize weight structure

* make example work

* make it work

* up

* up

* fix

* del

* add

* update

* Apply suggestions from code review

* correct transformer 2d

* finish

* up

* up

* up

* up

* fix

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

* Apply suggestions from code review

* up

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

* [WIP] Standardize fast pipeline tests with PipelineTestMixin

* refactor the sd tests a bit

* add more common tests

* add xformers

* add progressbar test

* cleanup

* upd fp16

* CycleDiffusionPipelineFastTests

* DanceDiffusionPipelineFastTests

* AltDiffusionPipelineFastTests

* StableDiffusion2PipelineFastTests

* StableDiffusion2InpaintPipelineFastTests

* StableDiffusionImageVariationPipelineFastTests

* StableDiffusionImg2ImgPipelineFastTests

* StableDiffusionInpaintPipelineFastTests

* remove unused mixins

* quality

* add missing inits

* try to fix mps tests

* fix mps tests

* add mps warmups

* skip for some pipelines

* style

* Update tests/test_pipelines_common.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix typo in pipeline_stable_diffusion.py

Fixes a typo in a warning message

* Fix copies.

* Fix copies
Co-authored-by: Scott <scott@scottinallca.ps>

* add AudioDiffusionPipeline and LatentAudioDiffusionPipeline

* add docs to toc

* fix tests

* fix tests

* fix tests

* fix tests

* fix tests

* Update pr_tests.yml

Fix tests

* parent 499ff34b3edc3e0c506313ab48f21514d8f58b09
author teticio <teticio@gmail.com> 1668765652 +0000
committer teticio <teticio@gmail.com> 1669041721 +0000

parent 499ff34b3edc3e0c506313ab48f21514d8f58b09
author teticio <teticio@gmail.com> 1668765652 +0000
committer teticio <teticio@gmail.com> 1669041704 +0000

add colab notebook

[Flax] Fix loading scheduler from subfolder (#1319)

[FLAX] Fix loading scheduler from subfolder

Fix/Enable all schedulers for in-painting (#1331)

* inpaint fix k lms

* onnox as well

* up

Correct path to schedlure (#1322)

* [Examples] Correct path

* uP

Avoid nested fix-copies (#1332)

* Avoid nested `# Copied from` statements during `make fix-copies`

* style

Fix img2img speed with LMS-Discrete Scheduler (#896)

Casting `self.sigmas` into a different dtype (the one of original_samples) is not advisable. In my img2img pipeline this leads to a long running time in the  `integrate.quad` call later on- by long I mean more than 10x slower.
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

Fix the order of casts for onnx inpainting (#1338)

Legacy Inpainting Pipeline for Onnx Models (#1237)

* Add legacy inpainting pipeline compatibility for onnx

* remove commented out line

* Add onnx legacy inpainting test

* Fix slow decorators

* pep8 styling

* isort styling

* dummy object

* ordering consistency

* style

* docstring styles

* Refactor common prompt encoding pattern

* Update tests to permanent repository home

* support all available schedulers until ONNX IO binding is available
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* updated styling from PR suggested feedback
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

Jax infer support negative prompt (#1337)

* support negative prompts in sd jax pipeline

* pass batched neg_prompt

* only encode when negative prompt is None
Co-authored-by: Juan Acevedo <jfacevedo@google.com>

Update README.md: Minor change to Imagic code snippet, missing dir error (#1347)

Minor change to Imagic Readme

Missing dir causes an error when running the example code.

make style

change the sample model (#1352)

* Update alt_diffusion.mdx

* Update alt_diffusion.mdx

Add bit diffusion [WIP] (#971)

