GitLab

* relax tolerance slightly

* Add more tests

* upload readme

* upload readme

* Apply suggestions from code review

* Improve API Autoencoder KL

* finalize

* finalize tests

* finalize tests

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* up

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

* Run ControlNet compile test in a separate subprocess

`torch.compile()` spawns several subprocesses and the GPU memory used
was not reclaimed after the test ran. This approach was taken from
`transformers`.

* Style

* Prepare a couple more compile tests to run in subprocess.

* Use require_torch_2 decorator.

* Test inpaint_compile in subprocess.

* Run img2img compile test in subprocess.

* Run stable diffusion compile test in subprocess.

* style

* Temporarily trigger on pr to test.

* Revert "Temporarily trigger on pr to test."

This reverts commit 82d76868ddf9cc634a9f14b2b0aef1d5433cd750.

* 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

* Better deprecation message

* Better deprecation message

* Better doc string

* Fixes

* fix more

* fix more

* Improve __getattr__

* correct more

* fix more

* fix

* Improve more

* more improvements

* fix more

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

* make style

* Fix all rest & add tests & remove old deprecation fns

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

* [Tests] parallelize

* finish folder structuring

* Parallelize tests more

* Correct saving of pipelines

* make sure logging level is correct

* try again

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

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

Improve init

* Workaround for saving dynamo-wrapped models.

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

* Apply workaround when overriding pipeline components.

* Ensure the correct config.json is saved to disk.

Instead of the dynamo class.

* Save correct module (not compiled one)

* Add test

* style

* fix docstrings

* Go back to using string comparisons.

PyTorch CPU does not have _dynamo.

* Simple test for save_pretrained of compiled models.

* Helper function to test whether module is compiled.

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

* Helper function to disable custom attention processors.

* Restore code deleted by mistake.

* Format

* Fix modeling_text_unet copy.

* Remove warmup passes in mps tests.

* Update mps docs: no warmup pass in PyTorch 2

* Update imports.

* [Tests] Correct PT2

* correct more

* move versatile to nightly

* up

* up

* again

* Apply suggestions from code review

* [From pretrained] Speed-up loading from cache

* up

* Fix more

* fix one more bug

* make style

* bigger refactor

* factor out function

* Improve more

* better

* deprecate return cache folder

* clean up

* improve tests

* up

* upload

* add nice tests

* simplify

* finish

* correct

* fix version

* rename

* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>

* rename

* correct doc string

* correct more

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

* apply code suggestions

* finish

---------
Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

[Variant] Add "variant" as input kwarg so to have better UX when downloading no_ema or fp16 weights (#2305)

* [Variant] Add variant loading mechanism

* clean

* improve further

* up

* add tests

* add some first tests

* up

* up

* use path splittetx

* add deprecate

* deprecation warnings

* improve docs

* up

* up

* up

* fix tests

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

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

* correct code format

* fix warning

* finish

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

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

* Update docs/source/en/using-diffusers/loading.mdx
Co-authored-by: Suraj Patil <surajp815@gmail.com>

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

* correct loading docs

* finish

---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Will Berman <wlbberman@gmail.com>

* up

* finish

* improve EMA

* style

* one EMA model

* quality

* fix tests

* fix test

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

* re organise the unconditional script

* backwards compatibility

* default to init values for some args

* fix ort script

* issubclass => isinstance

* update state_dict

* docstr

* doc

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

* use .to if device is passed

* deprecate device

* make flake happy

* fix typo
Co-authored-by: patil-suraj <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* 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>

* [Dtype] Align automatic dtype

* up

* up

* fix

* re-add accelerate

* Add test

* up

* no bfloat16 for mps

* fix

* rename test

* fix

* fix deprecated kwargs logic

* add tests

* finish

* add conversion script for vae

* uP

* uP

* more changes

* push

* up

* finish again

* up

* up

* up

* up

* finish

* up

* 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: Suraj Patil <surajp815@gmail.com>

* up

* up
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* [CI] Add Apple M1 tests

* setup-python

* python build

* conda install

* remove branch

* only 3.8 is built for osx-arm

* try fetching prebuilt tokenizers

* use user cache

* update shells

* Reports and cleanup

* -> MPS

* Disable parallel tests

* Better naming

* investigate worker crash

* return xdist

* restart

* num_workers=2

* still crashing?

