GitLab

* DataLoader will now bake in any transforms or image manipulations contained in the EXIF

Images may have rotations stored in EXIF. Training using such images will cause those transforms to be ignored while training and thus produce unexpected results

* Fixed the Dataloading EXIF issue in main DreamBooth training as well

* Run make style (black & isort)

* feat) optimization kr translation

* fix) typo, italic setting

* feat) dreambooth, text2image kr

* feat) lora kr

* fix) LoRA

* fix) fp16 fix

* fix) doc-builder style

* fix) fp16 일부 단어 수정

* fix) fp16 style fix

* fix) opt, training docs update

* feat) toctree update

* feat) toctree update

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Co-authored-by: Chanran Kim <seriousran@gmail.com>

* add use_karras_sigmas

* add karras test

* add doc

* Fix DPM single

* add test

* fix one more bug

* Apply suggestions from code review
Co-authored-by: StAlKeR7779 <stalkek7779@yandex.ru>

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Co-authored-by: StAlKeR7779 <stalkek7779@yandex.ru>

* up

* fix more

* Apply suggestions from code review

* fix more

* fix more

* Check it

* Remove 16:8

* fix more

* fix more

* fix more

* up

* up

* Test only stable diffusion

* Test only two files

* up

* Try out spinning up processes that can be killed

* up

* Apply suggestions from code review

* up

* up

add note on local directory path.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add: debugging to enabling memory efficient processing

* add: better warning message.

* Remove ONNX tests from PR.

They are already a part of push_tests.yml.

* Remove mps tests from PRs.

They are already performed on push.

* Fix workflow name for fast push tests.

* Extract mps tests to a workflow.

For better control/filtering.

* Remove --extra-index-url from mps tests

* Increase tolerance of mps test

This test passes in my Mac (Ventura 13.3) but fails in the CI hardware
(Ventura 13.2). I ran the local tests following the same steps that
exist in the CI workflow.

* Temporarily run mps tests on pr

So we can test.

* Revert "Temporarily run mps tests on pr"

Tests passed, go back to running on push.

explicit view kernel size as number elements in flattened indices

* distributed inference

* move to inference section

* apply feedback

* update with split_between_processes

* apply feedback

* add textual inversion inference to docs

* add to toctree

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* dreambooth docs torch.compile note

* Update examples/dreambooth/README.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/README.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Correct from_ckpt

* make style

* add inpaint lora scale support

* add inpaint lora scale test

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Co-authored-by: yueyang.hyy <yueyang.hyy@alibaba-inc.com>

add min snr to text2img lora training script

Release large tensors in attention (as soon as they're no longer required). Reduces peak VRAM by nearly 2 GB for 1024x1024 (even after slicing), and the savings scale up with image size.

* Make dreambooth lora more robust to orig unet

* up

* gradient checkpointing bug fix

* bug fix; changes for reviews

* reformat

* reformat

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

Added bugfix using f strings.

* Added explanation of 'strength' parameter

* Added get_timesteps function which relies on new strength parameter

* Added `strength` parameter which defaults to 1.

* Swapped ordering so `noise_timestep` can be calculated before masking the image

this is required when you aren't applying 100% noise to the masked region, e.g. strength < 1.

* Added strength to check_inputs, throws error if out of range

* Changed `prepare_latents` to initialise latents w.r.t strength

inspired from the stable diffusion img2img pipeline, init latents are initialised by converting the init image into a VAE latent and adding noise (based upon the strength parameter passed in), e.g. random when strength = 1, or the init image at strength = 0.

* WIP: Added a unit test for the new strength parameter in the StableDiffusionInpaintingPipeline

still need to add correct regression values

* Created a is_strength_max to initialise from pure random noise

* Updated unit tests w.r.t new strength parameter + fixed new strength unit test

* renamed parameter to avoid confusion with variable of same name

* Updated regression values for new strength test - now passes

* removed 'copied from' comment as this method is now different and divergent from the cpy

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

* Ensure backwards compatibility for prepare_mask_and_masked_image

created a return_image boolean and initialised to false

* Ensure backwards compatibility for prepare_latents

* Fixed copy check typo

* Fixes w.r.t backward compibility changes

* make style

* keep function argument ordering same for backwards compatibility in callees with copied from statements

* make fix-copies

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: William Berman <WLBberman@gmail.com>

* Update pipeline_if_superresolution.py

Allow arbitrary aspect ratio in IFSuperResolutionPipeline by using the input image shape

* IFSuperResolutionPipeline: allow the user to override the height and width through the arguments

* update IFSuperResolutionPipeline width/height doc string to match StableDiffusionInpaintPipeline conventions

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

Small update to "Next steps" section:

- PyTorch 2 is recommended.
- Updated improvement figures.

fix tiled vae bleand extent range

Fix incomplete docstrings for resnet.py

* Add DPM-Solver Multistep Inverse Scheduler

* Add draft tests for DiffEdit

* Add inverse sde-dpmsolver steps to tune image diversity from inverted latents

* Fix tests

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

* refactor controlnet and add img2img and inpaint

* First draft to get pipelines to work

* make style

* Fix more

* Fix more

* More tests

* Fix more

* Make inpainting work

* make style and more tests

* Apply suggestions from code review

* up

* make style

* Fix imports

* Fix more

* Fix more

* Improve examples

* add test

* Make sure import is correctly deprecated

* Make sure everything works in compile mode

* make sure authorship is correctly attributed

* add stable diffusion tensorrt img2img pipeline
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* update docstrings
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

---------
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

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

* Fix style rendering.

* Fix typo

* add: benchmarking stats for A100 and V100.

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

* address patrick's comments.

* add: rtx 4090 stats

* ⚔

 benchmark reports done

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

* 3313 pr link.

* add: plots.
Co-authored-by: Pedro <pedro@huggingface.co>

* fix formattimg

* update number percent.

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Replace `AttentionBlock` with `Attention`

* use _from_deprecated_attn_block check re: @patrickvonplaten