GitLab

* [Lora] first upload

* add first lora version

* upload

* more

* first training

* up

* correct

* improve

* finish loaders and inference

* up

* up

* fix more

* up

* finish more

* finish more

* up

* up

* change year

* revert year change

* Change lines

* Add cloneofsimo as co-author.
Co-authored-by: Simo Ryu <cloneofsimo@gmail.com>

* finish

* fix docs

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

* upload

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

* first proposal

* rename

* up

* Apply suggestions from code review

* better

* up

* finish

* up

* rename

* correct versatile

* up

* up

* up

* up

* fix

* Apply suggestions from code review

* make style

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

* add error message
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* finish

* fix

* Update tests/models/test_models_unet_2d.py

* style
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* make attn slice recursive

* remove set_attention_slice from blocks

* fix copies

* make enable_attention_slicing base class method of DiffusionPipeline

* fix set_attention_slice

* fix set_attention_slice

* fix copies

* add tests

* up

* up

* up

* update

* up

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

* Flax: start adapting to Stable Diffusion 2

* More changes.

* attention_head_dim can be a tuple.

* Fix typos

* Add simple SD 2 integration test.

Slice values taken from my Ampere GPU.

* Add simple UNet integration tests for Flax.

Note that the expected values are taken from the PyTorch results. This
ensures the Flax and PyTorch versions are not too far off.

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

* Typos and style

* Tests: verify jax is available.

* Style

* Make flake happy

* Remove typo.

* Simple Flax SD 2 pipeline tests.

* Import order

* Remove unused import.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: @camenduru 

* boom boom

* remove duplicate arg

* add use_linear_proj arg

* fix copies

* style

* add fast tests

* use_linear_proj -> use_linear_projection

* Schedulers: don't use float64 on mps

* Test set_timesteps() on device (float schedulers).

* SD pipeline: use device in set_timesteps.

* SD in-painting pipeline: use device in set_timesteps.

* Tests: fix mps crashes.

* Skip test_load_pipeline_from_git on mps.

Not compatible with float16.

* Use device.type instead of str in Euler schedulers.

* correct naming

* finish

* Apply suggestions from code review

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

* make accelerate hard dep

* default fast init

* move params to cpu when device map is None

* handle device_map=None

* handle torch < 1.9

* remove device_map="auto"

* style

* add accelerate in torch extra

* remove accelerate from extras["test"]

* raise an error if torch is available but not accelerate

* update installation docs

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

* improve defautl loading speed even further, allow disabling fats loading

* address review comments

* adapt the tests

* fix test_stable_diffusion_fast_load

* fix test_read_init

* temp fix for dummy checks

* Trigger Build

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

* improve test precision

get tests passing with greater precision using lewington images

* make old numpy load function a wrapper around a more flexible numpy loading function

* adhere to black formatting

* add more black formatting

* adhere to isort

* loosen precision and replace path
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* improve tests

* up

* finish

* upload

* add init

* up

* finish vae

* finish

* reduce loading time with device_map

* remove device_map from CPU

* uP

* start

* add more logic

* Update src/diffusers/models/unet_2d_condition_flax.py

* match weights

* up

* make model work

* making class more general, fixing missed file rename

* small fix

* make new conversion work

* up

* finalize conversion

* up

* first batch of variable renamings

* remove c and c_prev var names

* add mid and out block structure

* add pipeline

* up

* finish conversion

* finish

* upload

* more fixes

* Apply suggestions from code review

* add attr

* up

* uP

* up

* finish tests

* finish

* uP

* finish

* fix test

* up

* naming consistency in tests

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

* remove hardcoded 16

* Remove bogus

* fix some stuff

* finish

* improve logging

* docs

* upload
Co-authored-by: Nathan Lambert <nol@berkeley.edu>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Nathan Lambert <nathan@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* [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>

* Fix gradient checkpointing test

* more tsets

* use_deterministic_algorithms  for grad ckpt test

* remove eval

* Apply suggestions from code review

* Update tests/test_models_unet.py

* add accelerate to load models with smaller memory footprint

* remove low_cpu_mem_usage as it is reduntant

* move accelerate init weights context to modelling utils

* add test to ensure results are the same when loading with accelerate

* add tests to ensure ram usage gets lower when using accelerate

* move accelerate logic to single snippet under modelling utils and remove it from configuration utils

* format code using to pass quality check

* fix imports with isor

* add accelerate to test extra deps

* only import accelerate if device_map is set to auto

* move accelerate availability check to diffusers import utils

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

* [Utils] Add deprecate function

* up

* up

* uP

* up

* up

* up

* up

* uP

* up

* fix

* up

* move to deprecation utils file

* fix

* fix

* fix more

* lowe tolerance

* put model in eval mode

* 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

* [Tests] Mark the ncsnpp model tests as slow

* style

* 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

* update expected results of slow tests

* relax sum and mean tests

* Print shapes when reporting exception

* formatting

* fix sentence

* relax test_stable_diffusion_fast_ddim for gpu fp16

* relax flakey tests on GPU

* added comment on large tolerences

* black

* format

* set scheduler seed

* added generator

* use np.isclose

* set num_inference_steps to 50

* fix dep. warning

* update expected_slice

* preprocess if image

* updated expected results

* updated expected from CI

* pass generator to VAE

* undo change back to orig

* use orignal

* revert back the expected on cpu

* revert back values for CPU

* more undo

* update result after using gen

* update mean

* set generator for mps

* update expected on CI server

* undo

* use new seed every time

* cpu manual seed

* reduce num_inference_steps

* style

* use generator for randn
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* 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>

* [Tests] Make sure tests are on GPU

* move more models

* speed up tests

* split tests_modeling_utils

* Fix SD tests .to(device)

* fix merge

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