GitLab

* add dpmsolver discrete pytorch scheduler

* fix some typos in dpm-solver pytorch

* add dpm-solver pytorch in stable-diffusion pipeline

* add jax/flax version dpm-solver

* change code style

* change code style

* add docs

* add `add_noise` method for dpmsolver

* add pytorch unit test for dpmsolver

* add dummy object for pytorch dpmsolver

* Update src/diffusers/schedulers/scheduling_dpmsolver_discrete.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update tests/test_config.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update tests/test_config.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* resolve the code comments

* rename the file

* change class name

* fix code style

* add auto docs for dpmsolver multistep

* add more explanations for the stabilizing trick (for steps < 15)

* delete the dummy file

* change the API name of predict_epsilon, algorithm_type and solver_type

* add compatible lists
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Add CycleDiffusion pipeline for Stable Diffusion

* Add the option of passing noise to DDIMScheduler

Add the option of providing the noise itself to DDIMScheduler, instead of the random seed generator.

* Update README.md

* Update README.md

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update scheduling_ddim.py

* Update import format

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update scheduling_ddim.py

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

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

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

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

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

* Update scheduling_ddim.py

* Update scheduling_ddim.py

* Update scheduling_ddim.py

* add two tests

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update README.md

* Rename pipeline name as suggested in the latest reviewer comment

* Update test_pipelines.py

* Update test_pipelines.py

* Update test_pipelines.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Remove the generator

This generator does not control all randomness during sampling, which can be misleading.

* Update optimal hyperparameters

* Update src/diffusers/pipelines/stable_diffusion/README.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/README.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/README.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Apply suggestions from code review

* uP

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_cycle_diffusion.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* up

* up

* Replace assert with ValueError

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

* finish

* finish

* Update src/diffusers/modeling_utils.py

* Update src/diffusers/pipeline_utils.py
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* more fixes

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

* 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>

* Changes for VQ-diffusion VQVAE

Add specify dimension of embeddings to VQModel:
`VQModel` will by default set the dimension of embeddings to the number
of latent channels. The VQ-diffusion VQVAE has a smaller
embedding dimension, 128, than number of latent channels, 256.

Add AttnDownEncoderBlock2D and AttnUpDecoderBlock2D to the up and down
unet block helpers. VQ-diffusion's VQVAE uses those two block types.

* Changes for VQ-diffusion transformer

Modify attention.py so SpatialTransformer can be used for
VQ-diffusion's transformer.

SpatialTransformer:
- Can now operate over discrete inputs (classes of vector embeddings) as well as continuous.
- `in_channels` was made optional in the constructor so two locations where it was passed as a positional arg were moved to kwargs
- modified forward pass to take optional timestep embeddings

ImagePositionalEmbeddings:
- added to provide positional embeddings to discrete inputs for latent pixels

BasicTransformerBlock:
- norm layers were made configurable so that the VQ-diffusion could use AdaLayerNorm with timestep embeddings
- modified forward pass to take optional timestep embeddings

CrossAttention:
- now may optionally take a bias parameter for its query, key, and value linear layers

FeedForward:
- Internal layers are now configurable

ApproximateGELU:
- Activation function in VQ-diffusion's feedforward layer

AdaLayerNorm:
- Norm layer modified to incorporate timestep embeddings

* Add VQ-diffusion scheduler

* Add VQ-diffusion pipeline

* Add VQ-diffusion convert script to diffusers

* Add VQ-diffusion dummy objects

* Add VQ-diffusion markdown docs

* Add VQ-diffusion tests

* some renaming

* some fixes

* more renaming

* correct

* fix typo

* correct weights

* finalize

* fix tests

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

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

* finish

* finish

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

* feat: add repaint

* fix: fix quality check with `make fix-copies`

* fix: remove old unnecessary arg

* chore: change default to DDPM (looks better in experiments)

* ".to(device)" changed to "device="
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* make generator device-specific
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* make generator device-specific and change shape
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* fix: add preprocessing for image and mask
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* fix: update test
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

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

* Add docs and examples

* Fix toctree
Co-authored-by: fja <fja@zurich.ibm.com>
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>
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>

* 2x speedup using memory efficient attention

* remove einops dependency

* Swap K, M in op instantiation

* Simplify code, remove unnecessary maybe_init call and function, remove unused self.scale parameter

* make xformers a soft dependency

* remove one-liner functions

* change one letter variable to appropriate names

* Remove Env variable dependency, remove MemoryEfficientCrossAttention class and use enable_xformers_memory_efficient_attention method

* Add memory efficient attention toggle to img2img and inpaint pipelines

* Clearer management of xformers' availability

* update optimizations markdown to add info about memory efficient attention

* add benchmarks for TITAN RTX

* More detailed explanation of how the mem eff benchmark were ran

* Removing autocast from optimization markdown

* import_utils: import torch only if is available
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>

* k-diffusion-euler

* make style make quality

* make fix-copies

* fix tests for euler a

* Update src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Update src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Update src/diffusers/schedulers/scheduling_euler_discrete.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Update src/diffusers/schedulers/scheduling_euler_discrete.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* remove unused arg and method

