GitLab

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Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix unipc karras sigmas exception - fixes huggingface/diffusers#4580

* Add unipc scheduler tests for karras sigmas

* clean scheduler mixin

* up to dpmsolvermultistep

* finish cleaning

* first draft

* fix overview table

* apply feedback

* update reference code

* Add timestep_spacing to DDPM, LMSDiscrete, PNDM.

* Remove spurious line.

* More easy schedulers.

* Add `linspace` to DDIM

* Noise sigma for `trailing`.

* Add timestep_spacing to DEISMultistepScheduler.

Not sure the range is the way it was intended.

* Fix: remove line used to debug.

* Support timestep_spacing in DPMSolverMultistep, DPMSolverSDE, UniPC

* Fix: convert to numpy.

* Use sched. defaults when instantiating from_config

For params not present in the original configuration.

This makes it possible to switch pipeline schedulers even if they use
different timestep_spacing (or any other param).

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

* Missing args in DPMSolverMultistep

* Test: default args not in config

* Style

* Fix scheduler name in test

* Remove duplicated entries

* Add test for solver_type

This test currently fails in main. When switching from DEIS to UniPC,
solver_type is "logrho" (the default value from DEIS), which gets
translated to "bh1" by UniPC. This is different to the default value for
UniPC: "bh2". This is where the translation happens: https://github.com/huggingface/diffusers/blob/36d22d0709dc19776e3016fb3392d0f5578b0ab2/src/diffusers/schedulers/scheduling_unipc_multistep.py#L171



* UniPC: use same default for solver_type

Fixes a bug when switching from UniPC from another scheduler (i.e.,
DEIS) that uses a different solver type. The solver is now the same as
if we had instantiated the scheduler directly.

* do not save use default values

* fix more

* fix all

* fix schedulers

* fix more

* finish for real

* finish for real

* flaky tests

* Update tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py

* Default steps_offset to 0.

* Add missing docstrings

* Apply suggestions from code review

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

* Correct controlnet out of list error

* Apply suggestions from code review

* correct tests

* correct tests

* fix

* test all

* Apply suggestions from code review

* test all

* test all

* Apply suggestions from code review

* Apply suggestions from code review

* fix more tests

* Fix more

* Apply suggestions from code review

* finish

* Apply suggestions from code review

* Update src/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py

* finish

* [Config] Fix config prints and save, load

* Only use potential nn.Modules for dtype and device

* Correct vae image processor

* make sure in_channels is not accessed directly

* make sure in channels is only accessed via config

* Make sure schedulers only access config attributes

* Make sure to access config in SAG

* Fix vae processor and make style

* add tests

* uP

* make style

* Fix more naming issues

* Final fix with vae config

* change more

dynamic threshold sampling bug fix and docs

* [Schedulers] Correct config changing

* uP

* add tests

* Improve dynamic threshold

* Update code

* Add dynamic threshold to ddim and ddpm

* Encapsulate and leverage code copy mechanism

Update style

* Clean up DDPM/DDIM constructor arguments

* add test

* also add to unipc

---------
Co-authored-by: Peter Lin <peterlin9863@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix typos in the doc

* restyle the code

* add UniPC scheduler

* add the return type to the functions

* code quality check

* add tests

* finish docs

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

* [Bump version] 0.13

* Bump model up

* up

* added dit model

* import

* initial pipeline

* initial convert script

* initial pipeline

* make style

* raise valueerror

* single function

* rename classes

* use DDIMScheduler

* timesteps embedder

* samples to cpu

* fix var names

* fix numpy type

* use timesteps class for proj

* fix typo

* fix arg name

* flip_sin_to_cos and better var names

* fix C shape cal

* make style

* remove unused imports

* cleanup

* add back patch_size

* initial dit doc

* typo

* Update docs/source/api/pipelines/dit.mdx
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* added copyright license headers

* added example usage and toc

* fix variable names asserts

* remove comment

* added docs

* fix typo

* upstream changes

* set proper device for drop_ids

* added initial dit pipeline test

* update docs

* fix imports

* make fix-copies

* isort

* fix imports

* get rid of more magic numbers

* fix code when guidance is off

* remove block_kwargs

* cleanup script

* removed to_2tuple

* use FeedForward class instead of another MLP

* style

* work on mergint DiTBlock with BasicTransformerBlock

* added missing final_dropout and args to BasicTransformerBlock

* use norm from block

* fix arg

* remove unused arg

* fix call to class_embedder

* use timesteps

* make style

* attn_output gets multiplied

* removed commented code

* use Transformer2D

* use self.is_input_patches

* fix flags

* fixed conversion to use Transformer2DModel

* fixes for pipeline

* remove dit.py

* fix timesteps device

* use randn_tensor and fix fp16 inf.

* timesteps_emb already the right dtype

* fix dit test class

* fix test and style

* fix norm2 usage in vq-diffusion

* added author names to pipeline and lmagenet labels link

* fix tests

* use norm_type as string

* rename dit to transformer

* fix name

* fix test

* set  norm_type = "layer" by default

* fix tests

* do not skip common tests

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

* revert AdaLayerNorm API

* fix norm_type name

* make sure all components are in eval mode

* revert norm2 API

* compact

* finish deprecation

* add slow tests

* remove @

* refactor some stuff

* upload

* Update src/diffusers/pipelines/dit/pipeline_dit.py

* finish more

* finish docs

* improve docs

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

* feat : add log-rho deis multistep deis

* docs :fix typo

* docs : add docs for impl algo

* docs : remove duplicate ref

* finish deis

* add docs

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

upgrade version

* up

* up

* finish

* finish

* up

* up

* finish

* cast to float for quantile method

* add fp16 test for DPMSolverMultistepScheduler fix

* formatting update

* Add heun

* Finish first version of heun

* remove bogus

* finish

* finish

* improve

* up

* up

* fix more

* change progress bar

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

* finish

* up

* up

* up

* added initial v-pred support to DPM-solver

* fix sign

* added v_prediction to flax

* fixed typo

* fix

* fix deprecated kwargs logic

* add tests

* finish

* Adapt ddpm, ddpmsolver to prediction_type.

* Deprecate predict_epsilon in __init__.

* Bring FlaxDDIMScheduler up to date with DDIMScheduler.

* Set prediction_type as an ivar for consistency.

* Convert pipeline_ddpm

* Adapt tests.

* Adapt unconditional training script.

* Adapt BitDiffusion example.

* Add missing kwargs in dpmsolver_multistep

* Ugly workaround to accept deprecated predict_epsilon when loading
schedulers using from_pretrained.

* make style

* Remove import no longer in use.

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

* Use config.prediction_type everywhere

* Add a couple of Flax prediction type tests.

* make style

* fix register deprecated arg
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* 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>

* 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>