GitLab

* Improve docstrings and type hints in scheduling_ddim.py

- Add complete type hints for all function parameters
- Enhance docstrings to follow project conventions
- Add missing parameter descriptions

Fixes #9567

* Enhance docstrings and type hints in scheduling_ddim.py

- Update parameter types and descriptions for clarity
- Improve explanations in method docstrings to align with project standards
- Add optional annotations for parameters where applicable

* Refine type hints and docstrings in scheduling_ddim.py

- Update parameter types to use Literal for specific string options
- Enhance docstring descriptions for clarity and consistency
- Ensure all parameters have appropriate type annotations and defaults

* Apply review feedback on scheduling_ddim.py

- Replace "prevent singularities" with "avoid numerical instability" for better clarity
- Add backticks around `alpha_bar` variable name for consistent formatting
- Convert Imagen Video paper URLs to Hugging Face papers references

* Propagate changes using 'make fix-copies'

* Add missing Literal

* change syntax

* make style

* Update pipeline_flux.py

have flux pipeline work with unipc/dpm schedulers

* clean code

* Update scheduling_dpmsolver_multistep.py

* Update scheduling_unipc_multistep.py

* Update pipeline_flux.py

* Update scheduling_deis_multistep.py

* Update scheduling_dpmsolver_singlestep.py

* Apply style fixes

---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Álvaro Somoza <asomoza@users.noreply.github.com>

update

* Use HF Papers

* Apply style fixes

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

Fix `use_lu_lambdas` and `use_karras_sigmas` with `beta_schedule=squaredcos_cap_v2` in `DPMSolverMultistepScheduler` (#10740)

* fix docstrings

* add

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

---------
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 wrong output on 3n-1 steps count

* Add sde handling to 3 order

* make

* copies

---------
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

* support custom sigmas and timesteps, dpm euler

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* 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 typos

* Fix typo in SVD.md

* fix

* fix

* add a tests

* fix

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* 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>

* Setup LEdits++ file structure

* Fix import

* LEditsPP Stable Diffusion pipeline

* Include variable image aspect ratios

* Implement LEDITS++ for SDXL

* clean up LEditsPPPipelineStableDiffusion

* Adjust inversion output

* Added docu, more cleanup for LEditsPPPipelineStableDiffusion

* clean up LEditsPPPipelineStableDiffusionXL

* Update documentation

* Fix documentation import

* Add skeleton IF implementation

* Fix documentation typo

* Add LEDTIS docu to toctree

* Add missing title

* Finalize SD documentation

* Finalize SD-XL documentation

* Fix code style and quality

* Fix typo

* Fix return types

* added LEditsPPPipelineIF; minor changes for LEditsPPPipelineStableDiffusion and LEditsPPPipelineStableDiffusionXL

* Fix copy reference

* add documentation for IF

* Add first tests

* Fix batching for SD-XL

* Fix text encoding and perfect reconstruction for SD-XL

* Add tests for SD-XL, minor changes

* move user_mask to correct device, use cross_attention_kwargs also for inversion

* Example docstring

* Fix attention resolution for non-square images

* Refactoring for PR review

* Safely remove ledits_utils.py

* Style fixes

* Replace assertions with ValueError

* Remove LEditsPPPipelineIF

* Remove unecessary input checks

* Refactoring of CrossAttnProcessor

* Revert unecessary changes to scheduler

* Remove first progress-bar in inversion

* Refactor scheduler usage and reset

* Use imageprocessor instead of custom logic

* Fix scheduler init warning

* Fix error when running the pipeline in fp16

* Update documentation wrt perfect inversion

* Update tests

* Fix code quality and copy consistency

* Update LEditsPP import

* Remove enable/disable methods that are now in StableDiffusionMixin

* Change import in docs

* Revert import structure change

* Fix ledits imports

---------
Co-authored-by: Katharina Kornmeier <katharina.kornmeier@stud.tu-darmstadt.de>

* DPMMultistep rescale_betas_zero_snr

* DPM upcast samples in step()

* DPM rescale_betas_zero_snr UT

* DPMSolverMulti move sample upcast after model convert

Avoids having to re-use the dtype.

* Add a newline for Ruff

change to 2024

* fix

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

* stabilize dpmpp for sdxl by using euler at the final step

* add lu's uniform logsnr time steps

* add test

* fix check_copies

* fix tests

---------
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>

* initial commit

* move modules to import struct

* add dummy objects and _LazyModule

* add lazy import to schedulers

* clean up unused imports

* lazy import on models module

* lazy import for schedulers module

* add lazy import to pipelines module

* lazy import altdiffusion

* lazy import audio diffusion

* lazy import audioldm

* lazy import consistency model

* lazy import controlnet

* lazy import dance diffusion ddim ddpm

* lazy import deepfloyd

* lazy import kandinksy

* lazy imports

* lazy import semantic diffusion

* lazy imports

* lazy import stable diffusion

* move sd output to its own module

* clean up

* lazy import t2iadapter

* lazy import unclip

* lazy import versatile and vq diffsuion

* lazy import vq diffusion

* helper to fetch objects from modules

* lazy import sdxl

* lazy import txt2vid

* lazy import stochastic karras

* fix model imports

* fix bug

* lazy import

* clean up

* clean up

* fixes for tests

* fixes for tests

* clean up

* remove import of torch_utils from utils module

* clean up

* clean up

* fix mistake import statement

* dedicated modules for exporting and loading

* remove testing utils from utils module

* fixes from  merge conflicts

* Update src/diffusers/pipelines/kandinsky2_2/__init__.py

* fix docs

* fix alt diffusion copied from

* fix check dummies

* fix more docs

* remove accelerate import from utils module

* add type checking

* make style

* fix check dummies

* remove torch import from xformers check

* clean up error message

* fixes after upstream merges

* dummy objects fix

* fix tests

* remove unused module import

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