GitLab

* set supports gradient checkpointing to true where necessary; add missing no split modules

* fix cogvideox tests

* update

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

* update

* fix make copies

* update

* add relevant markers to the integration test suite.

* add copied.

* fox-copies

* temporarily add print.

* directly place on CUDA as CPU isn't that big on the CIO.

* fixes to fuse_lora, aryan was right.

* fixes

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

* Add torch_xla and from_single_file to instruct-pix2pix

* StableDiffusionInstructPix2PixPipelineSingleFileSlowTests

* StableDiffusionInstructPix2PixPipelineSingleFileSlowTests

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

* fix: lora unloading when using expanded Flux LoRAs.

* fix argument name.
Co-authored-by: a-r-r-o-w <contact.aryanvs@gmail.com>

* docs.

---------
Co-authored-by: a-r-r-o-w <contact.aryanvs@gmail.com>

add slow and nightly markers to sd3 lora integation.

* IP-Adapter support for `StableDiffusion3ControlNetPipeline`

* Update src/diffusers/pipelines/controlnet_sd3/pipeline_stable_diffusion_3_controlnet.py
Co-authored-by: hlky <hlky@hlky.ac>

---------
Co-authored-by: hlky <hlky@hlky.ac>

* check for base_layer key in transformer state dict

* test_lora_expansion_works_for_absent_keys

* check

* Update tests/lora/test_lora_layers_flux.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* check

* test_lora_expansion_works_for_absent_keys/test_lora_expansion_works_for_extra_keys

* absent->extra

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

* feat: support unload_lora_weights() for Flux Control.

* tighten test

* minor

* updates

* meta device fixes.

* Revert "Add support for sharded models when TorchAO quantization is enabled (#10256)"

This reverts commit 41ba8c0b

.

* update tests

* udpate

* update

* update

* update device map tests

* apply review suggestions

* update

* make style

* fix

* update docs

* update tests

* update workflow

* update

* improve tests

* allclose tolerance

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

* Update tests/quantization/torchao/test_torchao.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* improve tests

* fix

* update correct slices

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

fix bug on xpu

* update

* make style

* update

* update

* update

* make style

* single file related changes

* update

* fix

* update single file urls and docs

* update

* fix

* fixes to tests

* fixture

* fixes

updates

* misc lora test improvements.

* updates

* fixes to tests

* sana lora training tests and misc.

* remove push to hub

* Update examples/dreambooth/train_dreambooth_lora_sana.py
Co-authored-by: Aryan <aryan@huggingface.co>

---------
Co-authored-by: Aryan <aryan@huggingface.co>

refactor

* bump min torchao version to 0.7.0

* update

* 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>

add integration tests for lora expansion stuff in Flux.

* lora expansion with dummy zeros.

* updates

* fix working 🥳

* working.

* use torch.device meta for state dict expansion.

* tests
Co-authored-by: a-r-r-o-w <contact.aryanvs@gmail.com>

* fixes

* fixes

* switch to debug

* fix

* Apply suggestions from code review
Co-authored-by: Aryan <aryan@huggingface.co>

* fix stuff

* docs

---------
Co-authored-by: a-r-r-o-w <contact.aryanvs@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>

* add sharded + device_map check

* Added support for single IPAdapter on SD3.5 pipeline



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

fix

* 1217

* 1217

* 1217

* update

* reverse

* add test

* update test

* make style

* update

* make style

---------
Co-authored-by: Aryan <aryan@huggingface.co>

* Check correct model type is passed to `from_pretrained`

* Flax, skip scheduler

* test_wrong_model

* Fix for scheduler

* Update tests/pipelines/test_pipelines.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* EnumMeta

* Flax

* scheduler in expected types

* make

* type object 'CLIPTokenizer' has no attribute '_PipelineFastTests__name'

* support union

* fix typing in kandinsky

* make

* add LCMScheduler

* 'LCMScheduler' object has no attribute 'sigmas'

* tests for wrong scheduler

* make

* update

* warning

* tests

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

* import FlaxSchedulerMixin

* skip scheduler

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

* update

* udpate

* fix test

remove nullop imports

rename integration test

* flux_control_inpaint - failing test_flux_different_prompts

* removing test_flux_different_prompts?

* fix style

* fix from PR comments

* fix style

* reducing guidance_scale in demo

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

* make

* prepare_latents is not copied from

* update docs

* typos

---------
Co-authored-by: affromero <ubuntu@ip-172-31-17-146.ec2.internal>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: hlky <hlky@hlky.ac>

* feat: lora support for SANA.

* make fix-copies

* rename test class.

* attention_kwargs -> cross_attention_kwargs.

* Revert "attention_kwargs -> cross_attention_kwargs."

This reverts commit 23433bf9bccc12e0f2f55df26bae58a894e8b43b.

* exhaust 119 max line limit

* sana lora fine-tuning script.

* readme

* add a note about the supported models.

* Apply suggestions from code review
Co-authored-by: Aryan <aryan@huggingface.co>

* style

* docs for attention_kwargs.

* remove lora_scale from pag pipeline.

* copy fix

---------
Co-authored-by: Aryan <aryan@huggingface.co>

update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

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

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

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

* update

* update

* update

* update

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

* add lora support for ltx

* add tests

* fix copied from comments

* update

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

* torchao quantizer


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

* 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>