GitLab

* convert tensorrt controlnet

* Fix code quality

* Fix code quality

* Fix code quality

* Fix code quality

* Fix code quality

* Fix code quality

* Fix number controlnet condition

* Add convert SD XL to onnx

* Add convert SD XL to tensorrt

* Add convert SD XL to tensorrt

* Add examples in comments

* Add examples in comments

* Add test onnx controlnet

* Add tensorrt test

* Remove copied

* Move file test to examples/community

* Remove script

* Remove script

* Remove text

* Fix import

* Fix T2I MultiAdapter

* fix tests

---------
Co-authored-by: dotieuthien <thien.do@mservice.com.vn>
Co-authored-by: dotieuthien <dotieuthien9997@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: dotieuthien <hades@cinnamon.is>

* Implement `CustomDiffusionAttnProcessor2_0`

* Doc-strings and type annotations for `CustomDiffusionAttnProcessor2_0`. (#1)

* Update attnprocessor.md

* Update attention_processor.py

* Interops for `CustomDiffusionAttnProcessor2_0`.

* Formatted `attention_processor.py`.

* Formatted doc-string in `attention_processor.py`

* Conditional CustomDiffusion2_0 for training example.

* Remove unnecessary reference impl in comments.

* Fix `save_attn_procs`.

* [LoRA] fix typo in attention_processor.py

fixes #5062

* make style

* make fix-copies, logger comented for torch compile

Remove logger.info statement from Unet2DCondition code to ensure torch compile reliably succeeds (#4982)

* Remove logger.info statement from Unet2DCondition code to ensure torch compile reliably succeeds

* Convert logging statement to a comment for future archaeologists

* Update src/diffusers/models/unet_2d_condition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

* Add attn_groups argument to UNet2DMidBlock2D to control theinternal Attention block's GroupNorm.

* Add docstring for attn_norm_num_groups in UNet2DModel.

* Since the test UNet config uses resnet_time_scale_shift == 'scale_shift', also set attn_norm_num_groups to 32.

* Add test for attn_norm_num_groups to UNet2DModelTests.

* Fix expected slices for slow tests.

* Also fix tolerances for slow tests.

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

* Add files via upload
Co-authored-by: Shahmatov Arseniy <62886550+cene555@users.noreply.github.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* [Release 0.21] Bump version

