GitLab

* ControlNetUnion model

* 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

---------
Co-authored-by: Junyu Chen <chenjydl2003@gmail.com>
Co-authored-by: YiYi Xu <yixu310@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>

* fix

* update

* udpate

* update transformer

* make style

* fix

* add conversion script

* update

* fix

* update

* fix

* update

* fixes

* make style

* update

* update

* update

* init

* update

* update

* add

* up

* up

* up

* update

* mochi transformer

* remove original implementation

* make style

* update inits

* update conversion script

* docs

* Update src/diffusers/pipelines/mochi/pipeline_mochi.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update src/diffusers/pipelines/mochi/pipeline_mochi.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* fix docs

* pipeline fixes

* make style

* invert sigmas in scheduler; fix pipeline

* fix pipeline num_frames

* flip proj and gate in swiglu

* make style

* fix

* make style

* fix tests

* latent mean and std fix

* update

* cherry-pick 1069d210e1b9e84a366cdc7a13965626ea258178

* remove additional sigma already handled by flow match scheduler

* fix

* remove hardcoded value

* replace conv1x1 with linear

* Update src/diffusers/pipelines/mochi/pipeline_mochi.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* framewise decoding and conv_cache

* make style

* Apply suggestions from code review

* mochi vae encoder changes

* rebase correctly

* Update scripts/convert_mochi_to_diffusers.py

* fix tests

* fixes

* make style

* update

* make style

* update

* add framewise and tiled encoding

* make style

* make original vae implementation behaviour the default; note: framewise encoding does not work

* remove framewise encoding implementation due to presence of attn layers

* fight test 1

* fight test 2

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail.com>

* update

* refactor transformer part 1

* refactor part 2

* refactor part 3

* make style

* refactor part 4; modeling tests

* make style

* refactor part 5

* refactor part 6

* gradient checkpointing

* pipeline tests (broken atm)

* update

* add coauthor
Co-Authored-By: Huan Yang <hyang@fastmail.com>

* refactor part 7

* add docs

* make style

* add coauthor
Co-Authored-By: YiYi Xu <yixu310@gmail.com>

* make fix-copies

* undo unrelated change

* revert changes to embeddings, normalization, transformer

* refactor part 8

* make style

* refactor part 9

* make style

* fix

* apply suggestions from review

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

* update example

* remove attention mask for self-attention

* update

* copied from

* update

* update

---------
Co-authored-by: Huan Yang <hyang@fastmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* quantization config.

* fix-copies

* fix

* modules_to_not_convert

* add bitsandbytes utilities.

* make progress.

* fixes

* quality

* up

* up

rotary embedding refactor 2: update comments, fix dtype for use_real=False (#9312)

fix notes and dtype

up

up

* minor

* up

* up

* fix

* provide credits where due.

* make configurations work.

* fixes

* fix

* update_missing_keys

* fix

* fix

* make it work.

* fix

* provide credits to transformers.

* empty commit

* handle to() better.

* tests

* change to bnb from bitsandbytes

* fix tests

fix slow quality tests

SD3 remark

fix

complete int4 tests

add a readme to the test files.

add model cpu offload tests

warning test

* better safeguard.

* change merging status

* courtesy to transformers.

* move  upper.

* better

* make the unused kwargs warning friendlier.

* harmonize changes with https://github.com/huggingface/transformers/pull/33122



* style

* trainin tests

* feedback part i.

* Add Flux inpainting and Flux Img2Img (#9135)

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

Update `UNet2DConditionModel`'s error messages (#9230)

* refactor

[CI] Update Single file Nightly Tests (#9357)

* update

* update

feedback.

improve README for flux dreambooth lora (#9290)

* improve readme

* improve readme

* improve readme

* improve readme

fix one uncaught deprecation warning for accessing vae_latent_channels in VaeImagePreprocessor (#9372)

deprecation warning vae_latent_channels

add mixed int8 tests and more tests to nf4.

