GitLab

* fixes to tests

* fixture

* fixes

* fix the Positinoal Embedding bug in 2K model;

* Change the default model to the BF16 one for more stable training and output

* make style

* substract buffer size

* add compute_module_persistent_sizes

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

* Flux IP-Adapter

* test cfg

* make style

* temp remove copied from

* fix test

* fix test

* v2

* fix

* make style

* temp remove copied from

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Move encoder_hid_proj to inside FluxTransformer2DModel

* merge

* separate encode_prompt, add copied from, image_encoder offload

* make

* fix test

* fix

* Update src/diffusers/pipelines/flux/pipeline_flux.py

* test_flux_prompt_embeds change not needed

* true_cfg -> true_cfg_scale

* fix merge conflict

* test_flux_ip_adapter_inference

* add fast test

* FluxIPAdapterMixin not test mixin

* Update pipeline_flux.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

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

* Port UNet2DModel gradient checkpointing code from #6718.


---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Vincent Neemie <92559302+VincentNeemie@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: hlky <hlky@hlky.ac>

* update

* udpate

* fix test

* copy transformer

* copy vae

* copy pipeline

* make fix-copies

* refactor; make original code work with diffusers; test latents for comparison generated with this commit

* move rope into pipeline; remove flash attention; refactor

* begin conversion script

* make style

* refactor attention

* refactor

* refactor final layer

* their mlp -> our feedforward

* make style

* add docs

* refactor layer names

* refactor modulation

* cleanup

* refactor norms

* refactor activations

* refactor single blocks attention

* refactor attention processor

* make style

* cleanup a bit

* refactor double transformer block attention

* update mochi attn proc

* use diffusers attention implementation in all modules; checkpoint for all values matching original

* remove helper functions in vae

* refactor upsample

* refactor causal conv

* refactor resnet

* refactor

* refactor

* refactor

* grad checkpointing

* autoencoder test

* fix scaling factor

* refactor clip

* refactor llama text encoding

* add coauthor
Co-Authored-By: "Gregory D. Hunkins" <greg@ollano.com>

* refactor rope; diff: 0.14990234375; reason and fix: create rope grid on cpu and move to device

Note: The following line diverges from original behaviour. We create the grid on the device, whereas
original implementation creates it on CPU and then moves it to device. This results in numerical
differences in layerwise debugging outputs, but visually it is the same.

* use diffusers timesteps embedding; diff: 0.10205078125

* rename

* convert

* update

* add tests for transformer

* add pipeline tests; text encoder 2 is not optional

* fix attention implementation for torch

* add example

* update docs

* update docs

* apply suggestions from review

* refactor vae

* update

* Apply suggestions from code review
Co-authored-by: hlky <hlky@hlky.ac>

* Update src/diffusers/pipelines/hunyuan_video/pipeline_hunyuan_video.py
Co-authored-by: hlky <hlky@hlky.ac>

* Update src/diffusers/pipelines/hunyuan_video/pipeline_hunyuan_video.py
Co-authored-by: hlky <hlky@hlky.ac>

* make fix-copies

* update

---------
Co-authored-by: "Gregory D. Hunkins" <greg@ollano.com>
Co-authored-by: hlky <hlky@hlky.ac>

[Sana] Add Sana, including `SanaPipeline`, `SanaPAGPipeline`, `LinearAttentionProcessor`, `Flow-based DPM-sovler` and so on. (#9982)

* 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

* 1. add DCAE into diffusers;
2. make style and make quality;

* add DCAE_HF into diffusers;

* bug fixed;

* add SanaPipeline, SanaTransformer2D into diffusers;

* add sanaLinearAttnProcessor2_0;

* first update for SanaTransformer;

* first update for SanaPipeline;

* first success run SanaPipeline;

* model output finally match with original model with the same intput;

* code update;

* code update;

* add a flow dpm-solver scripts

* 🎉[important update]
1. Integrate flow-dpm-sovler into diffusers;
2. finally run successfully on both `FlowMatchEulerDiscreteScheduler` and `FlowDPMSolverMultistepScheduler`;

* 🎉🔧

[important update & fix huge bugs!!]
1. add SanaPAGPipeline & several related Sana linear attention operators;
2. `SanaTransformer2DModel` not supports multi-resolution input;
2. fix the multi-scale HW bugs in SanaPipeline and SanaPAGPipeline;
3. fix the flow-dpm-solver set_timestep() init `model_output` and `lower_order_nums` bugs;

* remove prints;

* add convert sana official checkpoint to diffusers format Safetensor.

