onediff is an out-of-the-box acceleration library for diffusion models, it provides:
onediff is the abbreviation of "one line of code to accelerate diffusion models".
Note that we haven't got a way to run SVD with TensorRT on Feb 29 2024.
We also maintain a repository for benchmarking the quality of generation after acceleration: odeval
Note: You can choose the latest versions you want for diffusers or transformers.
python3 -m pip install "torch" "transformers==4.27.1" "diffusers[torch]==0.19.3"
When considering the choice between OneFlow and Nexfort, either one is optional, and only one is needed.
For DiT structural models or H100 devices, it is recommended to use Nexfort.
For all other cases, it is recommended to use OneFlow. Note that optimizations within OneFlow will gradually transition to Nexfort in the future.
Install Nexfort is Optional. The detailed introduction of Nexfort is here.
python3 -m pip install -U torch==2.3.0 torchvision==0.18.0 torchaudio==2.3.0 torchao==0.1
python3 -m pip install -U nexfort
Install OneFlow is Optional.
NOTE: We have updated OneFlow frequently for onediff, so please install OneFlow by the links below.
CUDA 11.8
For NA/EU users
python3 -m pip install -U --pre oneflow -f https://github.com/siliconflow/oneflow_releases/releases/expanded_assets/community_cu118
For CN users
python3 -m pip install -U --pre oneflow -f https://oneflow-pro.oss-cn-beijing.aliyuncs.com/branch/community/cu118
CUDA 12.1
For NA/EU users
python3 -m pip install -U --pre oneflow -f https://github.com/siliconflow/oneflow_releases/releases/expanded_assets/community_cu121
For CN users
python3 -m pip install -U --pre oneflow -f https://oneflow-pro.oss-cn-beijing.aliyuncs.com/branch/community/cu121
CUDA 12.2
For NA/EU users
python3 -m pip install -U --pre oneflow -f https://github.com/siliconflow/oneflow_releases/releases/expanded_assets/community_cu122
For CN users
python3 -m pip install -U --pre oneflow -f https://oneflow-pro.oss-cn-beijing.aliyuncs.com/branch/community/cu122
python3 -m pip install --pre onediff
git clone https://github.com/siliconflow/onediff.git
cd onediff && python3 -m pip install -e .
Or install for development:
# install for dev
cd onediff && python3 -m pip install -e '.[dev]'
# code formatting and linting
pip3 install pre-commit
pre-commit install
pre-commit run --all-files
NOTE: If you intend to utilize plugins for ComfyUI/StableDiffusion-WebUI, we highly recommend installing OneDiff from the source rather than PyPI. This is necessary as you'll need to manually copy (or create a soft link) for the relevant code into the extension folder of these UIs/Libs.
| Functionality | Details |
|---|---|
| Compiling Time | About 1 minute (SDXL) |
| Deployment Methods | Plug and Play |
| Dynamic Image Size Support | Support with no overhead |
| Model Support | SD1.5~2.1, SDXL, SDXL Turbo, etc. |
| Algorithm Support | SD standard workflow, LoRA, ControlNet, SVD, InstantID, SDXL Lightning, etc. |
| SD Framework Support | ComfyUI, Diffusers, SD-webui |
| Save & Load Accelerated Models | Yes |
| Time of LoRA Switching | Hundreds of milliseconds |
| LoRA Occupancy | Tens of MB to hundreds of MB. |
| Device Support | NVIDIA GPU 3090 RTX/4090 RTX/A100/A800/A10 etc. (Compatibility with Ascend in progress) |
onediff supports the acceleration for SOTA models.
| AIGC Type | Models | HF diffusers | ComfyUI | SD web UI | |||
|---|---|---|---|---|---|---|---|
| Community | Enterprise | Community | Enterprise | Community | Enterprise | ||
| Image | SD 1.5 | stable | stable | stable | stable | stable | stable |
| SD 2.1 | stable | stable | stable | stable | stable | stable | |
| SDXL | stable | stable | stable | stable | stable | stable | |
| LoRA | stable | stable | stable | ||||
| ControlNet | stable | stable | |||||
| SDXL Turbo | stable | stable | |||||
| LCM | stable | stable | |||||
| SDXL DeepCache | alpha | alpha | alpha | alpha | |||
| InstantID | beta | beta | |||||
| Video | SVD(stable Video Diffusion) | stable | stable | stable | stable | ||
| SVD DeepCache | alpha | alpha | alpha | alpha |
Compile and save the compiled result offline, then load it online for serving
If you need Enterprise-level Support for your system or business, you can email us at contact@siliconflow.com, or contact us through the website: https://siliconflow.cn/pricing
| onediff Enterprise Edition | onediff Community Edition | |
|---|---|---|
| More Extreme and Dedicated optimization(usually another 20~100% performance gain) for the most used model | Yes | |
| Technical Support for deployment | High priority support | Community |
@software{Cai_OneDiff_An_out-of-the-box_2024,
author = {Cai, Shenghang},
month = jun,
title = {{OneDiff: An out-of-the-box acceleration library for diffusion models}},
url = {https://github.com/siliconflow/onediff},
version = {1.1.0},
year = {2024}
}
FAQs
an out-of-the-box acceleration library for diffusion models
We found that onediff demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
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