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  1. 30 Sep, 2024 1 commit
  3. 25 Sep, 2024 1 commit
  5. 23 Sep, 2024 1 commit
  7. 30 Jul, 2024 1 commit
    • Yoach Lacombe's avatar
      Stable Audio integration (#8716) · 69e72b1d
      Yoach Lacombe authored 
      

* WIP modeling code and pipeline

* add custom attention processor + custom activation + add to init

* correct ProjectionModel forward

* add stable audio to __initèè

* add autoencoder and update pipeline and modeling code

* add half Rope

* add partial rotary v2

* add temporary modfis to scheduler

* add EDM DPM Solver

* remove TODOs

* clean GLU

* remove att.group_norm to attn processor

* revert back src/diffusers/schedulers/scheduling_dpmsolver_multistep.py

* refactor GLU -> SwiGLU

* remove redundant args

* add channel multiples in autoencoder docstrings

* changes in docsrtings and copyright headers

* clean pipeline

* further cleaning

* remove peft and lora and fromoriginalmodel

* Delete src/diffusers/pipelines/stable_audio/diffusers.code-workspace

* make style

* dummy models

* fix copied from

* add fast oobleck tests

* add brownian tree

* oobleck autoencoder slow tests

* remove TODO

* fast stable audio pipeline tests

* add slow tests

* make style

* add first version of docs

* wrap is_torchsde_available to the scheduler

* fix slow test

* test with input waveform

* add input waveform

* remove some todos

* create stableaudio gaussian projection + make style

* add pipeline to toctree

* fix copied from

* make quality

* refactor timestep_features->time_proj

* refactor joint_attention_kwargs->cross_attention_kwargs

* remove forward_chunk

* move StableAudioDitModel to transformers folder

* correct convert + remove partial rotary embed

* apply suggestions from yiyixuxu -> removing attn.kv_heads

* remove temb

* remove cross_attention_kwargs

* further removal of cross_attention_kwargs

* remove text encoder autocast to fp16

* continue removing autocast

* make style

* refactor how text and audio are embedded

* add paper

* update example code

* make style

* unify projection model forward + fix device placement

* make style

* remove fuse qkv

* apply suggestions from review

* Update src/diffusers/pipelines/stable_audio/pipeline_stable_audio.py
Co-authored-by: default avatarYiYi Xu <yixu310@gmail.com>

* make style

* smaller models in fast tests

* pass sequential offloading fast tests

* add docs for vae and autoencoder

* make style and update example

* remove useless import

* add cosine scheduler

* dummy classes

* cosine scheduler docs

* better description of scheduler

---------
Co-authored-by: default avatarYiYi Xu <yixu310@gmail.com>
      69e72b1d
  9. 08 Jul, 2024 1 commit
  11. 24 Jun, 2024 1 commit
  13. 12 Jun, 2024 1 commit
  15. 05 Jun, 2024 1 commit
    • Tolga Cangöz's avatar
      Errata (#8322) · 98730c5d
      Tolga Cangöz authored 
      * Fix typos

* Trim trailing whitespaces

* Remove a trailing whitespace

* chore: Update MarigoldDepthPipeline checkpoint to prs-eth/marigold-lcm-v1-0

* Revert "chore: Update MarigoldDepthPipeline checkpoint to prs-eth/marigold-lcm-v1-0"

This reverts commit fd742b30b4258106008a6af4d0dd4664904f8595.

* pokemon -> naruto

* `DPMSolverMultistep` -> `DPMSolverMultistepScheduler`

* Improve Markdown stylization

* Improve style

* Improve style

* Refactor pipeline variable names for consistency

* up style
      98730c5d
  17. 14 Mar, 2024 1 commit
  19. 05 Mar, 2024 1 commit
  21. 29 Feb, 2024 1 commit
    • M. Tolga Cangöz's avatar
      [`Docs`] Fix typos (#7131) · f4fc7503
      M. Tolga Cangöz authored 
      * Add copyright notice to relevant files and fix typos

* Set `timestep_spacing` parameter of `StableDiffusionXLPipeline`'s scheduler to `'trailing'`.

* Update `StableDiffusionXLPipeline.from_single_file` by including EulerAncestralDiscreteScheduler with `timestep_spacing="trailing"` param.

* Update model loading method in SDXL Turbo documentation
      f4fc7503
  23. 08 Feb, 2024 1 commit
  25. 27 Nov, 2023 1 commit
  27. 13 Nov, 2023 1 commit
  29. 09 Nov, 2023 1 commit
  31. 24 Oct, 2023 1 commit
    • dg845's avatar
      Add Latent Consistency Models Pipeline (#5448) · 958e17da
      dg845 authored 
      

* initial commit for LatentConsistencyModelPipeline and LCMScheduler based on the community pipeline

* Add callback and freeu support.