* fix & remove

* fix more

* fix all, upload

make optional arguments explciit

* fix lora fuse unfuse

* add same changes to loaders.py

* add test

---------
Co-authored-by: multimodalart <joaopaulo.passos+multimodal@gmail.com>

* speed up lora loading

* Apply suggestions from code review

* up

* up

* Fix more

* Correct more

* Apply suggestions from code review

* up

* Fix more

* Fix more -

* up

* up

* [Utils] Correct custom init sort

* [Utils] Correct custom init sort

* [Utils] Correct custom init sort

* add type checking

* fix custom init sort

* fix test

* fix tests

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

* initial

* initial

* added initial convert script for paella vqmodel

* initial wuerstchen pipeline

* add LayerNorm2d

* added modules

* fix typo

* use model_v2

* embed clip caption amd negative_caption

* fixed name of var

* initial modules in one place

* WuerstchenPriorPipeline

* inital shape

* initial denoising prior loop

* fix output

* add WuerstchenPriorPipeline to __init__.py

* use the noise ratio in the Prior

* try to save pipeline

* save_pretrained working

* Few additions

* add _execution_device

* shape is int

* fix batch size

* fix shape of ratio

* fix shape of ratio

* fix output dataclass

* tests folder

* fix formatting

* fix float16 + started with generator

* Update pipeline_wuerstchen.py

* removed vqgan code

* add WuerstchenGeneratorPipeline

* fix WuerstchenGeneratorPipeline

* fix docstrings

* fix imports

* convert generator pipeline

* fix convert

* Work on Generator Pipeline. WIP

* Pipeline works with our diffuzz code

* apply scale factor

* removed vqgan.py

* use cosine schedule

* redo the denoising loop

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

* use torch.lerp

* use warp-diffusion org

* clip_sample=False,

* some refactoring

* use model_v3_stage_c

* c_cond size

* use clip-bigG

* allow stage b clip to be None

* add dummy

* würstchen scheduler

* minor changes

* set clip=None in the pipeline

* fix attention mask

* add attention_masks to text_encoder

* make fix-copies

* add back clip

* add text_encoder

* gen_text_encoder and tokenizer

* fix import

* updated pipeline test

* undo changes to pipeline test

* nip

* fix typo

* fix output name

* set guidance_scale=0 and remove diffuze

* fix doc strings

* make style

* nip

* removed unused

* initial docs

* rename

* toc

* cleanup

* remvoe test script

* fix-copies

* fix multi images

* remove dup

* remove unused modules

* undo changes for debugging

* no  new line

* remove dup conversion script

* fix doc string

* cleanup

* pass default args

* dup permute

* fix some tests

* fix prepare_latents

* move Prior class to modules

* offload only the text encoder and vqgan

* fix resolution calculation for prior

* nip

* removed testing script

* fix shape

* fix argument to set_timesteps

* do not change .gitignore

* fix resolution calculations + readme

* resolution calculation fix + readme

* small fixes

* Add combined pipeline

* rename generator -> decoder

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

* removed efficient_net

* create combined WuerstchenPipeline

* make arguments consistent with VQ model

* fix var names

* no need to return text_encoder_hidden_states

* add latent_dim_scale to config

* split model into its own file

* add WuerschenPipeline to docs

* remove unused latent_size

* register latent_dim_scale

* update script

* update docstring

* use Attention preprocessor

* concat with normed input

* fix-copies

* add docs

* fix test

* fix style

* add to cpu_offloaded_model

* updated type

* remove 1-line func

* updated type

* initial decoder test

* formatting

* formatting

* fix autodoc link

* num_inference_steps is int

* remove comments

* fix example in docs

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

* rename layernorm to WuerstchenLayerNorm

* rename DiffNext to WuerstchenDiffNeXt

* added comment about MixingResidualBlock

* move paella vq-vae to pipelines' folder

* initial decoder test

* increased test_float16_inference expected diff

* self_attn is always true

* more passing decoder tests

* batch image_embeds

* fix failing tests

* set the correct dtype

* relax inference test

* update prior

* added combined pipeline test

* faster test

* faster test

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

* fix issues from review

* update wuerstchen.md + change generator name

* resolve issues

* fix copied from usage and add back batch_size

* fix API

* fix arguments

* fix combined test

* Added timesteps argument + fixes

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

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

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

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

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

* Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py

* up

* Fix more

* failing tests

* up

* up

* correct naming

* correct docs

* correct docs

* fix test params

* correct docs

* fix classifier free guidance

* fix classifier free guidance

* fix more

* fix all

* make tests faster

---------
Co-authored-by: Dominic Rampas <d6582533@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Dominic Rampas <61938694+dome272@users.noreply.github.com>

* Add dropout param to get_down_block/get_up_block and UNet2DModel/UNet2DConditionModel.

* Add dropout param to Versatile Diffusion modeling, which has a copy of UNet2DConditionModel and its own get_down_block/get_up_block functions.

* throw warning when more than one lora is attempted to be fused.

* introduce support of lora scale during fusion.

* change test name

* changes

* change to _lora_scale

* lora_scale to call whenever applicable.

* debugging

* lora_scale additional.

* cross_attention_kwargs

* lora_scale -> scale.

* lora_scale fix

* lora_scale in patched projection.

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* styling.

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* remove unneeded prints.

* remove unneeded prints.

* assign cross_attention_kwargs.

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* clean up.

* refactor scale retrieval logic a bit.

* fix nonetypw

* fix: tests

* add more tests

* more fixes.

* figure out a way to pass lora_scale.

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

* unify the retrieval logic of lora_scale.

* move adjust_lora_scale_text_encoder to lora.py.

* introduce dynamic adjustment lora scale support to sd

* fix up copies

* Empty-Commit

* add: test to check fusion equivalence on different scales.

* handle lora fusion warning.

* make lora smaller

* make lora smaller

* make lora smaller

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

* proposal for flaky tests

* more precision fixes

* move more tests to use cosine distance

* more test fixes

* clean up

* use default attn

* clean up

* update expected value

* make style

* make style

* Apply suggestions from code review

* Update src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py

* make style

* fix failing tests

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

* Add GLIGEN Text Image implementation

* add style transfer from image

* fix check_repository_consistency

* add convert script GLIGEN model to Diffusers

* rename attention type

* fix style code

* remove PositionNetTextImage

* Revert "fix check_repository_consistency"

This reverts commit 15f098c96e00bb9e67b831161615b30a2d28d815.

* change attention type name

* update docs for GLIGEN

* change examples with hf-document-image

* fix style

* add CLIPImageProjection for GLIGEN

* Add new encode_prompt, load project matrix in pipe init

* move CLIPImageProjection to stable_diffusion

* add comment

* Fix Unfuse Lora

* add tests

* Fix more

* Fix more

* Fix all

* make style

* make style

* adding save and load for MultiAdapter, adding test

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

* Adding changes from review test_stable_diffusion_adapter

* import sorting fix

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

* Fuse loras

* initial implementation.

* add slow test one.

* styling

* add: test for checking efficiency

* print

* position

* place model offload correctly

* style

* style.

