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SD2 inpainting integration tests

* 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

* Upscaling fixed

* up

* more fixes

* fix

* more fixes

* finish again

* up

* Optional Components

* uP

* finish

* finish

* finish

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

* up

* Update src/diffusers/pipeline_utils.py

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

* fix

* add test

* fix test

* uP

* up

* fix some tests

* allow disabling self attention

* add class_embedding

* fix copies

* fix condition

* fix copies

* do_self_attention -> only_cross_attention

* fix copies

* num_classes -> num_class_embeds

* fix default value

* add v prediction

* adat euler for v pred

* velocity -> v_prediction

* simplify

* fix naming

* Update src/diffusers/schedulers/scheduling_euler_discrete.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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

* fix imports

* better error

* up

* finish

don't norm twice

* boom boom

* remove duplicate arg

* add use_linear_proj arg

* fix copies

* style

* add fast tests

* use_linear_proj -> use_linear_projection

* up

* convert dual unet

* revert dual attn

* adapt for vd-official

* test the full pipeline

* mixed inference

* mixed inference for text2img

* add image prompting

* fix clip norm

* split text2img and img2img

* fix format

* refactor text2img

* mega pipeline

* add optimus

* refactor image var

* wip text_unet

* text unet end to end

* update tests

* reshape

* fix image to text

* add some first docs

* dual guided pipeline

* fix token ratio

* propose change

* dual transformer as a native module

* DualTransformer(nn.Module)

* DualTransformer(nn.Module)

* correct unconditional image

* save-load with mega pipeline

* remove image to text

* up

* uP

* fix

* up

* final fix

* remove_unused_weights

* test updates

* save progress

* uP

* fix dual prompts

* some fixes

* finish

* style

* finish renaming

* up

* fix

* fix

* fix

* finish
Co-authored-by: anton-l <anton@huggingface.co>

* add StableDiffusionImageVariationPipeline

* add ini init

* use CLIPVisionModelWithProjection

* fix _encode_image

* add copied from

* fix copies

* add doc

* handle tensor in _encode_image

* add tests

* correct model_id

* remove copied from in enable_sequential_cpu_offload

* fix tests

* make slow tests pass

* update slow tests

* use temp model for now

* fix test_stable_diffusion_img_variation_intermediate_state

* fix test_stable_diffusion_img_variation_intermediate_state

* check for torch.Tensor

* quality

* fix name

* fix slow tests

* install transformers from source

* fix install

* fix install

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

* input_image -> image

* remove deprication warnings

* fix test_stable_diffusion_img_variation_multiple_images

* make flake happy
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* make sure fp16 runs well

* add fp16 test for superes

* Update src/diffusers/models/unet_2d.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* gen on cuda

* always run fast inferecne test on cpu

* run on cpu
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fix non square images with UNet2DModel and DDIM/DDPM pipelines

* fix unet_2d `sample_size` docstring

* update pipeline tests for unet uncond
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* use memory_efficient_attention by default

* Update src/diffusers/models/attention.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* use accelerator to check mixed_precision

* default `mixed_precision` to `None`

* pass mixed_precision to accelerate launch

* Add pipeline_stable_diffusion_safe.py to pipelines

* Fix repository consistency

Ran make fix-copies after adding new pipline

* Add Paper/Equation reference for parameters to doc string

* Ensure code style and quality

* Perform code refactoring

* Fix copies inherited from merge with huggingface/main

* Add docs

* Fix code style

* Fix errors in documentation

* Fix refactoring error

* remove debugging print statement

* added Safe Latent Diffusion tests

* Fix style

* Fix style

* Add pre-defined safety configurations

* Fix line-break

* fix some tests

* finish

* Change safety checker

* Add missing safety_checker.py file

* Remove unused imports
Co-authored-by: PatrickSchrML <patrick_schramowski@hotmail.de>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* up

* add readme

* up

* uP

perf: prefer batched matmuls for attention. added fast-path to Decoder when num_heads=1

* 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>

* Update alt_diffusion.mdx

* Update alt_diffusion.mdx

Handle batches and Tensors in `pipeline_stable_diffusion_inpaint.py:prepare_mask_and_masked_image` (#1003)

* Handle batches and Tensors in `prepare_mask_and_masked_image`

* `blackfy`
upgrade `black`

* handle mask as `np.array`

* add docstring

* revert `black` changes with smaller line length

* missing ValueError in docstring

* raise `TypeError` for image as tensor but not mask

* typo in mask shape selection

* check for batch dim

* fix: wrong indentation

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

Minor change to Imagic Readme

Missing dir causes an error when running the example code.

Update README.md

Minor spelling mistake.

* 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>

* 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>

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>

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

* style