* apply suggestions from review

* Clean up LCMScheduler

* Remove timeindex argument to LCMScheduler.step.

* Add support for clipping or thresholding the predicted original sample.

* Remove unused methods and arguments in LCMScheduler.

* Improve comment about (lack of) negative prompt support.

* Change input guidance_scale to match the StableDiffusionPipeline (Imagen) CFG formulation.

* Move lcm_origin_steps from pipeline __call__ to LCMScheduler.__init__/config (as origin_steps).

* Fix typo when clipping/thresholding in LCMScheduler.

* Add some initial LCMScheduler tests.

* add type annotations from review

* Fix type annotation bug.

* Override test_add_noise_device in LCMSchedulerTest since hardcoded timesteps doesn't work under default settings.

* Add generator argument pipeline prepare_latents call.

* Cast LCMScheduler.timesteps to long in set_timesteps.

* Add onestep and multistep full loop scheduler tests.

* Set default height/width to None and don't hardcode guidance scale embedding dim.

* Add initial LatentConsistencyPipeline fast and slow tests.

* Add initial documentation for LatentConsistencyModelPipeline and LCMScheduler.

* Make remaining failing fast tests pass.

* make style

* Make original_inference_steps configurable from pipeline __call__ again.

* make style

* Remove guidance_rescale arg from pipeline __call__ since LCM currently doesn't support CFG.

* Make LCMScheduler defaults match config of LCM_Dreamshaper_v7 checkpoint.

* Fix LatentConsistencyPipeline slow tests and add dummy expected slices.

* Add checks for original_steps in LCMScheduler.set_timesteps.

* make fix-copies

* Improve LatentConsistencyModelPipeline docs.

* Apply suggestions from code review
Co-authored-by: default avatarAryan V S <avs050602@gmail.com>

* Apply suggestions from code review
Co-authored-by: default avatarAryan V S <avs050602@gmail.com>

* Apply suggestions from code review
Co-authored-by: default avatarAryan V S <avs050602@gmail.com>

* Update src/diffusers/schedulers/scheduling_lcm.py

* Apply suggestions from code review
Co-authored-by: default avatarAryan V S <avs050602@gmail.com>

* finish

---------
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: default avatarAryan V S <avs050602@gmail.com>
      958e17da
  33. 15 Aug, 2023 1 commit
  35. 09 Aug, 2023 1 commit
    • Steven Liu's avatar
      [docs] Clean scheduler api (#4204) · 16ad13b6
      Steven Liu authored 
      * clean scheduler mixin

* up to dpmsolvermultistep

* finish cleaning

* first draft

* fix overview table

* apply feedback

* update reference code
      16ad13b6
  37. 26 Jul, 2023 1 commit
  39. 05 Jul, 2023 1 commit
    • dg845's avatar
      Add Consistency Models Pipeline (#3492) · aed7499a
      dg845 authored 
      

* initial commit

* Improve consistency models sampling implementation.

* Add CMStochasticIterativeScheduler, which implements the multi-step sampler (stochastic_iterative_sampler) in the original code, and make further improvements to sampling.

* Add Unet blocks for consistency models

* Add conversion script for Unet

* Fix bug in new unet blocks

* Fix attention weight loading

* Make design improvements to ConsistencyModelPipeline and CMStochasticIterativeScheduler and add initial version of tests.

* make style

* Make small random test UNet class conditional and set resnet_time_scale_shift to 'scale_shift' to better match consistency model checkpoints.

* Add support for converting a test UNet and non-class-conditional UNets to the consistency models conversion script.

* make style

* Change num_class_embeds to 1000 to better match the original consistency models implementation.

* Add support for distillation in pipeline_consistency_models.py.

* Improve consistency model tests:
	- Get small testing checkpoints from hub
	- Modify tests to take into account "distillation" parameter of ConsistencyModelPipeline
	- Add onestep, multistep tests for distillation and distillation + class conditional
	- Add expected image slices for onestep tests

* make style

* Improve ConsistencyModelPipeline:
	- Add initial support for class-conditional generation
	- Fix initial sigma for onestep generation
	- Fix some sigma shape issues

* make style

* Improve ConsistencyModelPipeline:
	- add latents __call__ argument and prepare_latents method
	- add check_inputs method
	- add initial docstrings for ConsistencyModelPipeline.__call__

* make style

* Fix bug when randomly generating class labels for class-conditional generation.

