GitLab

docs: Update Imagen Video paper link in scheduler docstrings.

* Improve docstrings and type hints in multiple diffusion schedulers

* docs: update Imagen Video paper link to Hugging Face Papers.

* refactor: enhance type hints and documentation in EulerDiscreteScheduler

Updated type hints for function parameters and return types in the EulerDiscreteScheduler class to improve code clarity and maintainability. Enhanced docstrings for several methods to provide clearer descriptions of their functionality and expected arguments. This includes specifying Literal types for certain parameters and ensuring consistent return type annotations across the class.

* refactor: enhance type hints and documentation across multiple schedulers

Updated type hints and improved docstrings in various scheduler classes, including CMStochasticIterativeScheduler, CosineDPMSolverMultistepScheduler, and others. This includes specifying parameter types, return types, and providing clearer descriptions of method functionalities. Notable changes include the addition of default values in the begin_index argument and enhanced explanations for noise addition methods. These improvements aim to enhance code clarity and maintainability across the scheduling module.

* refactor: update docstrings to clarify noise schedule construction

Revised docstrings across multiple scheduler classes to enhance clarity regarding the construction of noise schedules. Updated references to relevant papers, ensuring accurate citations for the methodologies used. This includes changes in DEISMultistepScheduler, DPMSolverMultistepInverseScheduler, and others, improving documentation consistency and readability.

* Enhance type hints and docstrings in scheduling_ddpm.py

- Added type hints for function parameters and return types across the DDPMScheduler class and related functions.
- Improved docstrings for clarity, including detailed descriptions of parameters and return values.
- Updated the alpha_transform_type and beta_schedule parameters to use Literal types for better type safety.
- Refined the _get_variance and previous_timestep methods with comprehensive documentation.

* Refactor docstrings and type hints in scheduling_ddpm.py

- Cleaned up whitespace in the rescale_zero_terminal_snr function.
- Enhanced the variance_type parameter in the DDPMScheduler class with improved formatting for better readability.
- Updated the docstring for the compute_variance method to maintain consistency and clarity in parameter descriptions and return values.

* Apply `make fix-copies`

* Refactor type hints across multiple scheduler files

- Updated type hints to include `Literal` for improved type safety in various scheduling files.
- Ensured consistency in type hinting for parameters and return types across the affected modules.
- This change enhances code clarity and maintainability.

* change syntax

* make style

update

* Use HF Papers

* Apply style fixes

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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

use_flow_sigmas copy

[Sana] Add Sana, including `SanaPipeline`, `SanaPAGPipeline`, `LinearAttentionProcessor`, `Flow-based DPM-sovler` and so on. (#9982)

* first add a script for DC-AE;

* DC-AE init

* replace triton with custom implementation

* 1. rename file and remove un-used codes;

* no longer rely on omegaconf and dataclass

* replace custom activation with diffuers activation

* remove dc_ae attention in attention_processor.py

* iinherit from ModelMixin

* inherit from ConfigMixin

* dc-ae reduce to one file

* update downsample and upsample

* clean code

* support DecoderOutput

* remove get_same_padding and val2tuple

* remove autocast and some assert

* update ResBlock

* remove contents within super().__init__

* Update src/diffusers/models/autoencoders/dc_ae.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* remove opsequential

* update other blocks to support the removal of build_norm

* remove build encoder/decoder project in/out

* remove inheritance of RMSNorm2d from LayerNorm

* remove reset_parameters for RMSNorm2d
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* remove device and dtype in RMSNorm2d __init__
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/models/autoencoders/dc_ae.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/models/autoencoders/dc_ae.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/models/autoencoders/dc_ae.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* remove op_list & build_block

* remove build_stage_main

* change file name to autoencoder_dc

* move LiteMLA to attention.py

* align with other vae decode output;

* add DC-AE into init files;

* update

* make quality && make style;

* quick push before dgx disappears again

* update

* make style

* update

* update

* fix

* refactor

* refactor

* refactor

* update

* possibly change to nn.Linear

* refactor

* make fix-copies

* replace vae with ae

* replace get_block_from_block_type to get_block

* replace downsample_block_type from Conv to conv for consistency

* add scaling factors

* incorporate changes for all checkpoints

* make style

* move mla to attention processor file; split qkv conv to linears

* refactor

* add tests

* from original file loader

* add docs

* add standard autoencoder methods

* combine attention processor

* fix tests

* update

* minor fix

* minor fix

* minor fix & in/out shortcut rename

* minor fix

* make style

* fix paper link

* update docs

* update single file loading

* make style

* remove single file loading support; todo for DN6

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* add abstract

* 1. add DCAE into diffusers;
2. make style and make quality;

* add DCAE_HF into diffusers;

* bug fixed;

* add SanaPipeline, SanaTransformer2D into diffusers;

* add sanaLinearAttnProcessor2_0;

* first update for SanaTransformer;

* first update for SanaPipeline;

