GitLab

* initial sparse control model draft

* remove unnecessary implementation

* copy animatediff pipeline

* remove deprecated callbacks

* update

* update pipeline implementation progress

* make style

* make fix-copies

* update progress

* add partially working pipeline

* remove debug prints

* add model docs

* dummy objects

* improve motion lora conversion script

* fix bugs

* update docstrings

* remove unnecessary model params; docs

* address review comment

* add copied from to zero_module

* copy animatediff test

* add fast tests

* update docs

* update

* update pipeline docs

* fix expected slice values

* fix license

* remove get_down_block usage

* remove temporal_double_self_attention from get_down_block

* update

* update docs with org and documentation images

* make from_unet work in sparsecontrolnetmodel

* add latest freeinit test from #8969

* make fix-copies

* LoraLoaderMixin -> StableDiffsuionLoraLoaderMixin

* add pipeline docs for latte

* add inference time to latte docs

* apply review suggestions

* add pag support sd15 controlnet

* fix quality import

* remove unecessary import

* remove if state

* fix tests

* remove useless function

* add sd1.5 controlnet pag docs

---------
Co-authored-by: anhnct8 <anhnct8@fpt.com>

* add pipeline documentation.

* add api spec for pipeline

* model documentation

* model spec

* update

* update

* update

* update

* initial draft

---------
Co-authored-by: zhuole1025 <zhuole1025@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* up

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

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

* add pag to sd pipelines

* add controlnet support

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

* doc for max_sequence_length

* better position and changed note to tip

* apply suggestions

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

* first draft


---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Junhwa Song <ethan9867@gmail.com>
Co-authored-by: Ahn Donghoon (안동훈 / suno) <suno.vivid@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

add note

* Fix typos

* Fix typos & up style

* chore: Update numbers

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

* Discourage using `revision`

* `make style && make quality`

* Refactor code to use 'variant' instead of 'revision'

* `revision="bf16"` -> `variant="bf16"`

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

* Trim all the trailing white space in the whole repo

* Remove unnecessary empty places

* make style && make quality

* Trim trailing white space

* trim

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

* sd3 controlnet



---------
Co-authored-by: haofanwang <haofanwang.ai@gmail.com>

[SD3 Docs] Corrected title about loading model with T5

Corrected the documentation title to "Loading the single file checkpoint with T5" Previously, it incorrectly stated "Loading the single file checkpoint without T5" which contradicted the code snippet showing how to load the SD3 checkpoint with the T5 model

* shift factor argument to tiny

* remove shift factor rejigging from the sd3 docs

* tased3 docs

* apply suggestion

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

* update

* update

* up

* add sd3

* update

* update

* add tests

* fix copies

* fix docs

* update

* add dreambooth lora

* add LoRA

* update

* update

* update

* update

* import fix

* update

* Update src/diffusers/pipelines/stable_diffusion_3/pipeline_stable_diffusion_3.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* import fix 2

* update

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

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

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

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

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

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

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

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

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

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

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

* update

* update

* update

* fix ckpt id

* fix more ids

* update

* missing doc

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

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

* Update docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_3.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_3.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update'

* fix

* update

* Update src/diffusers/models/autoencoders/autoencoder_kl.py

* Update src/diffusers/models/autoencoders/autoencoder_kl.py

* note on gated access.

* requirements

* licensing

---------
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Refactor code to remove unnecessary calls to `to(torch_device)`

* Refactor code to remove unnecessary calls to `to("cuda")`

* Update pipeline_stable_diffusion_diffedit.py

* optimizations to the hunyuan dit docs.

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

* Update docs/source/en/api/pipelines/hunyuandit.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* 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

* allow hunyuan dit to run under 6GB for GPU VRAM

* add section in the docs/

minor docs changes in hunyuandit

* add hunyuandit doc

* update hunyuandit doc

* update hunyuandit 2d model

* update toctree.yml for hunyuandit

* implement marigold depth and normals pipelines in diffusers core

* remove bibtex

* remove deprecations

* remove save_memory argument

* remove validate_vae

* remove config output

* remove batch_size autodetection

* remove presets logic
move default denoising_steps and processing_resolution into the model config
make default ensemble_size 1

* remove no_grad

* add fp16 to the example usage

* implement is_matplotlib_available
use is_matplotlib_available, is_scipy_available for conditional imports in the marigold depth pipeline

* move colormap, visualize_depth, and visualize_normals into export_utils.py

* make the denoising loop more lucid
fix the outputs to always be 4d tensors or lists of pil images
support a 4d input_image case
attempt to support model_cpu_offload_seq
move check_inputs into a separate function
change default batch_size to 1, remove any logic to make it bigger implicitly

* style

* rename denoising_steps into num_inference_steps

* rename input_image into image

* rename input_latent into latents

* remove decode_image
change decode_prediction to use the AutoencoderKL.decode method

* move clean_latent outside of progress_bar

* refactor marigold-reusable image processing bits into MarigoldImageProcessor class

* clean up the usage example docstring

* make ensemble functions members of the pipelines

* add early checks in check_inputs
rename E into ensemble_size in depth ensembling