[core] Freenoise memory improvements (#9262)

* update

* implement prompt interpolation

* make style

* resnet memory optimizations

* more memory optimizations; todo: refactor

* update

* update animatediff controlnet with latest changes

* refactor chunked inference changes

* remove print statements

* update

* chunk -> split

* remove changes from incorrect conflict resolution

* remove changes from incorrect conflict resolution

* add explanation of SplitInferenceModule

* update docs

* Revert "update docs"

This reverts commit c55a50a271b2cefa8fe340a4f2a3ab9b9d374ec0.

* update docstring for freenoise split inference

* apply suggestions from review

* add tests

* apply suggestions from review

quantization docs.

docs.

* Revert "Add Flux inpainting and Flux Img2Img (#9135)"

This reverts commit 5799954dd4b3d753c7c1b8d722941350fe4f62ca.

* tests

* don

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

* contribution guide.

* changes

* empty

* fix tests

* harmonize with https://github.com/huggingface/transformers/pull/33546

.

* numpy_cosine_distance

* config_dict modification.

* remove if config comment.

* note for load_state_dict changes.

* float8 check.

* quantizer.

* raise an error for non-True low_cpu_mem_usage values when using quant.

* low_cpu_mem_usage shenanigans when using fp32 modules.

* don't re-assign _pre_quantization_type.

* make comments clear.

* remove comments.

* handle mixed types better when moving to cpu.

* add tests to check if we're throwing warning rightly.

* better check.

* fix 8bit test_quality.

* handle dtype more robustly.

* better message when keep_in_fp32_modules.

* handle dtype casting.

* fix dtype checks in pipeline.

* fix warning message.

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

* mitigate the confusing cpu warning

---------
Co-authored-by: Vishnu V Jaddipal <95531133+Gothos@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* merge 9588

* max_shard_size="5GB" for colab running

* conversion script updates; modeling test; refactor transformer

* make fix-copies

* Update convert_cogview3_to_diffusers.py

* initial pipeline draft

* make style

* fight bugs 🐛

🪳

* add example

* add tests; refactor

* make style

* make fix-copies

* add co-author

YiYi Xu <yixu310@gmail.com>

* remove files

* add docs

* add co-author
Co-Authored-By: YiYi Xu <yixu310@gmail.com>

* fight docs

* address reviews

* make style

* make model work

* remove qkv fusion

* remove qkv fusion tets

* address review comments

* fix make fix-copies error

* remove None and TODO

* for FP16(draft)

* make style

* remove dynamic cfg

* remove pooled_projection_dim as a parameter

* fix tests

---------
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

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

* cnt model

* cnt model

* cnt model

* fix Loader "Copied"

* format

* txt_ids for  multiple images

* add test and format

* typo

* Update pipeline_flux_controlnet.py

* remove

* make quality

* fix copy

* Update src/diffusers/pipelines/flux/pipeline_flux_controlnet.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update src/diffusers/pipelines/flux/pipeline_flux_controlnet.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update src/diffusers/pipelines/flux/pipeline_flux_controlnet.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update src/diffusers/pipelines/flux/pipeline_flux_controlnet.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update src/diffusers/models/controlnet_flux.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* fix

* make copies

* test

* bs

---------
Co-authored-by: haofanwang <haofanwang.ai@gmail.com>
Co-authored-by: haofanwang <haofan@HaofandeMBP.lan>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* add CogVideoX

---------
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

add flux!
Signed-off-by: Adrien <adrien@huggingface.co>
Co-authored-by: Adrien <adrien.69740@gmail.com>
Co-authored-by: Anatoly Belikov <abelikov@singularitynet.io>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail.com>

