* 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>
* add test for expanding lora and normal lora error
* Update tests/lora/test_lora_layers_flux.py
* fix things.
* Update src/diffusers/loaders/peft.py
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Add offload option in flux-control training
* Update examples/flux-control/train_control_flux.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* modify help message
* fix format
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Use torch in get_2d_sincos_pos_embed
* Use torch in get_3d_sincos_pos_embed
* get_1d_sincos_pos_embed_from_grid in LatteTransformer3DModel
* deprecate
* move deprecate, make private
* fixed a dtype bfloat16 bug in torch_utils.py
when generating 1024*1024 image with bfloat16 dtype, there is an exception:
File "/opt/conda/lib/python3.10/site-packages/diffusers/utils/torch_utils.py", line 107, in fourier_filter
x_freq = fftn(x, dim=(-2, -1))
RuntimeError: Unsupported dtype BFloat16
* remove whitespace in torch_utils.py
* Update src/diffusers/utils/torch_utils.py
* Update torch_utils.py
---------
Co-authored-by: hlky <hlky@hlky.ac>
