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Oneflow-Inc/oneflow

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

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C++ Apache-2.0Created Feb 11, 2017

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Slowing (219d since push)
As of today · Source: github_public_v1
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Not a fork · Organization account
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No lockfile
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Overview

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

Capability facts

Languages
c++

Source: github.language · Jul 11, 2026

Categories

Developer ToolsComputer Vision

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 11, 2026)

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

Tags

mldeep-learningdistributedmachine-learningneural-networkcudadeep-neural-networksc

README

Preinstall docker image

docker pull oneflowinc/oneflow:nightly-cuda11.8

Pip Install

  • (Highly recommended) Upgrade pip

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

  • To install latest stable release of OneFlow with CUDA support:

    python3 -m pip install oneflow

  • To install nightly release of OneFlow with CPU-only support:

    python3 -m pip install --pre oneflow -f https://oneflow-staging.oss-cn-beijing.aliyuncs.com/branch/master/cpu

  • To install nightly release of OneFlow with CUDA support:

    python3 -m pip install --pre oneflow -f https://oneflow-staging.oss-cn-beijing.aliyuncs.com/branch/master/cu118

    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

Install from Source

Clone Source Code

  • Option 1: Clone source code from GitHub

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

  • Option 2: Download from Aliyun(Only available in China)

    curl https://oneflow-public.oss-cn-beijing.aliyuncs.com/oneflow-src.zip -o oneflow-src.zip
unzip oneflow-src.zip
Build OneFlow

  • Install dependencies

    apt install -y libopenblas-dev nasm g++ gcc python3-pip cmake autoconf libtool

    These dependencies are preinstalled in offical conda environment and docker image, you can use the offical conda environment here or use the docker image by:

    docker pull oneflowinc/manylinux2014_x86_64_cuda11.2

  • In the root directory of OneFlow source code, run:

    mkdir build
cd build

  • Config the project, inside build directory:

    • If you are in China

      config for CPU-only like this:

      cmake .. -C ../cmake/caches/cn/cpu.cmake

      config for CUDA like this:

      cmake .. -C ../cmake/caches/cn/cuda.cmake -DCMAKE_CUDA_ARCHITECTURES=80 -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda -DCUDNN_ROOT_DIR=/usr/local/cudnn

    • If you are not in China

      config for CPU-only like this:

      cmake .. -C ../cmake/caches/international/cpu.cmake

      config for CUDA like this:

      cmake .. -C ../cmake/caches/international/cuda.cmake -DCMAKE_CUDA_ARCHITECTURES=80 -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda -DCUDNN_ROOT_DIR=/usr/local/cudnn

      Here the DCMAKE_CUDA_ARCHITECTURES macro is used to specify the CUDA architecture, and the DCUDA_TOOLKIT_ROOT_DIR and DCUDNN_ROOT_DIR macros are used to specify the root path of the CUDA Toolkit and CUDNN.

  • 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

Getting Started

License

Apache License 2.0