* WIP modeling code and pipeline

* add custom attention processor + custom activation + add to init

* correct ProjectionModel forward

* add stable audio to __initèè

* add autoencoder and update pipeline and modeling code

* add half Rope

* add partial rotary v2

* add temporary modfis to scheduler

* add EDM DPM Solver

* remove TODOs

* clean GLU

* remove att.group_norm to attn processor

* revert back src/diffusers/schedulers/scheduling_dpmsolver_multistep.py

* refactor GLU -> SwiGLU

* remove redundant args

* add channel multiples in autoencoder docstrings

* changes in docsrtings and copyright headers

* clean pipeline

* further cleaning

* remove peft and lora and fromoriginalmodel

* Delete src/diffusers/pipelines/stable_audio/diffusers.code-workspace

* make style

* dummy models

* fix copied from

* add fast oobleck tests

* add brownian tree

* oobleck autoencoder slow tests

* remove TODO

* fast stable audio pipeline tests

* add slow tests

* make style

* add first version of docs

* wrap is_torchsde_available to the scheduler

* fix slow test

* test with input waveform

* add input waveform

* remove some todos

* create stableaudio gaussian projection + make style

* add pipeline to toctree

* fix copied from

* make quality

* refactor timestep_features->time_proj

* refactor joint_attention_kwargs->cross_attention_kwargs

* remove forward_chunk

* move StableAudioDitModel to transformers folder

* correct convert + remove partial rotary embed

* apply suggestions from yiyixuxu -> removing attn.kv_heads

* remove temb

* remove cross_attention_kwargs

* further removal of cross_attention_kwargs

* remove text encoder autocast to fp16

* continue removing autocast

* make style

* refactor how text and audio are embedded

* add paper

* update example code

* make style

* unify projection model forward + fix device placement

* make style

* remove fuse qkv

* apply suggestions from review

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

* make style

* smaller models in fast tests

* pass sequential offloading fast tests

* add docs for vae and autoencoder

* make style and update example

* remove useless import

* add cosine scheduler

* dummy classes

* cosine scheduler docs

* better description of scheduler

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

* 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 lavender flow transformer

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

* add Latte to diffusers

* remove print

* remove print

* remove print

* remove unuse codes

* remove layer_norm_latte and add a flag

* remove layer_norm_latte and add a flag

* update latte_pipeline

* update latte_pipeline

* remove unuse squeeze

* add norm_hidden_states.ndim == 2: # for Latte

* fixed test latte pipeline bugs

* fixed test latte pipeline bugs

* delete sh

* add doc for latte

* add licensing

* Move Transformer3DModelOutput to modeling_outputs

* give a default value to sample_size

* remove the einops dependency

* change norm2 for latte

* modify pipeline of latte

* update test for Latte

* modify some codes for latte

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* modify for Latte pipeline

* video_length -> num_frames; update prepare_latents copied from

* make fix-copies

* make style

* typo: videe -> video

* update

* modify for Latte pipeline

* modify latte pipeline

* modify latte pipeline

* modify latte pipeline

* modify latte pipeline

* modify for Latte pipeline

* Delete .vscode directory

* make style

* make fix-copies

* add latte transformer 3d to docs _toctree.yml

* update example

* reduce frames for test

* fixed bug of _text_preprocessing

* set num frame to 1 for testing

* remove unuse print

* add text = self._clean_caption(text) again

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>

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

* add controlnet support

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

* sd3 controlnet



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

* 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>

* Hunyuan Team: add HunyuanDiT related updates


---------
Co-authored-by: XCLiu <liuxc1996@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail.com>

* init for patches

* finish patched model.

* continuous transformer

* vectorized transformer2d.

* style.

* inits.

* fix-copies.

* introduce DiTTransformer2DModel.

* fixes

* use REMAPPING as suggested by @DN6

* better logging.

* add pixart transformer model.

* inits.

* caption_channels.

* attention masking.

* fix use_additional_conditions.

* remove print.

* debug

* flatten

* fix: assertion for sigma

* handle remapping for modeling_utils

* add tests for dit transformer2d

* quality

* placeholder for pixart tests

* pixart tests

* add _no_split_modules

* add docs.

* check

* check

* check

* check

* fix tests

* fix tests

* move Transformer output to modeling_output

* move errors better and bring back use_additional_conditions attribute.

* add unnecessary things from DiT.

* clean up pixart

* fix remapping

* fix device_map things in pixart2d.

* replace Transformer2DModel with appropriate classes in dit, pixart tests

* empty

* legacy mixin classes./

* use a remapping dict for fetching class names.

* change to specifc model types in the pipeline implementations.

* move _fetch_remapped_cls_from_config to modeling_loading_utils.py

* fix dependency problems.

* add deprecation note.