* unfuse test.

* final checks

* remove warning test

* remove warnings altogether

* debugging

* tighten up tests.

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* denugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debuging

* debugging

* debugging

* debugging

* suit up the generator initialization a bit.

* remove print

* update assertion.

* debugging

* remove print.

* fix: assertions.

* style

* can generator be a problem?

* generator

* correct tests.

* support text encoder lora fusion.

* tighten up tests.

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

* T2I-Adapter-XL

* update

* update

* add pipeline

* modify pipeline

* modify pipeline

* modify pipeline

* modify pipeline

* modify pipeline

* modify modeling_text_unet

* fix styling.

* fix: copies.

* adapter settings

* new test case

* new test case

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* revert prints.

* new test case

* remove print

* org test case

* add test_pipeline

* styling.

* fix copies.

* modify test parameter

* style.

* add adapter-xl doc

* double quotes in docs

* Fix potential type mismatch

* style.

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

* [LoRA Attn] Refactor LoRA attn

* correct for network alphas

* fix more

* fix more tests

* fix more tests

* Move below

* Finish

* better version

* correct serialization format

* fix

* fix more

* fix more

* fix more

* Apply suggestions from code review

* Update src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py

* deprecation

* relax atol for slow test slighly

* Finish tests

* make style

* make style

Fix torch compile for controlnete

* [fix] multi t2i adapter set total_downscale_factor

* move image checks into check inputs

* remove copied from

* Fix AutoencoderTiny encoder scaling convention

  * Add [-1, 1] -> [0, 1] rescaling to EncoderTiny

  * Move [0, 1] -> [-1, 1] rescaling from AutoencoderTiny.decode to DecoderTiny
    (i.e. immediately after the final conv, as early as possible)

  * Fix missing [0, 255] -> [0, 1] rescaling in AutoencoderTiny.forward

  * Update AutoencoderTinyIntegrationTests to protect against scaling issues.
    The new test constructs a simple image, round-trips it through AutoencoderTiny,
    and confirms the decoded result is approximately equal to the source image.
    This test checks behavior with and without tiling enabled.
    This test will fail if new AutoencoderTiny scaling issues are introduced.

  * Context: Raw TAESD weights expect images in [0, 1], but diffusers'
    convention represents images with zero-centered values in [-1, 1],
    so AutoencoderTiny needs to scale / unscale images at the start of
    encoding and at the end of decoding in order to work with diffusers.

* Re-add existing AutoencoderTiny test, update golden values

* Add comments to AutoencoderTiny.forward

* from audioldm

* unet down + mid

* vae, clap, flan-t5

* start sequence audio mae

* iterate on audioldm encoder

* finish encoder

* finish weight conversion

* text pre-processing

* gpt2 pre-processing

* fix projection model

* working

* unet equivalence

* finish in base

* add unet cond

* finish unet

* finish custom unet

* start clean-up

* revert base unet changes

* refactor pre-processing

* tests: from audioldm

* fix some tests

* more fixes

* iterate on tests

* make fix copies

* harden fast tests

* slow integration tests

* finish tests

* update checkpoint

* update copyright

* docs

* remove outdated method

* add docstring

* make style

* remove decode latents

* enable cpu offload

* (text_encoder_1, tokenizer_1) -> (text_encoder, tokenizer)

* more clean up

* more refactor

* build pr docs

* Update docs/source/en/api/pipelines/audioldm2.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* small clean

* tidy conversion

* update for large checkpoint

* generate -> generate_language_model

* full clap model

* shrink clap-audio in tests

* fix large integration test

* fix fast tests

* use generation config

* make style

* update docs

* finish docs

* finish doc

* update tests

* fix last test

* syntax

* finalise tests

* refactor projection model in prep for TTS

* fix fast tests

* style

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

* Impl tae slicing and tiling

* add tae tiling test

* add parameterized test

* formatted code

* fix failed test

* style docs

* make safetensors default

* set default save method as safetensors

* update tests

* update to support saving safetensors

* update test to account for safetensors default

* update example tests to use safetensors

* update example to support safetensors

* update unet tests for safetensors

* fix failing loader tests

* fix qc issues

* fix pipeline tests

* fix example test

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

* Support higher dimension LoRAs

* add: tests

* fix: assertion values.