* Create bit_diffusion.py

Bit diffusion based on the paper, arXiv:2208.04202, Chen2022AnalogBG

* adding bit diffusion to new branch

ran tests

* tests

* tests

* tests

* tests

* removed test folders + added to README

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

* move Mel to module in pipeline construction, make librosa optional

* fix imports

* fix copy & paste error in comment

* fix style

* add missing register_to_config

* fix class docstrings

* fix class docstrings

* tweak docstrings

* tweak docstrings

* update slow test

* put trailing commas back

* respect alphabetical order

* remove LatentAudioDiffusion, make vqvae optional

* move Mel from models back to pipelines :-)

* allow loading of pretrained audiodiffusion models

* fix tests

* fix dummies

* remove reference to latent_audio_diffusion in docs

* unused import

* inherit from SchedulerMixin to make loadable

* Apply suggestions from code review

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Research folder

* Update examples/research_projects/README.md

* up

* make attn slice recursive

* remove set_attention_slice from blocks

* fix copies

* make enable_attention_slicing base class method of DiffusionPipeline

* fix set_attention_slice

* fix set_attention_slice

* fix copies

* add tests

* up

* up

* up

* update

* up

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

up

* Fixed mask+masked_image in sd inpaint pipeline

Those were left unset when inputs are not PIL images

* Fixed formatting

* up

* up

* finish

* finish

* up

* up

* finish

* Do not use torch.long in mps

Addresses #1056.

* Use torch.int instead of float.

* Propagate changes.

* Do not silently change float -> int.

* Propagate changes.

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* Moving the mem efficiient attention activation to the top + recursive

* black, too bad there's no pre-commit ?
Co-authored-by: Benjamin Lefaudeux <benjamin@photoroom.com>

* feat: switch core pipelines to use image arg

* test: update tests for core pipelines

* feat: switch examples to use image arg

* docs: update docs to use image arg

* style: format code using black and doc-builder

* fix: deprecate use of init_image in all pipelines

* StableDiffusion: Decode latents separately to run larger batches

* Move VAE sliced decode under enable_vae_sliced_decode and vae.enable_sliced_decode

* Rename sliced_decode to slicing

* fix whitespace

* fix quality check and repository consistency

* VAE slicing tests and documentation

* API doc hooks for VAE slicing

* reformat vae slicing tests

* Skip VAE slicing for one-image batches

* Documentation tweaks for VAE slicing
Co-authored-by: Ilmari Heikkinen <ilmari@fhtr.org>

* Add heun

* Finish first version of heun

* remove bogus

* finish

* finish

* improve

* up

* up

* fix more

* change progress bar

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

* finish

* up

* up

* up

* Ensure Flax pipeline always returns numpy array.

* Clarify documentation.

Remove kwargs from call

* StableDiffusionUpscalePipeline

* fix a few things

* make it better

* fix image batching

* run vae in fp32

* fix docstr

* resize to mul of 64

* doc

* remove safety_checker

* add max_noise_level

* fix Copied

* begin tests

* slow tests

* default max_noise_level

* remove kwargs

* doc

* fix

* fix fast tests

* fix fast tests

* no sf

* don't offload vae
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix

* fix deprecated kwargs logic

* add tests

* finish

* Adapt ddpm, ddpmsolver to prediction_type.

* Deprecate predict_epsilon in __init__.

* Bring FlaxDDIMScheduler up to date with DDIMScheduler.

* Set prediction_type as an ivar for consistency.

* Convert pipeline_ddpm

* Adapt tests.

* Adapt unconditional training script.

* Adapt BitDiffusion example.

* Add missing kwargs in dpmsolver_multistep

* Ugly workaround to accept deprecated predict_epsilon when loading
schedulers using from_pretrained.

* make style

* Remove import no longer in use.

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Use config.prediction_type everywhere

* Add a couple of Flax prediction type tests.

* make style

* fix register deprecated arg
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

fix all tests

* up

* uP

* Support SD2 attention slicing

* Support SD2 attention slicing

* Add more copies

* Use attn_num_head_channels in blocks

* fix-copies

* Update tests

* fix imports

* up

* up

* fix

* uP

* more fixes

* up

* uP

* up

* up

* uP

* fix final tests