GitLab

* 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>

* update

* update

* update

* add stable cascade unet doc.

* fix path

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 pipeline docs for latte

* add inference time to latte docs

* apply review suggestions

* add pipeline documentation.

* add api spec for pipeline

* model documentation

* model spec

* initial draft

* 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>

* add docs on model sharding

* add entry to _toctree.

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

* simplify wording

* add a note on transformer library handling

* move device placement section

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

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

* first draft


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

* 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>

minor docs changes in hunyuandit

* Update transformer2d.md title

For the other classes (e.g., UNet2DModel) the title of the documentation coincides with the name of the class, but that was not the case for Transformer2DModel.

* Update model docs titles for consistency with class names

* add hunyuandit doc

* update hunyuandit doc

* update hunyuandit 2d model

* update toctree.yml for hunyuandit

* 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.

* files and formats

* fix callout

* feedback

* code sample

* feedback

* first draft

* edits

* noise schedule

* sigmas and zero snr

* feedback

* feedback

* implement marigold depth and normals pipelines in diffusers core

* remove bibtex

* remove deprecations

* remove save_memory argument

* remove validate_vae

* remove config output

* remove batch_size autodetection

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

* remove no_grad

* add fp16 to the example usage

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

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

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

* style

* rename denoising_steps into num_inference_steps

* rename input_image into image

* rename input_latent into latents

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

* move clean_latent outside of progress_bar

* refactor marigold-reusable image processing bits into MarigoldImageProcessor class

* clean up the usage example docstring

* make ensemble functions members of the pipelines

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

* fix vae_scale_factor computation

* better compatibility with torch.compile
better variable naming

* move export_depth_to_png to export_utils

* remove encode_prediction

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

* do not shortcut vae.config variables

* change all asserts to raise ValueError

* rename output_prediction_type to output_type

* better variable names
clean up variable deletion code

* better variable names

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

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

* fix generator device placement checks

* move encode_empty_text body into the pipeline call

* minor empty text encoding simplifications

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

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

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

* remove forgotten print

* add prediction_type model config

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

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

* fix `output_uncertainty=False`

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

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

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

* minor message improvement

* fix cpu offloading

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

* fix missing comma

* change torch.FloatTensor to torch.Tensor

* fix importing of MarigoldImageProcessor

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

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

* fix num_images computation

* remove MarigoldImageProcessor and outputs from import structure
update tests

* update docstrings

* update init

* update

* style

* fix

* fix

* up

* up

* up

* add simple test

* up

* update expected np input/output to be channel last

* move expand_tensor_or_array into the MarigoldImageProcessor

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

* add basic docs.

* add anton's contribution statement

* remove todos.

* fix assertion values for marigold depth slow tests

* fix assertion values for depth normals.

* remove print

* support AutoencoderTiny in the pipelines

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

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

* [doc] add marigold to pipelines overview

* [doc] add section "usage examples"

* fix an issue with latents check in the pipelines

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

* grammarly

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

* style

* print

* fix the assertions.

* take from the github runner.

* take the slices from action artifacts

* style.

* update with the slices from the runner.

* remove unnecessary code blocks.

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

This reverts commit a505165150afd8dab23c474d1a054ea505a56a5f.

* remove invitation for new modalities

* split out marigold usage examples

* doc cleanup

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

* 1. add doc for PixArtSigmaPipeline;

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

* introduce videoprocessor.

* fix quality

* address yiyi's feedback

* fix preprocess_video call.

* video_processor -> image_processor

* fix

* fix more.

* quality

* image_processor -> video_processor

* support List[List[PIL.Image.Image]]

* change to video_processor.

* documentation

* Apply suggestions from code review

* changes

* remove print.

* refactor video processor (part # 7776) (#7861)

* update

* update remove deprecate

* Update src/diffusers/video_processor.py

* update

* Apply suggestions from code review

* deprecate list of 5d for video and list of 4d for image + apply other feedbacks

* up

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

* add doc.

* tensor2vid -> postprocess_video.

* refactor preprocess with preprocess_video

* set default values.

* empty commit

* more refactoring of prepare_latents in animatediff vid2vid

* checking documentation

* remove documentation for now.

* fix animatediff sdxl

* fix test failure [part of video processor PR] (#7905)

up

* remove preceed_with_frames.

* doc

* fix

* fix

* remove video input as a single-frame video.

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

* combine

* edits

* lcm

* lcm lora

* fix

* fix hfoption

* edits

* community pipelines

* feedback

* consolidate

* refactor

* code snippets

* fix path

* fix path in guide

* code outputs

* align toctree title

* title

* fix title

* reproducibility

* feedback

* feedback

* fix path

* github link

* toctree

* optim

* feedback

* improve overview

* pipelines

* schedulers and models

* community pipelines

* feedback

* Create tgate.md

* Update _toctree.yml

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

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

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

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

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

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

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

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

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

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

* Update tgate.md

* Update tgate.md

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

* CheckIn - created DownSubBlocks

* Added extra channels, implemented subblock fwd

* Fixed connection sizes

* checkin

* Removed iter, next in forward

* Models for SD21 & SDXL run through

* Added back pipelines, cleared up connections

* Cleaned up connection creation

* added debug logs

* updated logs

* logs: added input loading

* Update umer_debug_logger.py

* log: Loading hint

* Update umer_debug_logger.py

* added logs

* Changed debug logging

* debug: added more logs

* Fixed num_norm_groups

* Debug: Logging all of SDXL input

* Update umer_debug_logger.py

* debug: updated logs

* checkim

* Readded tests

* Removed debug logs

* Fixed Slow Tests

* Added value ckecks | Updated model_cpu_offload_seq

* accelerate-offloading works ; fast tests work

* Made unet & addon explicit in controlnet

* Updated slow tests

* Added dtype/device to ControlNetXS

* Filled in test model paths

* Added image_encoder/feature_extractor to XL pipe

* Fixed fast tests

* Added comments and docstrings

* Fixed copies

* Added docs ; Updates slow tests

* Moved changes to UNetMidBlock2DCrossAttn

* tiny cleanups

* Removed stray prints

* Removed ip adapters + freeU

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

* Fixed test_save_load_float16

* Make style, quality, fix-copies

* Changed loading/saving API for ControlNetXS

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

* Removed ControlNet-XS from research examples

* Make style, quality, fix-copies

* Small fixes

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

* checkin May 11 '23

* CheckIn Mar 12 '24

* Fixed tests for SD

* Added tests for UNetControlNetXSModel

* Fixed SDXL tests

* cleanup

* Delete Pipfile

* CheckIn Mar 20

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

* check-in Mar 23

* checkin 24 Mar

* Created init for UNetCnxs and CnxsAddon

* CheckIn

* Made from_modules, from_unet and no_control work

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

* Fixed freezing

* Added gradient ckpt'ing; fixed tests

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

* Don't create UNet in init ; removed class_emb

* Incorporated review feedback

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

* Make style, quality, fix-copies

* Implemented review feedback

* Removed compatibility check for vae/ctrl embedding

* make style, quality, fix-copies

* Delete Pipfile

* Integrated review feedback

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

* Reduced size of test tensors

For this, added `norm_num_groups` as parameter everywhere

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

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

* Fixed save_pretrained/from_pretrained bug

* Removed redundant code

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

* refactor t2i

* add code snippets

* prompt enhance

* edits

* align titles

* feedback

* feedback

* feedback

* link to style

* post-release

* quality

* add edm schedulers in doc

* add in toctree

* address reviewe comments

* add tcd intro

* resolve repos

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

* revise NFEs related

* change inpainting location

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