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* add inpainting

* added proper noising of init_latent as reccommened by jackloomen (https://github.com/huggingface/diffusers/pull/241#issuecomment-1226283542)

* move image preprocessing inside pipeline and allow non 512x512 mask

* Accept latents as input for StableDiffusionPipeline.

* Notebook to demonstrate reusable seeds (latents).

* More accurate type annotation
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Review comments: move to device, raise instead of assert.

* Actually commit the test notebook.

I had mistakenly pushed an empty file instead.

* Adapt notebook to Colab.

* Update examples readme.

* Move notebook to personal repo.
Co-authored-by: Suraj Patil <surajp815@gmail.com>

raise error if strength is not in desired range

* boom boom

* reorganise examples

* add image2image in example inference

* add readme

* fix example

* update colab url

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

* fix init_timestep

* update colab url

* update main readme

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

* Support training with an image folder

* style

In https://github.com/huggingface/diffusers/issues/124 I incorrectly suggested that the image set creation process was undocumented.  In reality, I just hadn't located it.  @patrickvonplaten did so for me.

This PR places a hotlink so that people like me can be shoehorned over where they needed to be.

* New unet, gradient accumulation

* Save every n epochs

* Remove find_unused_params, hooray!

* Update examples

* Switch to DDPM completely

* Catch unused params in DDP

* Fix proj_out, add test

ema model stepping done automatically now

* add a metrics logger

* fix LatentDiffusionUncondPipeline

* add VQModel in init

* add image logging to tensorboard

* switch manual templates to the modelcards package

* hide ldm example
Co-authored-by: patil-suraj <surajp815@gmail.com>