* first success run SanaPipeline;

* model output finally match with original model with the same intput;

* code update;

* code update;

* add a flow dpm-solver scripts

* 🎉[important update]
1. Integrate flow-dpm-sovler into diffusers;
2. finally run successfully on both `FlowMatchEulerDiscreteScheduler` and `FlowDPMSolverMultistepScheduler`;

* 🎉🔧

[important update & fix huge bugs!!]
1. add SanaPAGPipeline & several related Sana linear attention operators;
2. `SanaTransformer2DModel` not supports multi-resolution input;
2. fix the multi-scale HW bugs in SanaPipeline and SanaPAGPipeline;
3. fix the flow-dpm-solver set_timestep() init `model_output` and `lower_order_nums` bugs;

* remove prints;

* add convert sana official checkpoint to diffusers format Safetensor.

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/pipelines/pag/pipeline_pag_sana.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/pipelines/sana/pipeline_sana.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/pipelines/sana/pipeline_sana.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* update Sana for DC-AE's recent commit;

* make style && make quality

* Add StableDiffusion3PAGImg2Img Pipeline + Fix SD3 Unconditional PAG (#9932)

* fix progress bar updates in SD 1.5 PAG Img2Img pipeline

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Co-authored-by: Vinh H. Pham <phamvinh257@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* make the vae can be None in `__init__` of `SanaPipeline`

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: hlky <hlky@hlky.ac>

* change the ae related code due to the latest update of DCAE branch;

* change the ae related code due to the latest update of DCAE branch;

* 1. change code based on AutoencoderDC;
2. fix the bug of new GLUMBConv;
3. run success;

* update for solving conversation.

* 1. fix bugs and run convert script success;
2. Downloading ckpt from hub automatically;

* make style && make quality;

* 1. remove un-unsed parameters in init;
2. code update;

* remove test file

* refactor; add docs; add tests; update conversion script

* make style

* make fix-copies

* refactor

* udpate pipelines

* pag tests and refactor

* remove sana pag conversion script

* handle weight casting in conversion script

* update conversion script

* add a processor

* 1. add bf16 pth file path;
2. add complex human instruct in pipeline;

* fix fast \tests

* change gemma-2-2b-it ckpt to a non-gated repo;

* fix the pth path bug in conversion script;

* change grad ckpt to original; make style

* fix the complex_human_instruct bug and typo;

* remove dpmsolver flow scheduler

* apply review suggestions

* change the `FlowMatchEulerDiscreteScheduler` to default `DPMSolverMultistepScheduler` with flow matching scheduler.

* fix the tokenizer.padding_side='right' bug;

* update docs

* make fix-copies

* fix imports

* fix docs

* add integration test

* update docs

* update examples

* fix convert_model_output in schedulers

* fix failing tests

---------
Co-authored-by: Junyu Chen <chenjydl2003@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: chenjy2003 <70215701+chenjy2003@users.noreply.github.com>
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: hlky <hlky@hlky.ac>

* Fix beta and exponential sigmas + add tests

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

Fix grammatical error

* find & replace all FloatTensors to Tensor

* apply formatting

* Update torch.FloatTensor to torch.Tensor in the remaining files

* formatting

* Fix the rest of the places where FloatTensor is used as well as in documentation

* formatting

* Update new file from FloatTensor to Tensor

* add: utility to format our docs too 📜

* debugging saga

* fix: message

* checking

* should be fixed.

* revert pipeline_fixture

* remove empty line

* make style

* fix: setup.py

* style.

* Fix PyTorch's convention for inplace functions

* Fix import structure in __init__.py and update config loading logic in test_config.py

* Update configuration access

* Fix typos

* Trim trailing white spaces

* Fix typo in logger name

* Revert "Fix PyTorch's convention for inplace functions"

This reverts commit f65dc4afcb57ceb43d5d06389229d47bafb10d2d.

* Fix typo in step_index property description

* Revert "Update configuration access"

This reverts commit 8d44e870b8c1ad08802e3e904c34baeca1b598f8.

* Revert "Fix import structure in __init__.py and update config loading logic in test_config.py"

This reverts commit 2ad5e8bca25aede3b912da22bd57285b598fe171.

* Fix typos

* Fix typos

* Fix typos

* Fix a typo: tranform -> transform

* Change step_offset scheduler docstrings

* Mention it may be needed by some models

* More docstrings

These ones failed literal S&R because I performed it case-sensitive
which is fun.

