GitLab

* Support multiimage masking

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* disable test

* update

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Co-authored-by: yiyixuxu <yixu310@gmail,com>

* Restore unet params back to normal from EMA when validation call is finished

* empty commit

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

Allow safety and feature extractor arguments to be passed to convert_from_ckpt

Allows management of safety checker and feature extractor
from outside of the convert ckpt class.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add audioldm2 tts

* change gpt2 max new tokens

* remove unnecessary pipeline and class

* add TTS to AudioLDM2Pipeline

* add TTS docs

* delete unnecessary file

* remove unnecessary import

* add audioldm2 slow testcase

* fix code quality

* remove AudioLDMLearnablePositionalEmbedding

* add variable check vits encoder

* add use_learned_position_embedding

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Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

add set_begin_index for all if pipelines

* reduce block sizes for unet1d.

* reduce blocks for unet_2d.

* reduce block size for unet_motion

* increase channels.

* correctly increase channels.

* reduce number of layers in unet2dconditionmodel tests.

* reduce block sizes for unet2dconditionmodel tests

* reduce block sizes for unet3dconditionmodel.

* fix: test_feed_forward_chunking

* fix: test_forward_with_norm_groups

* skip spatiotemporal tests on MPS.

* reduce block size in AutoencoderKL.

* reduce block sizes for vqmodel.

* further reduce block size.

* make style.

* Empty-Commit

* reduce sizes for ConsistencyDecoderVAETests

* further reduction.

* further block reductions in AutoencoderKL and AssymetricAutoencoderKL.

* massively reduce the block size in unet2dcontionmodel.

* reduce sizes for unet3d

* fix tests in unet3d.

* reduce blocks further in motion unet.

* fix: output shape

* add attention_head_dim to the test configuration.

* remove unexpected keyword arg

* up a bit.

* groups.

* up again

* fix

* Skip `test_freeu_enabled ` on MPS

* Small fixes

- import skip_mps correctly
- disable all instances of test_freeu_enabled

* Empty commit to trigger tests

* Empty commit to trigger CI

* Update pipeline_animatediff_video2video.py

* commit with test for whether latent input can be passed into animatediffvid2vid

* increase number of workers for the tests.

* move to beefier runner.

* improve the fast push tests too.

* use a beefy machine for pytorch pipeline tests

* up the number of workers further.

* refactor transformers 2d into multiple legacy variants.

* fix: init.

* fix recursive init.

* add inits.

* make transformer block creation more modular.

* complete refactor.

* remove forward

* debug

* remove legacy blocks and refactor within the module itself.

* remove print

* guard caption projection

* remove fetcher.

* reduce the number of args.

* fix: norm_type

* group variables that are shared.

* remove _get_transformer_blocks

* harmonize the init function signatures.

* transformer_blocks to common

* repeat .

* UniPC Multistep add `rescale_betas_zero_snr`

Same patch as DPM and Euler with the patched final alpha cumprod

BF16 doesn't seem to break down, I think cause UniPC upcasts during some
phases already? We could still force an upcast since it only
loses ≈ 0.005 it/s for me but the difference in output is very small. A
better endeavor might upcasting in step() and removing all the other
upcasts elsewhere?

* UniPC ZSNR UT

* Re-add `rescale_betas_zsnr` doc oops

* UniPC UTs iterate solvers on FP16

It wasn't catching errs on order==3. Might be excessive?

* UniPC Multistep fix tensor dtype/device on order=3

* UniPC UTs Add v_pred to fp16 test iter

For completions sake. Probably overkill?

* add: utility to format our docs too 📜

* debugging saga

* fix: message

* checking

* should be fixed.

* revert pipeline_fixture

* remove empty line

* make style

* fix: setup.py

* style.

* 7529 do not disable autocast for cuda devices

* Remove typecasting error check for non-mps platforms, as a correct autocast implementation makes it a non-issue

* add autocast fix to other training examples

* disable native_amp for dreambooth (sdxl)

* disable native_amp for pix2pix (sdxl)

* remove tests from remaining files

* disable native_amp on huggingface accelerator for every training example that uses it

* convert more usages of autocast to nullcontext, make style fixes

* make style fixes

* style.

* Empty-Commit

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

* start printing the tensors.

* print full throttle

* set static slices for 7 tests.

* remove printing.

* flatten

* disable test for controlnet

* what happens when things are seeded properly?

* set the right value

* style./

* make pia test fail to check things

* print.