* fix vae_scale_factor computation

* better compatibility with torch.compile
better variable naming

* move export_depth_to_png to export_utils

* remove encode_prediction

* improve visualize_depth and visualize_normals to accept multi-dimensional data and lists
remove visualization functions from the pipelines
move exporting depth as 16-bit PNGs functionality from the depth pipeline
update example docstrings

* do not shortcut vae.config variables

* change all asserts to raise ValueError

* rename output_prediction_type to output_type

* better variable names
clean up variable deletion code

* better variable names

* pass desc and leave kwargs into the diffusers progress_bar
implement nested progress bar for images and steps loops

* implement scale_invariant and shift_invariant flags in the ensemble_depth function
add scale_invariant and shift_invariant flags readout from the model config
further refactor ensemble_depth
support ensembling without alignment
add ensemble_depth docstring

* fix generator device placement checks

* move encode_empty_text body into the pipeline call

* minor empty text encoding simplifications

* adjust pipelines' class docstrings to explain the added construction arguments

* improve the scipy failure condition
add comments
improve docstrings
change the default use_full_z_range to True

* make input image values range check configurable in the preprocessor
refactor load_image_canonical in preprocessor to reject unknown types and return the image in the expected 4D format of tensor and on right device
support a list of everything as inputs to the pipeline, change type to PipelineImageInput
implement a check that all input list elements have the same dimensions
improve docstrings of pipeline outputs
remove check_input pipeline argument

* remove forgotten print

* add prediction_type model config

* add uncertainty visualization into export utils
fix NaN values in normals uncertainties

* change default of output_uncertainty to False
better handle the case of an attempt to export or visualize none

* fix `output_uncertainty=False`

* remove kwargs
fix check_inputs according to the new inputs of the pipeline

* rename prepare_latent into prepare_latents as in other pipelines
annotate prepare_latents in normals pipeline with "Copied from"
annotate encode_image in normals pipeline with "Copied from"

* move nested-capable `progress_bar` method into the pipelines
revert the original `progress_bar` method in pipeline_utils

* minor message improvement

* fix cpu offloading

* move colormap, visualize_depth, export_depth_to_16bit_png, visualize_normals, visualize_uncertainty to marigold_image_processing.py
update example docstrings

* fix missing comma

* change torch.FloatTensor to torch.Tensor

* fix importing of MarigoldImageProcessor

* fix vae offloading
fix batched image encoding
remove separate encode_image function and use vae.encode instead

* implement marigold's intial tests
relax generator checks in line with other pipelines
implement return_dict __call__ argument in line with other pipelines

* fix num_images computation

* remove MarigoldImageProcessor and outputs from import structure
update tests

* update docstrings

* update init

* update

* style

* fix

* fix

* up

* up

* up

* add simple test

* up

* update expected np input/output to be channel last

* move expand_tensor_or_array into the MarigoldImageProcessor

* rewrite tests to follow conventions - hardcoded slices instead of image artifacts
write more smoke tests

* add basic docs.

* add anton's contribution statement

* remove todos.

* fix assertion values for marigold depth slow tests

* fix assertion values for depth normals.

* remove print

* support AutoencoderTiny in the pipelines

* update documentation page
add Available Pipelines section
add Available Checkpoints section
add warning about num_inference_steps

* fix missing import in docstring
fix wrong value in visualize_depth docstring

* [doc] add marigold to pipelines overview

* [doc] add section "usage examples"

* fix an issue with latents check in the pipelines

* add "Frame-by-frame Video Processing with Consistency" section

* grammarly

* replace tables with images with css-styled images (blindly)

* style

* print

* fix the assertions.

* take from the github runner.

* take the slices from action artifacts

* style.

* update with the slices from the runner.

* remove unnecessary code blocks.

* Revert "[doc] add marigold to pipelines overview"

This reverts commit a505165150afd8dab23c474d1a054ea505a56a5f.

* remove invitation for new modalities

* split out marigold usage examples

* doc cleanup

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

* Add details about 1-stage implementation

* Add details about 1-stage implementation

* 1. add doc for PixArtSigmaPipeline;

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Guillaume LEGENDRE <glegendre01@gmail.com>
Co-authored-by: Álvaro Somoza <asomoza@users.noreply.github.com>
Co-authored-by: Bagheera <59658056+bghira@users.noreply.github.com>
Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Hyoungwon Cho <jhw9811@korea.ac.kr>
Co-authored-by: yiyixuxu <yixu310@gmail.com>
Co-authored-by: Tolga Cangöz <46008593+standardAI@users.noreply.github.com>
Co-authored-by: Philip Pham <phillypham@google.com>