* 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>

* add: support TCD scheduler


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

* move model helper function in pipeline to EfficiencyMixin

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

* add DPM scheduler with EDM formulation

* set sigmas in init

* add _compute_sigmas

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* address some review comments

* up,

* add tests

---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Add EDMEulerScheduler

* address review comments

* fix import

* fix test

* add tests

* add co-author

Co-authored-by:  @dg845 dgu8957@gmail.com

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* add Sa-Solver



---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: scxue <xueshuchen17@mails.ucas.edu.cn>
Co-authored-by: jschen <chenjunsong4@h-partners.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* update

* update

* update

* update

* update

* make style

* remove docs

* update

* move to research folder.

* fix-copies

* remove _toctree entry.

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

amused

rename

Update docs/source/en/api/pipelines/amused.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

AdaLayerNormContinuous default values

custom micro conditioning

micro conditioning docs

put lookup from codebook in constructor

fix conversion script

remove manual fused flash attn kernel

add training script

temp remove training script

add dummy gradient checkpointing func

clarify temperatures is an instance variable by setting it

remove additional SkipFF block args

hardcode norm args

rename tests folder

fix paths and samples

fix tests

add training script

training readme

lora saving and loading

non-lora saving/loading

some readme fixes

guards

Update docs/source/en/api/pipelines/amused.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Update examples/amused/README.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Update examples/amused/train_amused.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

vae upcasting

add fp16 integration tests

use tuple for micro cond

copyrights

remove casts

delegate to torch.nn.LayerNorm

move temperature to pipeline call

upsampling/downsampling changes

* Check in 23-10-05

* check-in 23-10-06

* check-in 23-10-07 2pm

* check-in 23-10-08

* check-in 231009T1200

* check-in 230109

* checkin 231010

* init + forward run

* checkin

* checkin

* ControlNetXSModel is now saveable+loadable

* Forward works

* checkin

* Pipeline works with `no_control=True`

* checkin

* debug: save intermediate outputs of resnet

* checkin

* Understood time error + fixed connection error

* checkin

* checkin 231106T1600

* turned off detailled debug prints

* time debug logs

* small fix

* Separated control_scale for connections/time

* simplified debug logging

* Full denoising works with control scale = 0

* aligned logs

* Added control_attention_head_dim param

* Passing n_heads instead of dim_head into ctrl unet

* Fixed ctrl midblock bug

* Cleanup

* Fixed time dtype bug

* checkin

* 1. from_unet, 2. base passed, 3. all unet params

* checkin

* Finished docstrings

* cleanup

* make style

* checkin

* more tests pass

* Fixed tests

* removed debug logs

* make style + quality

* make fix-copies

* fixed documentation

* added cnxs to doc toc

* added control start/end param

* Update controlnetxs_sdxl.md

* tried to fix copies..

* Fixed norm_num_groups in from_unet

* added sdxl-depth test

* created SD2.1 controlnet-xs pipeline

* re-added debug logs

* Adjusting group norm ; readded logs

* Added debug log statements

* removed debug logs ; started tests for sd2.1

* updated sd21 tests

* fixed tests

* fixed tests

* slightly increased error tolerance for 1 test

* make style & quality

* Added docs for CNXS-SD

* make fix-copies

* Fixed sd compile test ; fixed gradient ckpointing

* vae downs = cnxs conditioning downs; removed guess

* make style & quality

* Fixed tests

* fixed test

* Incorporated review feedback

* simplified control model surgery

* fixed tests & make style / quality

* Updated docs; deleted pip & cursor files

* Rolled back minimal change to resnet

* Update resnet.py

* Update resnet.py

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

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

* Incorporated review feedback

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

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

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

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

* Update src/diffusers/models/controlnetxs.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/models/controlnetxs.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/pipelines/controlnet_xs/pipeline_controlnet_xs.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

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

* Update src/diffusers/pipelines/controlnet_xs/pipeline_controlnet_xs_sd_xl.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Incorporated doc feedback

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* 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>

* 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

* consistency decoder

* rename

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

* Update src/diffusers/pipelines/consistency_models/pipeline_consistency_models.py

* uP

* Apply suggestions from code review

* uP

* uP

* uP

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

* draft design

* clean up

* clean up

* clean up

* clean up

* clean up

* clean  up

* clean up

* clean up

* clean up

* update pipeline

* clean up

* clean up

* clean up

* add tests

* change motion block

* clean up

* clean up

* clean up

* update

* update

* update

* update

* update

* update

* update

* update

* clean up

* update

* update

* update model test

* update

* update

* update

* update

* make style

* update

* fix embeddings

* update

* merge upstream

* max fix copies

* fix bug

* fix mistake

* add docs

* update

* clean up

* update

* clean up

* clean up

* fix docstrings

* fix docstrings

* update

* update

* clean  up

* update

* initial commit for LatentConsistencyModelPipeline and LCMScheduler based on the community pipeline

* Add callback and freeu support.

