OneFlow

OneFlow is a performance-centered and open-source deep learning framework.

Latest News

Version 0.6.0 is out!
- Improved consistent mode support.
- More performant eager execution.
- Full changelog

Publication

OneFlow: Redesign the Distributed Deep Learning Framework from Scratch

Bibtex Citation

@misc{yuan2021oneflow,
      title={OneFlow: Redesign the Distributed Deep Learning Framework from Scratch},
      author={Jinhui Yuan and Xinqi Li and Cheng Cheng and Juncheng Liu and Ran Guo and Shenghang Cai and Chi Yao and Fei Yang and Xiaodong Yi and Chuan Wu and Haoran Zhang and Jie Zhao},
      year={2021},
      eprint={2110.15032},
      archivePrefix={arXiv},
      primaryClass={cs.DC}
}

Install OneFlow

System Requirements

Python 3.6, 3.7, 3.8, 3.9

(Highly recommended) Upgrade pip

python3 -m pip install --upgrade pip #--user

CUDA Toolkit Linux x86_64 Driver
- CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information, please refer to CUDA compatibility documentation.
- Please upgrade your Nvidia driver to version 440.33 or above and install OneFlow for CUDA 10.2 if possible.

Install with Pip Package

To install latest stable release of OneFlow with CUDA support:

python3 -m pip install -f https://release.oneflow.info oneflow==0.6.0+cu102

To install nightly release of OneFlow with CUDA support:

python3 -m pip install --pre oneflow -f https://staging.oneflow.info/branch/master/cu102

To install other available builds for different variants:

Stable

python3 -m pip install --find-links https://release.oneflow.info oneflow==0.6.0+[PLATFORM]

Nightly

python3 -m pip install --pre oneflow -f https://staging.oneflow.info/branch/master/[PLATFORM]

All available [PLATFORM]:

Platform	CUDA Driver Version	Supported GPUs
cu112	>= 450.80.02	GTX 10xx, RTX 20xx, A100, RTX 30xx
cu111	>= 450.80.02	GTX 10xx, RTX 20xx, A100, RTX 30xx
cu110, cu110_xla	>= 450.36.06	GTX 10xx, RTX 20xx, A100
cu102, cu102_xla	>= 440.33	GTX 10xx, RTX 20xx
cu101, cu101_xla	>= 418.39	GTX 10xx, RTX 20xx
cu100, cu100_xla	>= 410.48	GTX 10xx, RTX 20xx
cpu	N/A	N/A

If you are in China, you could run this to have pip download packages from domestic mirror of pypi:
```
python3 -m pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
```
For more information on this, please refer to pypi 镜像使用帮助

Use docker image

docker pull oneflowinc/oneflow:nightly-cuda10.2
docker pull oneflowinc/oneflow:nightly-cuda11.1

Build from Source

Clone Source Code

Option 1: Clone source code from GitHub

git clone https://github.com/Oneflow-Inc/oneflow --depth=1

Option 2: Download from Aliyun
If you are in China, please download OneFlow source code from: https://oneflow-public.oss-cn-beijing.aliyuncs.com/oneflow-src.zip
```
curl https://oneflow-public.oss-cn-beijing.aliyuncs.com/oneflow-src.zip -o oneflow-src.zip
unzip oneflow-src.zip
```

Build OneFlow

Option 1: Build with Conda (recommended)
Please refer to this repo
Option 2: Build in docker container (recommended)
- Pull a docker image:
```
docker pull oneflowinc/oneflow-manylinux2014-cuda10.2:0.1
```
  All images available : https://hub.docker.com/u/oneflowinc
- In the root directory of OneFlow source code, run:
```
python3 docker/package/manylinux/build_wheel.py --inplace --python_version=3.6
```
  This should produce .whl files in the directory wheelhouse
- If you are in China, you might need to add these flags:
```
--use_tuna --use_system_proxy --use_aliyun_mirror
```
- You can choose CUDA/Python versions of wheel by adding:
```
--cuda_version=10.1 --python_version=3.6,3.7
```
- For more useful flags, plese run the script with flag --help or refer to the source code of the script.
Option 3: Build on bare metal
- Install dependencies
  - on Ubuntu 20.04, run:
```
sudo apt install -y libopenblas-dev nasm g++ gcc python3-pip cmake autoconf libtool
```
  - on macOS, run:
```
brew install nasm
```
- In the root directory of OneFlow source code, run:
```
mkdir build
cd build
```
- Config the project, inside build directory:
  - If you are in China
    
    run this to config for CUDA:
```
cmake .. -C ../cmake/caches/cn/cuda.cmake
```
    run this to config for CPU-only:
```
cmake .. -C ../cmake/caches/cn/cpu.cmake
```
  - If you are not in China
    
    run this to config for CUDA:
```
cmake .. -C ../cmake/caches/international/cuda.cmake
```
    run this to config for CPU-only:
```
cmake .. -C ../cmake/caches/international/cpu.cmake
```
- Build the project, inside build directory, run:
```
make -j$(nproc)
```
- Add oneflow to your PYTHONPATH, inside build directory, run:
```
source source.sh
```
  Please note that this change is not permanent.
- Simple validation
```
python3 -m oneflow --doctor
```

Troubleshooting

Please refer to troubleshooting for common issues you might encounter when compiling and running OneFlow.

Advanced features

XRT

You can check this doc to obtain more details about how to use XLA and TensorRT with OneFlow.

Getting Started

Please refer to QUICKSTART
中文版请参见快速上手

Documentation

Model Zoo and Benchmark

Communication

GitHub issues: any install, bug, feature issues.
www.oneflow.org: brand related information.
中文
- QQ 群: 331883
- 微信号（加好友入交流群）: OneFlowXZS
- 知乎
International
- Discord
- Twitter
- LinkedIn
- Medium

The Team

OneFlow was originally developed by OneFlow Inc and Zhejiang Lab.

License

Apache License 2.0