GitLab

* fix xformers lora

* improve

* fix

PEFT Integration for Text Encoder to handle multiple alphas/ranks, disable/enable adapters and support for multiple adapters (#5147)

* more fixes

* up

* up

* style

* add in setup

* oops

* more changes

* v1 rzfactor CI

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

* few todos

* protect torch import

* style

* fix fuse text encoder

* Update src/diffusers/loaders.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* replace with `recurse_replace_peft_layers`

* keep old modules for BC

* adjustments on `adjust_lora_scale_text_encoder`

* nit

* move tests

* add conversion utils

* remove unneeded methods

* use class method instead

* oops

* use `base_version`

* fix examples

* fix CI

* fix weird error with python 3.8

* fix

* better fix

* style

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

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

* add comment

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* conv2d support for recurse remove

* added docstrings

* more docstring

* add deprecate

* revert

* try to fix merge conflicts

* peft integration features for text encoder

1. support multiple rank/alpha values
2. support multiple active adapters
3. support disabling and enabling adapters

* fix bug

* fix code quality

* Apply suggestions from code review
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* fix bugs

* Apply suggestions from code review
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* address comments
Co-Authored-By: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* fix code quality

* address comments

* address comments

* Apply suggestions from code review

* find and replace

---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

* split_head_dim flax attn

* Make split_head_dim non default

* make style and make quality

* add description for split_head_dim flag

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

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

* fix SDXL flax init

* finish

* Fix

* Fix FullAdapterXL.total_downscale_factor.

* Fix incorrect error message in T2IAdapter.__init__(...).

* Move IP-Adapter test_total_downscale_factor(...) to pipeline test file (requested in code review).

* Add more info to error message about an unsupported T2I-Adapter adapter_type.

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

* [Doc builder] Ensure slow import for doc builder

* Apply suggestions from code review

* env for doc builder

* fix more

* [Diffusers] Set import to slow as env variable

* fix docs

* fix docs

* Apply suggestions from code review

* Apply suggestions from code review

* fix docs

* fix docs

* support transformer_layers_per block in flax UNet

* add support for text_time additional embeddings to Flax UNet

* rename attention layers for VAE

* add shape asserts when renaming attention layers

* transpose VAE attention layers

* add pipeline flax SDXL code [WIP]

* continue add pipeline flax SDXL code [WIP]

* cleanup

* Working on JIT support

Fixed prompt embedding shapes so they work in parallel mode. Assuming we
always have both text encoders for now, for simplicity.

* Fixing embeddings (untested)

* Remove spurious line

* Shard guidance_scale when jitting.

* Decode images

* Fix sharding

* style

* Refiner UNet can be loaded.

* Refiner / img2img pipeline

* Allow latent outputs from base and latent inputs in refiner

This makes it possible to chain base + refiner without having to use the
vae decoder in the base model, the vae encoder in the refiner, skipping
conversions to/from PIL, and avoiding TPU <-> CPU memory copies.

* Adapt to FlaxCLIPTextModelOutput

* Update Flax XL pipeline to FlaxCLIPTextModelOutput

* make fix-copies

* make style

* add euler scheduler

* Fix import

* Fix copies, comment unused code.

* Fix SDXL Flax imports

* Fix euler discrete begin

* improve init import

* finish

* put discrete euler in init

* fix flax euler

* Fix more

* make style

* correct init

* correct init

* Temporarily remove FlaxStableDiffusionXLImg2ImgPipeline

* correct pipelines

* finish

---------
Co-authored-by: Martin Müller <martin.muller.me@gmail.com>
Co-authored-by: patil-suraj <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* more fixes

* up

* up

* style

* add in setup

* oops

* more changes

* v1 rzfactor CI

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

* few todos

* protect torch import

* style

* fix fuse text encoder

* Update src/diffusers/loaders.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* replace with `recurse_replace_peft_layers`

* keep old modules for BC

* adjustments on `adjust_lora_scale_text_encoder`

* nit

* move tests

* add conversion utils

* remove unneeded methods

* use class method instead

* oops

* use `base_version`

* fix examples

* fix CI

* fix weird error with python 3.8

* fix

* better fix

* style

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

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

* add comment

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* conv2d support for recurse remove

* added docstrings

* more docstring

* add deprecate

* revert

* try to fix merge conflicts

* v1 tests

* add new decorator

* add saving utilities test

* adapt tests a bit

* add save / from_pretrained tests

* add saving tests

* add scale tests

* fix deps tests

* fix lora CI

* fix tests

* add comment

* fix

* style

* add slow tests

* slow tests pass

* style

* Update src/diffusers/utils/import_utils.py
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

* circumvents pattern finding issue

* left a todo

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

* update hub path

* add lora workflow

* fix

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

* better condition.

* debugging

* how about now?

* how about now?

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* debugging

* support for lycoris.

* style

* add: lycoris test

* fix from_pretrained call.

* fix assertion values.

* 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

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