GitLab

move kandinsky convert script

* add

* fix api docs

* edits

* Support IP-Adapter Plus

* fix format

* restore before black format

* restore before black format

* generic

* Refactor PerceiverAttention

* format

* fix test and refactor PerceiverAttention

* generic encode_image

* keep attention implementation

* merge tests

* encode_image backward compatible

* code quality

* fix controlnet inpaint pipeline

* refactor FFN

* refactor FFN

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

* update setup and deps table

* update

* update

* update

* up

* up

* update

* up

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* quality fix

* fix failure reporting

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

* Update value_guided_sampling.py

Changed the scheduler step function as predict_epsilon parameter is not there in latest  DDPM Scheduler

* Update value_guided_sampling.md

Updated a link to a working notebook

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

* fix: duplicate unet prefix problem.

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

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

* adapt PixArtAlphaPipeline for pixart-lcm model

* remove original_inference_steps from __call__

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

* Post Release: v0.24.0

* post pone deprecation

* post pone deprecation

* Add model_index.json

* fix dpm
* all scheulers

clean-up kendinsky 3.0

Fix assertion bug

Allow text encoder to be passed

Update __init__.py

* 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>

* Fixed custom module importing on Windows

Windows use back slash and `os.path.join()` follows that convention.

* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>

* Update pipeline_utils.py

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

* integrated sdxl for the text2video-zero pipeline

* make fix-copies

* fixed CI issues

* make fix-copies

* added docs and `copied from` statements

* added fast tests

* made a small change in docs

* quality+style check fix

* updated docs. added controlnet inference with sdxl

* added device compatibility for fast tests

* fixed docstrings

* changing vae upcasting

* remove torch.empty_cache to speed up inference
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* made fast tests to run on dummy models only, fixed copied from statements

* fixed testing utils imports

* Added bullet points for SDXL support

* fixed formatting & quality

* Update tests/pipelines/text_to_video/test_text_to_video_zero_sdxl.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update tests/pipelines/text_to_video/test_text_to_video_zero_sdxl.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fixed minor error for merging

* fixed updates of sdxl

* made fast tests inherit from `PipelineTesterMixin` and run in 3-4secs on CPU

* make style && make quality

* reimplemented fast tests w/o default attn processor

* make style & make quality

* make fix-copies

* make fix-copies

* fixed docs

* make style & make quality & make fix-copies

* bug fix in cross attention

* make style && make quality

* make fix-copies

* fix gpu issues

* make fix-copies

* updated pipeline signature

---------
Co-authored-by: Vahram <vahram.tadevosyan@lambda-loginnode02.cm.cluster>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Add SSD-1B support for controlnet model

* Add conditioning_channels into ControlNet init from unet

* Fix black formatting

* Isort fixes

* Adds SSD-1B controlnet pipeline test with UNetMidBlock2D as mid block

* Overrides failing ssd-1b tests

* Fixes tests after main branch update

* Fixes code quality checks

---------
Co-authored-by: Marko Kostiv <marko@linearity.io>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Change pipeline_controlnet_inpaint.py to add ip-adapter support. Changes are similar to those in pipeline_controlnet

* Change tests for the StableDiffusionControlNetInpaintPipeline by adding image_encoder: None

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

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

* move several state dict conversion utils out of lora.py

* check

* check

* check

* check

* check

* check

* check

* revert back

* check

* check

* again check

* maybe fix?

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

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

---------
Co-authored-by: Aflalo <estellea@isl-gpu27.rr.intel.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

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

* add comments to explain the code better

* add comments to explain the code better

* add comments to explain the code better

* add comments to explain the code better

* add comments to explain the code better

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using.

* Update src/diffusers/models/unet_2d_blocks.py

This changes suggest by maintener.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update src/diffusers/models/unet_2d_blocks.py

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

* Update unet_2d_blocks.py

I changed the Parameter to Args text.

* Update unet_2d_blocks.py

proper indentation set in this file.

* Update unet_2d_blocks.py

a little bit of change in the act_fun argument line.

* I run the black command to reformat style in the code

* Update unet_2d_blocks.py

similar doc-string add to have in the original diffusion repository.

