GitLab

* 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

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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

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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>

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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.

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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

Update pr_tests.yml

* Add `sigmoid` beta scheduler to `DDPMScheduler` docstring

* Add `sigmoid` beta scheduler to `RePaintScheduler` docstring

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

* up

* up

* Improve checkpointing lora

* fix more

* Improve doc string

* Update src/diffusers/loaders.py

* make stytle

* Apply suggestions from code review

* Update src/diffusers/loaders.py

* Apply suggestions from code review

* Apply suggestions from code review

* better

* Fix all

* Fix multi-GPU dreambooth

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

* Fix all

* make style

* make style

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

Add omegaconfg

* [deepspeed] partial ZeRO-3 support

* cleanup

* improve deepspeed fixes

* Improve

* make style

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

add transformers to install

* enable deterministic pytorch and cuda operations.

* disable manual seeding.

* make style && make quality for unet_2d tests.

* enable determinism for the unet2dconditional model.

* add CUBLAS_WORKSPACE_CONFIG for better reproducibility.

* relax tolerance (very weird issue, though).

* revert to torch manual_seed() where needed.

* relax more tolerance.

* better placement of the cuda variable and relax more tolerance.

* enable determinism for 3d condition model.

* relax tolerance.

* add: determinism to alt_diffusion.

* relax tolerance for alt diffusion.

* dance diffusion.

* dance diffusion is flaky.

* test_dict_tuple_outputs_equivalent edit.

* fix two more tests.

* fix more ddim tests.

* fix: argument.

* change to diff in place of difference.

* fix: test_save_load call.

* test_save_load_float16 call.

* fix: expected_max_diff

* fix: paint by example.

* relax tolerance.

* add determinism to 1d unet model.

* torch 2.0 regressions seem to be brutal

* determinism to vae.

* add reason to skipping.

* up tolerance.

* determinism to vq.

* determinism to cuda.

* determinism to the generic test pipeline file.

* refactor general pipelines testing a bit.

* determinism to alt diffusion i2i

* up tolerance for alt diff i2i and audio diff

* up tolerance.

* determinism to audioldm

* increase tolerance for audioldm lms.

* increase tolerance for paint by paint.

* increase tolerance for repaint.

* determinism to cycle diffusion and sd 1.

* relax tol for cycle diffusion 🚲

* relax tol for sd 1.0

* relax tol for controlnet.

* determinism to img var.

* relax tol for img variation.

* tolerance to i2i sd

* make style

* determinism to inpaint.

* relax tolerance for inpaiting.

* determinism for inpainting legacy

* relax tolerance.

* determinism to instruct pix2pix

* determinism to model editing.

* model editing tolerance.

* panorama determinism

* determinism to pix2pix zero.

* determinism to sag.

* sd 2. determinism

* sd. tolerance

* disallow tf32 matmul.

* relax tolerance is all you need.

* make style and determinism to sd 2 depth

* relax tolerance for depth.

* tolerance to diffedit.

* tolerance to sd 2 inpaint.

* up tolerance.

* determinism in upscaling.

* tolerance in upscaler.

* more tolerance relaxation.

* determinism to v pred.

* up tol for v_pred

* unclip determinism

* determinism to unclip img2img

* determinism to text to video.

* determinism to last set of tests

* up tol.

* vq cumsum doesn't have a deterministic kernel

* relax tol

* relax tol

* add inferring_controlnet_cond_batch

* Revert "add inferring_controlnet_cond_batch"

This reverts commit abe8d6311d4b7f5b9409ca709c7fabf80d06c1a9.

* set guess_mode to True
whenever global_pool_conditions is True
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* nit

* add integration test

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

Fix typo in last code block. Correct "prommpts" to "prompt"

* safetensors

* apply feedback

* apply feedback

* Apply suggestions from code review

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

* first draft

* apply feedback

* conv_in.weight thrown away

* StableDiffusionInpaintingPipeline now resizes input images and masks w.r.t to passed input height and width. Default is already set to 512. This addresses the common tensor mismatch error. Also moved type check into relevant funciton to keep main pipeline body tidy.

* Fixed StableDiffusionInpaintingPrepareMaskAndMaskedImageTests

Due to previous commit these tests were failing as height and width need to be passed into the prepare_mask_and_masked_image function, I have updated the code and added a height/width variable per unit test as it seemed more appropriate than the current hard coded solution

* Added a resolution test to StableDiffusionInpaintPipelineSlowTests

this unit test simply gets the input and resizes it into some that would fail (e.g. would throw a tensor mismatch error/not a mult of 8). Then passes it through the pipeline and verifies it produces output with correct dims w.r.t the passed height and width

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