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

change to 2024

* load cumprod tensor to device
Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>

* fixing ci
Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>

* make fix-copies
Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>

---------
Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>

* add Sa-Solver



---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: scxue <xueshuchen17@mails.ucas.edu.cn>
Co-authored-by: jschen <chenjunsong4@h-partners.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* correct

* Apply suggestions from code review

* make style

* fix

* copies

---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* fix dpm
* all scheulers

* begin model

* finish blocks

* add_embedding

* addition_time_embed_dim

* use TimestepEmbedding

* fix temporal res block

* fix time_pos_embed

* fix add_embedding

* add conversion script

* fix model

* up

* add new resnet blocks

* make forward work

* return sample in original shape

* fix temb shape in TemporalResnetBlock

* add spatio temporal transformers

* add vae blocks

* fix blocks

* update

* update

* fix shapes in Alphablender and add time activation in res blcok

* use new blocks

* style

* fix temb shape

* fix SpatioTemporalResBlock

* reuse TemporalBasicTransformerBlock

* fix TemporalBasicTransformerBlock

* use TransformerSpatioTemporalModel

* fix TransformerSpatioTemporalModel

* fix time_context dim

* clean up

* make temb optional

* add blocks

* rename model

* update conversion script

* remove UNetMidBlockSpatioTemporal

* add in init

* remove unused arg

* remove unused arg

* remove more unsed args

* up

* up

* check for None

* update vae

* update up/mid blocks for decoder

* begin pipeline

* adapt scheduler

* add guidance scalings

* fix norm eps in temporal transformers

* add temporal autoencoder

* make pipeline run

* fix frame decodig

* decode in float32

* decode n frames at a time

* pass decoding_t to decode_latents

* fix decode_latents

* vae encode/decode in fp32

* fix dtype in TransformerSpatioTemporalModel

* type image_latents same as image_embeddings

* allow using differnt eps in temporal block for video decoder

* fix default values in vae

* pass num frames in decode

* switch spatial to temporal for mixing in VAE

* fix num frames during split decoding

* cast alpha to sample dtype

* fix attention in MidBlockTemporalDecoder

* fix typo

* fix guidance_scales dtype

* fix missing activation in TemporalDecoder

* skip_post_quant_conv

* add vae conversion

* style

* take guidance scale as input

* up

* allow passing PIL to export_video

* accept fps as arg

* add pipeline and vae in init

* remove hack

* use AutoencoderKLTemporalDecoder

* don't scale image latents

* add unet tests

* clean up unet

* clean TransformerSpatioTemporalModel

* add slow svd test

* clean up

* make temb optional in Decoder mid block

* fix norm eps in TransformerSpatioTemporalModel

* clean up temp decoder

* clean up

* clean up

* use c_noise values for timesteps

* use math for log

* update

* fix copies

* doc

* upcast vae

* update forward pass for gradient checkpointing

* make added_time_ids is tensor

* up

* fix upcasting

* remove post quant conv

* add _resize_with_antialiasing

* fix _compute_padding

* cleanup model

* more cleanup

* more cleanup

* more cleanup

* remove freeu

* remove attn slice

* small clean

* up

* up

* remove extra step kwargs

* remove eta

* remove dropout

* remove callback

* remove merge factor args

* clean

* clean up

* move to dedicated folder

* remove attention_head_dim

* docstr and small fix

* update unet doc strings

* rename decoding_t

* correct linting

* store c_skip and c_out

* cleanup

* clean TemporalResnetBlock

* more cleanup

* clean up vae

* clean up

* begin doc

* more cleanup

* up

* up

* doc

* Improve

* better naming

* better naming

* better naming

* better naming

* better naming

* better naming

* better naming

* better naming

* Apply suggestions from code review

* Default chunk size to None

* add example

* Better

* Apply suggestions from code review

* update doc

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

* style

* Get torch compile working

* up

* rename

* fix doc

* add chunking

* torch compile

* torch compile

* add modelling outputs

* torch compile

* Improve chunking

* Apply suggestions from code review

* Update docs/source/en/using-diffusers/svd.md

* Close diff tag

* remove slicing

* resnet docstr

* add docstr in resnet

* rename

* Apply suggestions from code review

* update tests

* Fix output type latents

* fix more

* fix more

* Update docs/source/en/using-diffusers/svd.md

* fix more

* add pipeline tests

* remove unused arg

* clean  up

* make sure get_scaling receives tensors

* fix euler scheduler

* fix get_scalings

* simply euler for now

* remove old test file

* use randn_tensor to create noise

* fix device for rand tensor

* increase expected_max_difference

* fix test_inference_batch_single_identical

* actually fix test_inference_batch_single_identical

* disable test_save_load_float16

* skip test_float16_inference

* skip test_inference_batch_single_identical

* fix test_xformers_attention_forwardGenerator_pass

* Apply suggestions from code review

* update StableVideoDiffusionPipelineSlowTests

* update image

* add diffusers example

* fix more

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: apolinário <joaopaulo.passos@gmail.com>

* ruff format

* not need to use doc-builder's black styling as the doc is styled in ruff

* make fix-copies

* comment

* use run_ruff

* Update Unipc einsum to support 1D and 3D diffusion.

* Add unittest

* Update unittest & edge case

* Fix unittest

* Fix testing_utils.py

* Fix unittest file

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

* remove to _device() for sigmas

* update add_noise to use simgas

---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>

---------
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

---------
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