* update conversion script to handle motion adapter sdxl checkpoint

* add animatediff xl

* handle addition_embed_type

* fix output

* update

* add imports

* make fix-copies

* add decode latents

* update docstrings

* add animatediff sdxl to docs

* remove unnecessary lines

* update example

* add test

* revert conv_in conv_out kernel param

* remove unused param addition_embed_type_num_heads

* latest IPAdapter impl

* make fix-copies

* fix return

* add IPAdapterTesterMixin to tests

* fix return

* revert based on suggestion

* add freeinit

* fix test_to_dtype test

* use StableDiffusionMixin instead of different helper methods

* fix progress bar iterations

* apply suggestions from review

* hardcode flip_sin_to_cos and freq_shift

* make fix-copies

* fix ip adapter implementation

* fix last failing test

* make style

* Update docs/source/en/api/pipelines/animatediff.md
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* remove todo

* fix doc-builder errors

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* refactor

* code snippets

* fix path

* fix path in guide

* code outputs

* align toctree title

* title

* fix title

* autopipeline

* edits

* feedback

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

* CheckIn - created DownSubBlocks

* Added extra channels, implemented subblock fwd

* Fixed connection sizes

* checkin

* Removed iter, next in forward

* Models for SD21 & SDXL run through

* Added back pipelines, cleared up connections

* Cleaned up connection creation

* added debug logs

* updated logs

* logs: added input loading

* Update umer_debug_logger.py

* log: Loading hint

* Update umer_debug_logger.py

* added logs

* Changed debug logging

* debug: added more logs

* Fixed num_norm_groups

* Debug: Logging all of SDXL input

* Update umer_debug_logger.py

* debug: updated logs

* checkim

* Readded tests

* Removed debug logs

* Fixed Slow Tests

* Added value ckecks | Updated model_cpu_offload_seq

* accelerate-offloading works ; fast tests work

* Made unet & addon explicit in controlnet

* Updated slow tests

* Added dtype/device to ControlNetXS

* Filled in test model paths

* Added image_encoder/feature_extractor to XL pipe

* Fixed fast tests

* Added comments and docstrings

* Fixed copies

* Added docs ; Updates slow tests

* Moved changes to UNetMidBlock2DCrossAttn

* tiny cleanups

* Removed stray prints

* Removed ip adapters + freeU

- Removed ip adapters + freeU as they don't make sense for ControlNet-XS
- Fixed imports of UNet components

* Fixed test_save_load_float16

* Make style, quality, fix-copies

* Changed loading/saving API for ControlNetXS

- Changed loading/saving API for ControlNetXS
- other small fixes

* Removed ControlNet-XS from research examples

* Make style, quality, fix-copies

* Small fixes

- deleted ControlNetXSModel.init_original
- added time_embedding_mix to StableDiffusionControlNetXSPipeline .from_pretrained / StableDiffusionXLControlNetXSPipeline.from_pretrained
- fixed copy hints

* checkin May 11 '23

* CheckIn Mar 12 '24

* Fixed tests for SD

* Added tests for UNetControlNetXSModel

* Fixed SDXL tests

* cleanup

* Delete Pipfile

* CheckIn Mar 20

Started replacing sub blocks  by `ControlNetXSCrossAttnDownBlock2D` and `ControlNetXSCrossAttnUplock2D`

* check-in Mar 23

* checkin 24 Mar

* Created init for UNetCnxs and CnxsAddon

* CheckIn

* Made from_modules, from_unet and no_control work

* make style,quality,fix-copies & small changes

* Fixed freezing

* Added gradient ckpt'ing; fixed tests

* Fix slow tests(+compile) ; clear naming confusion

* Don't create UNet in init ; removed class_emb

* Incorporated review feedback

- Deleted get_base_pipeline /  get_controlnet_addon for pipes
- Pipes inherit from StableDiffusionXLPipeline
- Made module dicts for cnxs-addon's down/mid/up classes
- Added support for qkv fusion and freeU

* Make style, quality, fix-copies

* Implemented review feedback

* Removed compatibility check for vae/ctrl embedding

* make style, quality, fix-copies

* Delete Pipfile

* Integrated review feedback

- Importing ControlNetConditioningEmbedding now
- get_down/mid/up_block_addon now outside class
- renamed `do_control` to `apply_control`

* Reduced size of test tensors

For this, added `norm_num_groups` as parameter everywhere

* Renamed cnxs-`Addon` to cnxs-`Adapter`

- `ControlNetXSAddon` -> `ControlNetXSAdapter`
- `ControlNetXSAddonDownBlockComponents` -> `DownBlockControlNetXSAdapter`, and similarly for mid/up
- `get_mid_block_addon` -> `get_mid_block_adapter`, and similarly for mid/up

* Fixed save_pretrained/from_pretrained bug

* Removed redundant code

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* refactor t2i

* add code snippets

* add audioldm2 tts

* change gpt2 max new tokens

* remove unnecessary pipeline and class

* add TTS to AudioLDM2Pipeline

* add TTS docs

* delete unnecessary file

* remove unnecessary import

* add audioldm2 slow testcase

* fix code quality

* remove AudioLDMLearnablePositionalEmbedding

* add variable check vits encoder

* add use_learned_position_embedding

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* update

* fix

* gradio docs

* Update docs/source/en/api/pipelines/stable_diffusion/overview.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* changes

* changes

* changes

* Update docs/source/en/api/pipelines/stable_diffusion/overview.md

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