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

* Add GLIGEN implementation

* GLIGEN: Fix code quality check failures

* GLIGEN: Fix Import block un-sorted or un-formatted failures

* GLIGEN: Fix check_repository_consistency failures

* GLIGEN: Add 'PositionNet' to versatile_diffusion/modeling_text_unet.py

* GLIGEN: check_repository_consistency: fix 'copy does not match' error

* GLIGEN: Fix review comments (1)

* GLIGEN: Fix E721 Do not compare types, use `isinstance()` failures

* GLIGEN : Ensure _encode_prompt() copy matches to StableDiffusionPipeline

* GLIGEN: Fix ruff E721 failure in unidiffuser/test_unidiffuser.py

* GLIGEN: doc_builder: restyle pipeline_stable_diffusion_gligen.py

* GIGLEN: reset files unrelated to gligen

* GLIGEN: Fix documentation comments (1)

* GLIGEN: Fix review comments (2)

* GLIGEN: Added FastTest

* GLIGEN: Fix review comments (3)

[Pipeline utils] feat: implement push_to_hub for standalone models, schedulers as well as pipelines (#4128)

* feat: implement push_to_hub for standalone models.

* address PR feedback.

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

* remove max_shard_size.

* add: support for scheduler push_to_hub

* enable push_to_hub support for flax schedulers.

* enable push_to_hub for pipelines.

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

* reflect pr feedback.

* address another round of deedback.

* better handling of kwargs.

* add: tests

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

* setting hub staging to False for now.

* incorporate staging test as a separate job.
Co-authored-by: ydshieh <2521628+ydshieh@users.noreply.github.com>

* fix: tokenizer loading.

* fix: json dumping.

* move is_staging_test to a better location.

* better treatment to tokens.

* define repo_id to better handle concurrency

* style

* explicitly set token

* Empty-Commit

* move SUER, TOKEN to test

* collate org_repo_id

* delete repo

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: ydshieh <2521628+ydshieh@users.noreply.github.com>

* [WIP] Remove code snippets containing `is_safetensors_available()`

* Modifying `import_utils.py`

* update pipeline tests for safetensor default

* fix test related to cached requests

* address import nits

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

* grad checkpointing

* fix make fix-copies

* fix

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

* correct

* correct blocks

* finish

* finish

* finish

* Apply suggestions from code review

* fix

* up

* up

* up

* Update examples/dreambooth/README_sdxl.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Apply suggestions from code review

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

* add: model implementation of tiny autoencoder.

* add: inits.

* push the latest devs.

* add: conversion script and finish.

* add: scaling factor args.

* debugging

* fix denormalization.

* fix: positional argument.

* handle use_torch_2_0_or_xformers.

* handle post_quant_conv

* handle dtype

* fix: sdxl image processor for tiny ae.

* fix: sdxl image processor for tiny ae.

* unify upcasting logic.

* copied from madness.

* remove trailing whitespace.

* set is_tiny_vae = False

* address PR comments.

* change to AutoencoderTiny

* make act_fn an str throughout

* fix: apply_forward_hook decorator call

* get rid of the special is_tiny_vae flag.

* directly scale the output.

* fix dummies?

* fix: act_fn.

* get rid of the Clamp() layer.

* bring back copied from.

* movement of the blocks to appropriate modules.

* add: docstrings to AutoencoderTiny

* add: documentation.

* changes to the conversion script.

* add doc entry.

* settle tests.

* style

* add one slow test.

* fix

* fix 2

* fix 2

* fix: 4

* fix: 5

* finish integration tests

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

* style

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

Update unet_1d.py

highlighting the way the modules are actually fed in the main code as the order matters because no skip block attaches time embeds whilst others do not

* sdxl lora changes.

* better name replacement.

* better replacement.

* debugging

* debugging

* debugging

* debugging

* debugging

* remove print.

* print state dict keys.

* print

* distingisuih better

* debuggable.

* fxi: tyests

* fix: arg from training script.

* access from class.

* run style

* debug

* save intermediate

* some simplifications for SDXL LoRA

* styling

* unet config is not needed in diffusers format.

* fix: dynamic SGM block mapping for SDXL kohya loras (#4322)

* Use lora compatible layers for linear proj_in/proj_out (#4323)

* improve condition for using the sgm_diffusers mapping

* informative comment.

* load compatible keys and embedding layer maaping.

* Get SDXL 1.0 example lora to load

* simplify

* specif ranks and hidden sizes.

* better handling of k rank and hidden

* debug

* debug

* debug

* debug

* debug

* fix: alpha keys

* add check for handling LoRAAttnAddedKVProcessor

* sanity comment

* modifications for text encoder SDXL

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* denugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* up

* up

* up

* up

* up

* up

* unneeded comments.

* unneeded comments.

* kwargs for the other attention processors.

* kwargs for the other attention processors.

* debugging

* debugging

* debugging

* debugging

* improve

* debugging

* debugging

* more print

* Fix alphas

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* clean up

* clean up.

* debugging

* fix: text

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Batuhan Taskaya <batuhan@python.org>

* fix torch compile

* Fix all

* make style

* 0.20.0dev0

* make style