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fix resume step in train_text_to_image example

only have api docstring once for sD

* [Deterministic torch randn] Allow tensors to be generated on CPU

* fix more

* up

* fix more

* up

* Update src/diffusers/utils/torch_utils.py
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* Apply suggestions from code review

* up

* up

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

* Add condtional generation

* add fast test for conditional audio generation

* add add_noise to scheduling-sde-ve

* run Black formater

Add accelerate and xformers to diffusers-cli env

* Add UnCLIPImageVariationPipeline to dummy imports

* style

* add a doc page for each pipeline under api/pipelines/stable_diffusion
* add pipeline examples to docstrings
* updated stable_diffusion_2 page
* updated default markdown syntax to list methods based on https://github.com/huggingface/diffusers/pull/1870


* add function decorator
Co-authored-by: yiyixuxu <yixu@Yis-MacBook-Pro.lan>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Fixes to the help for report_to in training scripts.

* misc fixes

* more comments

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

* set transformers verbosity to warning
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Numpy 1.24 had removed the "float" scalar alias as it was depricated in v1.20.
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
https://numpy.org/devdocs/release/1.24.0-notes.html#expired-deprecations

Fix typo in train_dreambooth_inpaint.

* [Attention] Finish refactor attention file

* correct more

* fix

* more fixes

* correct

* up

* allow using non-ema weights for training

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

* address more review comment

* reorganise a few lines

* always pad text to max_length to match original training

* ifx collate_fn

* remove unused code

* don't prepare ema_unet, don't register lr scheduler

* style

* assert => ValueError

* add allow_tf32

* set log level

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

update loss computation

* [Docs] Improve docs

* up

* Fix ema decay and clarify nomenclature.

* Rename var.

[Unclip] Make sure text_embeddings & image_embeddings can directly be passed to enable interpolation tasks. (#1858)

* [Unclip] Make sure latents can be reused

* allow one to directly pass embeddings

* up

* make unclip for text work

* finish allowing to pass embeddings

* correct more

* make style

* move files a bit

* more refactors

* fix more

* more fixes

* fix more onnx

* make style

* upload

* fix

* up

* fix more

* up again

* up

* small fix

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

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

* Flax: Add components function

* Flax: Fix img2img and align with other pipeline

* Flax: Fix PRNGKey type

* Refactor strength to start_timestep

* Fix preprocess images

* Fix processed_images dimen

* latents.shape -> latents_shape

* Fix typo

* Remove "static" comment

* Remove unnecessary optional types in _generate

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

Co-authored-by: Henrik Forstén <henrik.forsten@gmail.com>

* update TI script

* make flake happy

* fix typo

* [Dtype] Align automatic dtype

* up

* up

* fix

* re-add accelerate

fix versatile

* initial

* type hints

* update scheduler type hint

* add to README

* add example generation to README

* v -> mix_factor

* load scheduler from pretrained

* unCLIP image variation

* remove prior comment re: @pcuenca

* stable diffusion -> unCLIP re: @pcuenca

* add copy froms re: @patil-suraj

* allow selecting precision to make DB class images

addresses #1831

* add prior_generation_precision argument

* correct prior_generation_precision's description
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Make xformers optional even if it is available

* Raise exception if xformers is used but not available

* Rename use_xformers to enable_xformers_memory_efficient_attention

* Add a note about xformers in README

* Reformat code style

* Width was typod as weight

* Run Black

* Device to use (e.g. cpu, cuda:0, cuda:1, etc.)

* "cuda" if torch.cuda.is_available() else "cpu"

* Make safety_checker optional in more pipelines.

* Remove inappropriate comment in inpaint pipeline.

* InPaint Test: set feature_extractor to None.

* Remove import

* img2img test: set feature_extractor to None.

* inpaint sd2 test: set feature_extractor to None.
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Fix inconsistencies between code and comments in the function 'preprocess'

* unwrap_model text encoder before accessing weights

* fix another call

* fix the right call

* Remove hardcoded names from PT scripts

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

* reorder model wrap

* bug fix
Co-authored-by: Prathik Rao <prathikrao@microsoft.com>