* update doc

* quality

* make flake happy

* use logger instead of warn

* raise error instead of deprication

* don't require scipy

* pass generator in step

* fix tests

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

* Update tests/test_scheduler.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* remove unused generator

* pass generator as extra_step_kwargs

* update tests

* pass generator as kwarg

* pass generator as kwarg

* quality

* fix test for lms

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

* Fix pipelines user_agent, ignore CI requests

* fix circular import

* N/A versions

* N/A versions

* 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>

* Reorganize pipeline tests

* fix vq

Check if MPS backend is registered before calling is_available()

[DiffusionPipeline.from_pretrained] add warning when passing unused kwargs

* ONNX supervised inpainting

* sync with the torch pipeline

* fix concat

* update ref values

* back to 8 steps

* type fix

* make fix-copies

Rename and deprecate

* Bump to 0.6.0.dev0

* Deprecate tensor_format and .samples

* style

* upd

* upd

* style

* sample -> images

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

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

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

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

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

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

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

* [Dummy imports] Better error message

* Test: load pipeline with LMS scheduler.

Fails with a cryptic message if scipy is not installed.

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

* pass norm_num_groups param and add tests

* set resnet_groups for FlaxUNetMidBlock2D

* fixed docstrings

* fixed typo

* using is_flax_available util and created require_flax decorator

* [Custom Pipelines]

* uP

* make style

* finish

* finish

* remove ipdb

* upload

* fix

* finish docs

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

* finish

* final uploads

* remove unnecessary test
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: apolinario <joaopaulo.passos@gmail.com>

* fix accelerate for testing

* fix copies

* uP

* Fix import if PyTorch is not installed.

* Style (blank line)

* 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

* docs: `src/diffusers` readability improvements
Signed-off-by: Ryan Russell <git@ryanrussell.org>

* docs: `make style` lint
Signed-off-by: Ryan Russell <git@ryanrussell.org>
Signed-off-by: Ryan Russell <git@ryanrussell.org>

* WIP: flax FlaxDiffusionPipeline & FlaxStableDiffusionPipeline

* todo comment

* Fix imports

* Fix imports

* add dummies

* Fix empty init

* make pipeline work

* up

* Use Flax schedulers (typing, docstring)

* Wrap model imports inside availability checks.

* more updates

* make sure flax is not broken

* make style

* more fixes

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

* Fix BaseOutput initialization from dict

* style

* Simplify post-init, add tests

* remove debug

* Fix is_onnx_available

Fix: If user install onnxruntime-gpu, is_onnx_available() will return False.

* add more onnxruntime candidates

* Run `make style`
Co-authored-by: anton-l <anton@huggingface.co>

* First UNet Flax modeling blocks.

Mimic the structure of the PyTorch files.
The model classes themselves need work, depending on what we do about
configuration and initialization.

* Remove FlaxUNet2DConfig class.

* ignore_for_config non-config args.

* Implement `FlaxModelMixin`

* Use new mixins for Flax UNet.

For some reason the configuration is not correctly applied; the
signature of the `__init__` method does not contain all the parameters
by the time it's inspected in `extract_init_dict`.

* Import `FlaxUNet2DConditionModel` if flax is available.

* Rm unused method `framework`

* Update src/diffusers/modeling_flax_utils.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Indicate types in flax.struct.dataclass as pointed out by @mishig25
Co-authored-by: Mishig Davaadorj <mishig.davaadorj@coloradocollege.edu>

* Fix typo in transformer block.

* make style

* some more changes

* make style

* Add comment

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

* Rm unneeded comment

* Update docstrings

* correct ignore kwargs

* make style

* Update docstring examples

* Make style

* Style: remove empty line.

* Apply style (after upgrading black from pinned version)

* Remove some commented code and unused imports.

* Add init_weights (not yet in use until #513).

* Trickle down deterministic to blocks.

* Rename q, k, v according to the latest PyTorch version.

Note that weights were exported with the old names, so we need to be
careful.

* Flax UNet docstrings, default props as in PyTorch.

* Fix minor typos in PyTorch docstrings.

* Use FlaxUNet2DConditionOutput as output from UNet.

* make style
Co-authored-by: Mishig Davaadorj <dmishig@gmail.com>
Co-authored-by: Mishig Davaadorj <mishig.davaadorj@coloradocollege.edu>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* beta never changes removed from state

* fix typos in docs

* removed unused var

* initial ddim flax scheduler

* import

* added dummy objects

* fix style

* fix typo

* docs

* fix typo in comment

* set return type

* added flax ddom

* fix style

* remake

* pass PRNG key as argument and split before use

* fix doc string

* use config

* added flax Karras VE scheduler

* make style

* fix dummy

* fix ndarray type annotation

* replace returns a new state

* added lms_discrete scheduler

* use self.config

* add_noise needs state

* use config

* use config

* docstring

* added flax score sde ve

* fix imports

* fix typos

* Implement `FlaxModelMixin`

* Rm unused method `framework`

* Update src/diffusers/modeling_flax_utils.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* some more changes

* make style

* Add comment

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

* Rm unneeded comment

* Update docstrings

* correct ignore kwargs

* make style

* Update docstring examples

* Make style

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

* Rm incorrect docstring

* Add FlaxModelMixin to __init__.py

* make fix-copies
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>