* apply suggestions from review

* Clean up LCMScheduler

* Remove timeindex argument to LCMScheduler.step.

* Add support for clipping or thresholding the predicted original sample.

* Remove unused methods and arguments in LCMScheduler.

* Improve comment about (lack of) negative prompt support.

* Change input guidance_scale to match the StableDiffusionPipeline (Imagen) CFG formulation.

* Move lcm_origin_steps from pipeline __call__ to LCMScheduler.__init__/config (as origin_steps).

* Fix typo when clipping/thresholding in LCMScheduler.

* Add some initial LCMScheduler tests.

* add type annotations from review

* Fix type annotation bug.

* Override test_add_noise_device in LCMSchedulerTest since hardcoded timesteps doesn't work under default settings.

* Add generator argument pipeline prepare_latents call.

* Cast LCMScheduler.timesteps to long in set_timesteps.

* Add onestep and multistep full loop scheduler tests.

* Set default height/width to None and don't hardcode guidance scale embedding dim.

* Add initial LatentConsistencyPipeline fast and slow tests.

* Add initial documentation for LatentConsistencyModelPipeline and LCMScheduler.

* Make remaining failing fast tests pass.

* make style

* Make original_inference_steps configurable from pipeline __call__ again.

* make style

* Remove guidance_rescale arg from pipeline __call__ since LCM currently doesn't support CFG.

* Make LCMScheduler defaults match config of LCM_Dreamshaper_v7 checkpoint.

* Fix LatentConsistencyPipeline slow tests and add dummy expected slices.

* Add checks for original_steps in LCMScheduler.set_timesteps.

* make fix-copies

* Improve LatentConsistencyModelPipeline docs.

* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>

* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>

* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>

* Update src/diffusers/schedulers/scheduling_lcm.py

* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>

* finish

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Aryan V S <avs050602@gmail.com>

* Add BLIP Diffusion skeleton

* Add other model components

* Add BLIP2, need to change it for now

* Fix pipeline imports

* Load pretrained ViT

* Make qformer fwd pass same

* Replicate fwd passes

* Fix device bug

* Add accelerate functions

* Remove extra functions from Blip2

* Minor bug

* Integrate initial review changes

* Refactoring

* Refactoring

* Refactor

* Add controlnet

* Refactor

* Update conversion script

* Add image processor

* Shift postprocessing to ImageProcessor

* Refactor

* Fix device

* Add fast tests

* Update conversion script

* Fix checkpoint conversion script

* Integrate review changes

* Integrate reivew changes

* Remove unused functions from test

* Reuse HF image processor in Cond image

* Create new BlipImageProcessor based on transfomers

* Fix image preprocessor

* Minor

* Minor

* Add canny preprocessing

* Fix controlnet preprocessing

* Fix blip diffusion test

* Add controlnet test

* Add initial doc strings

* Integrate review changes

* Refactor

* Update examples

* Remove DDIM comments

* Add copied from for prepare_latents

* Add type anotations

* Add docstrings

* Do black formatting

* Add batch support

* Make tests pass

* Make controlnet tests pass

* Black formatting

* Fix progress bar

* Fix some licensing comments

* Fix imports

* Refactor controlnet

* Make tests faster

* Edit examples

* Black formatting/Ruff

* Add doc

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

* Move controlnet pipeline

* Make tests faster

* Fix imports

* Fix formatting

* Fix make errors

* Fix make errors

* Minor

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

* Edit docs

* Fix 16 bit loading

* Update examples

* Edit toctree

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

* Minor

* Add tips

* Edit examples

* Update model paths

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

* 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>