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* [CI] Add slow MPS tests

* fix yml

* temporarily resolve caching

* Tests: fix mps crashes.

* Skip test_load_pipeline_from_git on mps.

Not compatible with float16.

* Increase tolerance, use CPU generator, alt. slices.

* Move to nightly

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

* Add xformers attention to VAE

* Simplify VAE xformers code

* Update src/diffusers/models/attention.py
Co-authored-by: Ilmari Heikkinen <ilmari@fhtr.org>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Add parameter safe_serialization to DiffusionPipeline.save_pretrained

* Add option safe_serialization on ModelMixin.save_pretrained

* Add test test_save_safe_serialization

* Black

* Re-trigger the CI

* Fix doc-builder

* Validate files are saved as safetensor in test_save_safe_serialization

- Add the missing `scale_model_input` method to `FlaxLMSDiscreteScheduler`
- Use `jnp.append` for appending to `state.derivatives`
- Use `jnp.delete` to pop from `state.derivatives`

* Create train_dreambooth_inpaint.py

train_dreambooth.py adapted to work with the inpaint model, generating random masks during the training

* Update train_dreambooth_inpaint.py

refactored train_dreambooth_inpaint with black

* Update train_dreambooth_inpaint.py

* Update train_dreambooth_inpaint.py

* Update train_dreambooth_inpaint.py

Fix prior preservation

* add instructions to readme, fix SD2 compatibility

* 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

Fixed doc to install from training packages

fix typo, remove incorrect arguments from .train()

* 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>

* Conversion SD 2

* finish

Allow returning local path

* Add an explicit `--image_size` to the conversion script

* style

* Fix Flax flip_sin_to_cos

* Adding flip_sin_to_cos
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>

* support v prediction in other schedulers

* v heun

* add tests for v pred

* fix tests

* fix test euler a

* v ddpm

* 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

* Correct stacklevel

* fix

* Replace deprecated hub utils in `train_unconditional_ort`

* typo

* Add doc for Stable Diffusion on Habana Gaudi

* Make style

* Add benchmark

* Center-align columns in the benchmark table

Remove reminder comment.

* Add better docs xformers

* update

* Apply suggestions from code review

* fix

* [Dreambooth] Make compatible with alt diffusion

* make style

* add example

* Add test

* up

* no bfloat16 for mps

* fix

* rename test

* Add `ort_nightly_directml` to the `onnxruntime` candidates

* style

* cast to float for quantile method

* add fp16 test for DPMSolverMultistepScheduler fix

* formatting update

* 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>

* updates img2img_inpainting README

* Adds example image to community pipeline README

* Flax: start adapting to Stable Diffusion 2

* More changes.

* attention_head_dim can be a tuple.

* Fix typos

* Add simple SD 2 integration test.

Slice values taken from my Ampere GPU.

* Add simple UNet integration tests for Flax.

Note that the expected values are taken from the PyTorch results. This
ensures the Flax and PyTorch versions are not too far off.

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

* Typos and style

* Tests: verify jax is available.

* Style

* Make flake happy

* Remove typo.

* Simple Flax SD 2 pipeline tests.

* Import order

* Remove unused import.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: @camenduru