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

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

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

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

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

* update Sana for DC-AE's recent commit;

* make style && make quality

* Add StableDiffusion3PAGImg2Img Pipeline + Fix SD3 Unconditional PAG (#9932)

* fix progress bar updates in SD 1.5 PAG Img2Img pipeline

---------
Co-authored-by: Vinh H. Pham <phamvinh257@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* make the vae can be None in `__init__` of `SanaPipeline`

* Update src/diffusers/models/transformers/sana_transformer_2d.py
Co-authored-by: hlky <hlky@hlky.ac>

* change the ae related code due to the latest update of DCAE branch;

* change the ae related code due to the latest update of DCAE branch;

* 1. change code based on AutoencoderDC;
2. fix the bug of new GLUMBConv;
3. run success;

* update for solving conversation.

* 1. fix bugs and run convert script success;
2. Downloading ckpt from hub automatically;

* make style && make quality;

* 1. remove un-unsed parameters in init;
2. code update;

* remove test file

* refactor; add docs; add tests; update conversion script

* make style

* make fix-copies

* refactor

* udpate pipelines

* pag tests and refactor

* remove sana pag conversion script

* handle weight casting in conversion script

* update conversion script

* add a processor

* 1. add bf16 pth file path;
2. add complex human instruct in pipeline;

* fix fast \tests

* change gemma-2-2b-it ckpt to a non-gated repo;

* fix the pth path bug in conversion script;

* change grad ckpt to original; make style

* fix the complex_human_instruct bug and typo;

* remove dpmsolver flow scheduler

* apply review suggestions

* change the `FlowMatchEulerDiscreteScheduler` to default `DPMSolverMultistepScheduler` with flow matching scheduler.

* fix the tokenizer.padding_side='right' bug;

* update docs

* make fix-copies

* fix imports

* fix docs

* add integration test

* update docs

* update examples

* fix convert_model_output in schedulers

* fix failing tests

---------
Co-authored-by: Junyu Chen <chenjydl2003@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@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>
Co-authored-by: hlky <hlky@hlky.ac>

* transformer

* make style & make fix-copies

* transformer

* add transformer tests

* 80% vae

* make style

* make fix-copies

* fix

* undo cogvideox changes

* update

* update

* match vae

* add docs

* t2v pipeline working; scheduler needs to be checked

* docs

* add pipeline test

* update

* update

* make fix-copies

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

* update

* copy t2v to i2v pipeline

* update

* apply review suggestions

* update

* make style

* remove framewise encoding/decoding

* pack/unpack latents

* image2video

* update

* make fix-copies

* update

* update

* rope scale fix

* debug layerwise code

* remove debug

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* propagate precision changes to i2v pipeline

* remove downcast

* address review comments

* fix comment

* address review comments

* [Single File] LTX support for loading original weights (#10135)

* from original file mixin for ltx

* undo config mapping fn changes

* update

* add single file to pipelines

* update docs

* Update src/diffusers/models/autoencoders/autoencoder_kl_ltx.py

* Update src/diffusers/models/autoencoders/autoencoder_kl_ltx.py

* rename classes based on ltx review

* point to original repository for inference

* make style

* resolve conflicts correctly

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

* Add support for XFormers in SD3

* sd3 xformers test

* sd3 xformers quality

* sd3 xformers update

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

depcrecate save_attn_procs().

* 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>

* add: autoencoderkl tests

* autoencodertiny.

* fix

* asymmetric autoencoder.

* more

* integration tests for stable audio decoder.

* consistency decoder vae tests

* remove grad check from consistency decoder.

