GitLab

* Add a reference to the name 'Sampler'

- Facilitate people that are familiar with the name samplers to understand that we call that schedulers
- Better SEO if people are googling for samplers to find our library as well

* Update README.md with a reference to 'Sampler'

* [Tests] Adjust TPU test values

* slow tests

* remaining refs

* [Tests] Fix mps+generator fast tests

* mps for Euler

* retry

* warmup issue again?

* fix reproducible initial noise

* Revert "fix reproducible initial noise"

This reverts commit f300d05cb9782ed320064a0c58577a32d4139e6d.

* fix reproducible initial noise

* fix device

* Match the generator device to the pipeline for DDPM and DDIM

* style

* fix

* update values

* fix fast tests

* trigger slow tests

* deprecate

* last value fixes

* mps fixes

* up

* more fixes

* fix

* finalize

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

* upload models

* up

Flax tests: don't hardcode number of devices.

This makes it possible to test on CPU/GPU. However, expected slices are
only checked when there are 8 devices.

copy from other pipeline

up

* Add ldm super resolution pipeline

* style

* fix copies

* style

* fix doc

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

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

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* add doc

* address comments

* address comments

* fix doc

* minor

* add tests

* add tests

* load text encoder from subfolder

* fix test

* fix test

* style

* style

* handle mps latents

* unfix typo

* unfix typo

* Update tests/pipelines/latent_diffusion/test_latent_diffusion_superresolution.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fix set_timesteps mps

* fix set_timesteps mps

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* style

* test 64x64 instead of 256x256
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* [Loading] Make edge cases work

* up

* finish

* up

fix script convert LDM

add ddim in clip guided

* fix tests

* Fix more

* more

* Fix cpu offloading

* get offloaded devices locally for SD pipelines

add licenses

* [Scheduler] Move predict epsilon to init

* up

* uP

* uP

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

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

handle dtype xformers

* Restore compatibility with old ONNX pipeline.

I think it broke in #552.

* Add missing attribute `vae_encoder`

* [ONNX] Improve ONNX scheduler compatibility, fix safety_checker

* typo

* Make errors for invalid options without "--with_prior_preservation"

* Make --instance_prompt required

* Removed needless check because --instance_data_dir is marked with required

* Updated messages

* Use logger.warning instead of raise errors
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Schedulers: don't use float64 on mps

* Test set_timesteps() on device (float schedulers).

* SD pipeline: use device in set_timesteps.

* SD in-painting pipeline: use device in set_timesteps.

* Tests: fix mps crashes.

* Skip test_load_pipeline_from_git on mps.

Not compatible with float16.

* Use device.type instead of str in Euler schedulers.

* fix noise device in ddim sched

* fix typo

* self.device -> device

* remove duplicated if

* use str device

* don't use str for device

Unless it's intentional, lol

Link to Dreambooth blog post instead of W&B report.

load text encoder from subfolder

* Add multilingual_stable_diffusion.py file

* Add multilingual stable diffusion to examples README file

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

* adds image to image inpainting with `PIL.Image.Image` inputs
the base implementation claims to support `torch.Tensor` but seems it
would also fail in this case.

* `make style` and `make quality`

* updates community examples readme
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* [Stable Diffusion Inpaint Legacy] Fiix some things

* uP

* add loading script

* Apply suggestions from code review

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* correct

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

* uP
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Change title to match the sidebar in _toctree.

* Fix custom pipe link, add link to contribute.

* Fix community pipeline links.

fix typo

Remove warning about half precision on MPS.

* add dpmsolver discrete pytorch scheduler

* fix some typos in dpm-solver pytorch

* add dpm-solver pytorch in stable-diffusion pipeline

* add jax/flax version dpm-solver

* change code style

* change code style

* add docs

* add `add_noise` method for dpmsolver

* add pytorch unit test for dpmsolver

* add dummy object for pytorch dpmsolver

* Update src/diffusers/schedulers/scheduling_dpmsolver_discrete.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update tests/test_config.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update tests/test_config.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* resolve the code comments

* rename the file

* change class name

* fix code style

* add auto docs for dpmsolver multistep

* add more explanations for the stabilizing trick (for steps < 15)

* delete the dummy file

* change the API name of predict_epsilon, algorithm_type and solver_type

* add compatible lists
Co-authored-by: Suraj Patil <surajp815@gmail.com>