* fix pia.

* checking for animatediff.

* fix: animatediff.

* video synthesis

* final piece.

* style.

* print guess.

* fix: assertion for control guess.

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Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* remove class assignments for linear and conv.

* fix: self.nn

* make nightly workflow dispatchable.

* add a note about running the release tests to setup.py

update

* initial-commit pipeline created

* updated README.md

* add from_pipe



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Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* add HD-Painter pipeline

* style fixing

* refactor, change doc, fix ruff

* fix docs

* used correct ruff version

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Co-authored-by: Hayk Manukyan <youremail@yourdomain.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

fix

* Fix SVD bug (shape of `time_context`)

* Formatting code

* Formatting src/diffusers/models/transformers/transformer_temporal.py by `make style && make quality`

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Co-authored-by: kevinkhwu <kevinkhwu@tencent.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

update

* add resample option; check denoise_step; update ckpt path

* Add seeding in pipeline to increase reproducibility

* fix typo

* fix typo

* fix ip adapter support

* Update sag pipelines tests, adjust sag pipeline to pass tests

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Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Add `final_sigma_zero` to UniPCMultistep

Effectively the same trick as DDIM's `set_alpha_to_one` and
DPM's `final_sigma_type='zero'`.
Currently False by default but maybe this should be True?

* `final_sigma_zero: bool` -> `final_sigmas_type: str`

Should 1:1 match DPM Multistep now.

* Set `final_sigmas_type='sigma_min'` in UniPC UTs

* pag_initial

* pag_docs

* edit_docs

* custom

* typo

* delete_docs

* whitespace

* make style

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

* initial commit - instantid img2img

* adapting to img2img

* change add_time_ids

* change add_time_ids

* WIP changes

* add strength to timesteps

* check insightface import

* style

* check insightface import changed to warning

* check insightface import changed to warning

* style

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Co-authored-by: apolinário <joaopaulo.passos@gmail.com>

Fixed important typo

* Initial commit

* Implemented block lora

- implemented block lora
- updated docs
- added tests

* Finishing up

* Reverted unrelated changes made by make style

* Fixed typo

* Fixed bug + Made text_encoder_2 scalable

* Integrated some review feedback

* Incorporated review feedback

* Fix tests

* Made every module configurable

* Adapter to new lora test structure

* Final cleanup

* Some more final fixes

- Included examples in `using_peft_for_inference.md`
- Added hint that only attns are scaled
- Removed NoneTypes
- Added test to check mismatching lens of adapter names / weights raise error

* Update using_peft_for_inference.md

* Update using_peft_for_inference.md

* Make style, quality, fix-copies

* Updated tutorial;Warning if scale/adapter mismatch

* floats are forwarded as-is; changed tutorial scale

* make style, quality, fix-copies

* Fixed typo in tutorial

* Moved some warnings into `lora_loader_utils.py`

* Moved scale/lora mismatch warnings back

* Integrated final review suggestions

* Empty commit to trigger CI

* Reverted emoty commit to trigger CI

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

* update

* update

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

* speed up test_vae_slicing in animatediff

* speed up test_karras_schedulers_shape for attend and excite.

* style.

* get the static slices out.

* specify torch print options.

* modify

* test run with controlnet

* specify kwarg

* fix: things

* not None

* flatten

* controlnet img2img

* complete controlet sd

* finish more

* finish more

* finish more

* finish more

* finish the final batch

* add cpu check for expected_pipe_slice.

* finish the rest

* remove print

* style

* fix ssd1b controlnet test

* checking ssd1b

* disable the test.

* make the test_ip_adapter_single controlnet test more robust

* fix: simple inpaint

* multi

* disable panorama

* enable again

* panorama is shaky so leave it for now

* remove print

* raise tolerance.

use float16 and add torch.no_grad()

* Bug fix for controlnetpipeline check_image

Bug fix for controlnetpipeline check_image when using multicontrolnet and prompt list

* Update test_inference_multiple_prompt_input function

* Update test_controlnet.py

add test for multiple prompts and multiple image conditioning

* Update test_controlnet.py

Fix format error

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Co-authored-by: Lvkesheng Shen <45848260+Fantast416@users.noreply.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add remove_all_hooks

* a few more fix and tests

* up

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

* split tests

* add

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

* apple mps: training support for SDXL LoRA

* sdxl: support training lora, dreambooth, t2i, pix2pix, and controlnet on apple mps

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