* faulthandler for segfaults

* faulthandler for segfaults

* remove restarts, stop on segfault

* torch version

* change installation order

* Use pre-RC version of PyTorch.

To be updated when it is released.

* Skip crashing test on MPS, add new one that works.

* Skip cuda tests in mps device.

* Actually use generator in test.

I think this was a typo.

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

* [Utils] Add deprecate function

* up

* up

* uP

* up

* up

* up

* up

* uP

* up

* fix

* up

* move to deprecation utils file

* fix

* fix

* fix more

* add grad ckpt to downsample blocks

* make it work

* don't pass gradient_checkpointing to upsample block

* add tests for UNet2DConditionModel

* add test_gradient_checkpointing

* add gradient_checkpointing for up and down blocks

* add functions to enable and disable grad ckpt

* remove the forward argument

* better naming

* make supports_gradient_checkpointing private

* Fix typos

* Add a typo check action

* Fix a bug

* Changed to manual typo check currently

Ref: https://github.com/huggingface/diffusers/pull/483#pullrequestreview-1104468010

Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Removed a confusing message

* Renamed "nin_shortcut" to "in_shortcut"

* Add memo about NIN
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* pass norm_num_groups to unet blocs and attention

* fix UNet2DConditionModel

* add norm_num_groups arg in vae

* add tests

* remove comment

* Apply suggestions from code review

* Initial support for mps in Stable Diffusion pipeline.

* Initial "warmup" implementation when using mps.

* Make some deterministic tests pass with mps.

* Disable training tests when using mps.

* SD: generate latents in CPU then move to device.

This is especially important when using the mps device, because
generators are not supported there. See for example
https://github.com/pytorch/pytorch/issues/84288.

In addition, the other pipelines seem to use the same approach: generate
the random samples then move to the appropriate device.

After this change, generating an image in MPS produces the same result
as when using the CPU, if the same seed is used.

* Remove prints.

* Pass AutoencoderKL test_output_pretrained with mps.

Sampling from `posterior` must be done in CPU.

* Style

* Do not use torch.long for log op in mps device.

* Perform incompatible padding ops in CPU.

UNet tests now pass.
See https://github.com/pytorch/pytorch/issues/84535



* Style: fix import order.

* Remove unused symbols.

* Remove MPSWarmupMixin, do not apply automatically.

We do apply warmup in the tests, but not during normal use.
This adopts some PR suggestions by @patrickvonplaten.

* Add comment for mps fallback to CPU step.

* Add README_mps.md for mps installation and use.

* Apply `black` to modified files.

* Restrict README_mps to SD, show measures in table.

* Make PNDM indexing compatible with mps.

Addresses #239.

* Do not use float64 when using LDMScheduler.

Fixes #358.

* Fix typo identified by @patil-suraj
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Adapt example to new output style.

* Restore 1:1 results reproducibility with CompVis.

However, mps latents need to be generated in CPU because generators
don't work in the mps device.

* Move PyTorch nightly to requirements.

* Adapt `test_scheduler_outputs_equivalence` ton MPS.

* mps: skip training tests instead of ignoring silently.

* Make VQModel tests pass on mps.

* mps ddim tests: warmup, increase tolerance.

* ScoreSdeVeScheduler indexing made mps compatible.

* Make ldm pipeline tests pass using warmup.

* Style

* Simplify casting as suggested in PR.

* Add Known Issues to readme.

* `isort` import order.

* Remove _mps_warmup helpers from ModelMixin.

And just make changes to the tests.

* Skip tests using unittest decorator for consistency.

* Remove temporary var.

* Remove spurious blank space.

* Remove unused symbol.

* Remove README_mps.
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> 

* add outputs for models

* add for pipelines

* finish schedulers

* better naming

* adapt tests as well

* replace dict access with . access

* make schedulers works

* finish

* correct readme

* make  bcp compatible

* up

* small fix

* finish

* more fixes

* more fixes

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

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

* Adapt model outputs

* Apply more suggestions

* finish examples

* correct
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* split tests_modeling_utils

* Fix SD tests .to(device)

* fix merge

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