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OneFlow

OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. With OneFlow, it is easy to:

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Latest News

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

  • Linux. As for now, there is no pre-built release for macOS, Windows.

  • Python 3.7, 3.8, 3.9, 3.10

  • (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 oneflow
  • To install nightly release of OneFlow with CUDA support:

    python3 -m pip install --pre oneflow -f https://staging.oneflow.info/branch/master/cu117
  • To install other available builds for different variants:

    • Stable
      python3 -m pip install --find-links https://release.oneflow.info oneflow==0.9.0+cu117
    • Nightly
      python3 -m pip install --pre oneflow -f https://staging.oneflow.info/branch/master/[PLATFORM]
      
    • All available [PLATFORM]:
      Platform CUDA Driver Version Supported GPUs
      cu117 >= 450.80.02 GTX 10xx, RTX 20xx, A100, RTX 30xx
      cu102 >= 440.33 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-cuda11.7

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 the docker image:

      docker pull oneflowinc/manylinux2014_x86_64_cuda11.2
    • Follow the instructions in the bare metal build guide below.

  • Option 3: Build on bare metal

    • Install dependencies (not required if you are using docker):

      • 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

  • OneFlow-XRT: An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.

Getting Started

Documentation

Model Zoo and Benchmark

Communication

The Team

OneFlow was originally developed by OneFlow Inc and Zhejiang Lab.

License

Apache License 2.0

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OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.

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  • C++ 57.4%
  • Python 28.0%
  • Cuda 11.1%
  • C 2.1%
  • MLIR 0.7%
  • CMake 0.6%
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