* I enhanced the code by replacing multiple redundant variables with a single variable, as they all served the same purpose. Additionally, I utilized the get_activation function for improved flexibility in choosing activation functions.

* Using as black package to reformated my file

* reverte some changes

* Remove conv_out_padding variables and using as conv_in_padding

* conv_out_padding create and add them into the code.

* run black command to solving styling problem

* add little bit space between comment and import statement

* I am utilizing the ruff library to address the style issues in my Makefile.

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Avoid computing min() that is expensive when do_normalize is False

Avoid extra computing when do_normalize is False

* Add custom timesteps support to LCMScheduler.

* Add custom timesteps support to StableDiffusionPipeline.

* Add custom timesteps support to StableDiffusionXLPipeline.

* Add custom timesteps support to remaining Stable Diffusion pipelines which support LCMScheduler (img2img, inpaint).

* Add custom timesteps support to remaining Stable Diffusion XL pipelines which support LCMScheduler (img2img, inpaint).

* Add custom timesteps support to StableDiffusionControlNetPipeline.

* Add custom timesteps support to T21 Stable Diffusion (XL) Adapters.

* Clean up Stable Diffusion inpaint tests.

* Manually add support for custom timesteps to AltDiffusion pipelines since make fix-copies doesn't appear to work correctly (it deletes the whole pipeline).

* make style

* Refactor pipeline timestep handling into the retrieve_timesteps function.

* deprecated: KarrasVeScheduler, ScoreSdeVpScheduler

* delete tests relevant to deprecated schedulers

* chore: run make style

* fix: import error caused due to incorrect _import_structure after deprecation

* fix: ScoreSdeVpScheduler was not importable from diffusers

* remove import added by assumption

* Update src/diffusers/schedulers/__init__.py as suggested by @patrickvonplaten
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* make it a part deprecated

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

* Fix

* fix

* fix doc

* fix doc....again.......

* remove karras_ve test folder
Co-Authored-By: YiYi Xu <yixu310@gmail.com>

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

add support for gradient checkpointing in transformer_2d

* [Fix: pixart-alpha]
add ASPECT_RATIO_512_BIN in use_resolution_binning for random 512px image generation.

* add slow test file for 512px generation without resolution binning

* fix: slow tests for resolution binning.

---------
Co-authored-by: jschen <chenjunsong4@h-partners.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* finalize

* finalize

* finalize

* add slow test

* add slow test

* add slow test

* Fix more

* add slow test

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* Better

* Fix more

* Fix more

* add slow test

* Add auto pipelines

* add slow test

* Add all

* add slow test

* add slow test

* add slow test

* add slow test

* add slow test

* Apply suggestions from code review

* add slow test

* add slow test

* [Lora] Seperate logic

* [Lora] Seperate logic

* [Lora] Seperate logic

* add comments to explain the code better

* add comments to explain the code better

* add ip-adapter


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Co-authored-by: okotaku <to78314910@gmail.com>
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* fix

* feedback

* add new callbacks to src/diffusers/pipelines/controlnet/pipeline_controlnet.py

* update callbacks

* fix repeated kwarg

* update

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

* first draft

* remove old loader doc

* start adding lora code examples

* finish

* add link to loralinearlayer

* feedback

* fix

* Change LCMScheduler.set_timesteps to pick more evenly spaced inference timesteps.

* Change inference_indices implementation to better match previous behavior.

* Add num_inference_steps=26 test case to test_inference_steps.

* run CI

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Co-authored-by: patil-suraj <surajp815@gmail.com>

An upcoming change to JAX will include non-local (addressable) CPU devices in jax.devices() when JAX is used multicontroller-style, where there are multiple Python processes.

This change preserves the current behavior by replacing uses of jax.devices("cpu"), which previously only returned local devices, with jax.local_devices("cpu"), which will return local devices both now and in the future.

This change is always safe (i.e., it should always preserve the previous behavior), but it may sometimes be unnecessary if code is never used in a multicontroller setting.
Co-authored-by: Peter Hawkins <phawkins@google.com>