* Switch CMStochasticIterativeScheduler to configuring a sigma schedule and make related changes to the pipeline and tests.

* Remove some unused code and make style.

* Fix small bug in CMStochasticIterativeScheduler.

* Add expected slices for multistep sampling tests and make them pass.

* Work on consistency model fast tests:
	- in pipeline, call self.scheduler.scale_model_input before denoising
	- get expected slices for Euler and Heun scheduler tests
	- make Euler test pass
	- mark Heun test as expected fail because it doesn't support prediction_type "sample" yet
	- remove DPM and Euler Ancestral tests because they don't support use_karras_sigmas

* make style

* Refactor conversion script to make it easier to add more model architectures to convert in the future.

* Work on ConsistencyModelPipeline tests:
	- Fix device bug when handling class labels in ConsistencyModelPipeline.__call__
	- Add slow tests for onestep and multistep sampling and make them pass
	- Refactor fast tests
	- Refactor ConsistencyModelPipeline.__init__

* make style

* Remove the add_noise and add_noise_to_input methods from CMStochasticIterativeScheduler for now.

* Run python utils/check_copies.py --fix_and_overwrite
python utils/check_dummies.py --fix_and_overwrite to make dummy objects for new pipeline and scheduler.

* Make fast tests from PipelineTesterMixin pass.

* make style

* Refactor consistency models pipeline and scheduler:
	- Remove support for Karras schedulers (only support CMStochasticIterativeScheduler)
	- Move sigma manipulation, input scaling, denoising from pipeline to scheduler
	- Make corresponding changes to tests and ensure they pass

* make style

* Add docstrings and further refactor pipeline and scheduler.

* make style

* Add initial version of the consistency models documentation.

* Refactor custom timesteps logic following DDPMScheduler/IFPipeline and temporarily add torch 2.0 SDPA kernel selection logic for debugging.

* make style

* Convert current slow tests to use fp16 and flash attention.

* make style

* Add slow tests for normal attention on cuda device.

* make style

* Fix attention weights loading

* Update consistency model fast tests for new test checkpoints with attention fix.

* make style

* apply suggestions

* Add add_noise method to CMStochasticIterativeScheduler (copied from EulerDiscreteScheduler).

* Conversion script now outputs pipeline instead of UNet and add support for LSUN-256 models and different schedulers.

* When both timesteps and num_inference_steps are supplied, raise warning instead of error (timesteps take precedence).

* make style

* Add remaining diffusers model checkpoints for models in the original consistency model release and update usage example.

* apply suggestions from review

* make style

* fix attention naming

* Add tests for CMStochasticIterativeScheduler.

* make style

* Make CMStochasticIterativeScheduler tests pass.

* make style

* Override test_step_shape in CMStochasticIterativeSchedulerTest instead of modifying it in SchedulerCommonTest.

* make style

* rename some models

* Improve API

* rename some models

* Remove duplicated block

* Add docstring and make torch compile work

* More fixes

* Fixes

* Apply suggestions from code review

* Apply suggestions from code review

* add more docstring

* update consistency conversion script

---------
Co-authored-by: default avatarayushmangal <ayushmangal@microsoft.com>
Co-authored-by: default avatarAyush Mangal <43698245+ayushtues@users.noreply.github.com>
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      aed7499a
  41. 16 Jun, 2023 1 commit
  43. 07 Jun, 2023 1 commit
  45. 16 May, 2023 1 commit
  47. 27 Apr, 2023 1 commit
    • Nipun Jindal's avatar
      [2064]: Add stochastic sampler (sample_dpmpp_sde) (#3020) · fd512d74
      Nipun Jindal authored 
      

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* Review comments

* [Review comment]: Add is_torchsde_available()

* [Review comment]: Test and docs

* [Review comment]

* [Review comment]

* [Review comment]

* [Review comment]

* [Review comment]

---------
Co-authored-by: default avatarnjindal <njindal@adobe.com>
      fd512d74
  49. 04 Apr, 2023 6 commits
  51. 01 Mar, 2023 1 commit
  53. 17 Feb, 2023 1 commit
  55. 16 Feb, 2023 1 commit
  57. 15 Feb, 2023 1 commit
  59. 17 Jan, 2023 1 commit
    • Kashif Rasul's avatar
      DiT Pipeline (#1806) · 37d113cc
      Kashif Rasul authored 
      

* 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: default avatarSuraj 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: default avatarSuraj 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: default avatarSuraj Patil <surajp815@gmail.com>
Co-authored-by: default avatarWilliam Berman <WLBberman@gmail.com>
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      37d113cc
  61. 04 Jan, 2023 2 commits