* cog

* bye test_models_vae.py

* fix

* fix

* remove allegro

* fixes

* fixes

* fixes

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

* fix: missing AutoencoderKL lora adapter

* fix

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

* add skip_layers argument to SD3 transformer model class

* add unit test for skip_layers in stable diffusion 3

* sd3: pipeline should support skip layer guidance

* up

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

* feat: save_lora_adapter.

* CogVideoX1_1PatchEmbed test

* 1360 * 768

* refactor

* make style

* update docs

* add modeling tests for cogvideox 1.5

* update

* make fix-copies

* add ofs embed(for convert)

* add ofs embed(for convert)

* more resolution for cogvideox1.5-5b-i2v

* use even number of latent frames only

* update pipeline implementations

* make style

* set patch_size_t as None by default

* #skip frames 0

* refactor

* make style

* update docs

* fix ofs_embed

* update docs

* invert_scale_latents

* update

* fix

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

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

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

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

* Update src/diffusers/models/transformers/cogvideox_transformer_3d.py

* update conversion script

* remove copied from

* fix test

* Update docs/source/en/api/pipelines/cogvideox.md

* Update docs/source/en/api/pipelines/cogvideox.md

* Update docs/source/en/api/pipelines/cogvideox.md

* Update docs/source/en/api/pipelines/cogvideox.md

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

* 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>

* check.

* fixes

* fixes

* updates

* fixes

* fixes

* 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>

* update some docs and tests!

---------
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: apolinário <joaopaulo.passos@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>

* Support bfloat16 for Upsample2D

* Add test and use is_torch_version

* Resolve comments and add decorator

* Simplify require_torch_version_greater_equal decorator

* Run make style

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

* fix variant-idenitification.

* fix variant

* fix sharded variant checkpoint loading.

* Apply suggestions from code review

* fixes.

* more fixes.

* remove print.

* fixes

* fixes

* comments

* fixes

* apply suggestions.

* hub_utils.py

* fix test

* updates

* fixes

* fixes

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* updates.

* removep patch file.

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

* update sd15 repo

* update more

* check if default attn procs fix it.

* print

* print

* replace

* style./

* replace revision with variant.

* replace with stable-diffusion-v1-5/stable-diffusion-inpainting.

* replace with stable-diffusion-v1-5/stable-diffusion-v1-5.

* fix

* update

* update

* update

* update

* update

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

* enabel on xpu

* fix style

* remove 2 shapes from SDFunctionTesterMixin::test_vae_tiling

* combine freeu enable/disable test to reduce many inference runs

* remove low signal unet test for signature

* remove low signal embeddings test

* remove low signal progress bar test from PipelineTesterMixin

* combine ip-adapter single and multi tests to save many inferences

* fix broken tests

* Update tests/pipelines/test_pipelines_common.py

* Update tests/pipelines/test_pipelines_common.py

* add progress bar tests

* update

* update

* update

* update

update

* 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

* undo memory optimization changes

* update docstrings

* fix tests

* fix pia tests

* apply suggestions from review

* add tests

* update comment

* refactor rotary embeds

* adding jsmidt as co-author of this PR for https://github.com/huggingface/diffusers/pull/9133



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

* update

* update

* update

* update

* Added test suite for lumina

* Fixed failing tests

* Improved code quality

* Added function docstrings

* Improved formatting

* feat: support sharding for flux.

* tests

* refactor context parallel cache; update torch compile time benchmark

* add tiling support

* make style

* remove num_frames % 8 == 0 requirement

* update default num_frames to original value

* add explanations + refactor

* update torch compile example

* update docs

* update

* clean up if-statements

* address review comments

* add test for vae tiling

* update docs

* update docs

* update docstrings

* add modeling test for cogvideox transformer

* make style

* Fix loading sharded checkpoint when we have variant

* add test

* remote print

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

* add hunyuan model test

* apply suggestions

* reduce dims further

* reduce dims further

* run make style

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

* add LatteTransformer3DModel model test

* change patch_size to 1

* reduce req len

* reduce channel dims

* increase num_layers

* reduce dims further

* run make style

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>