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

OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
https://github.com/Oneflow-Inc/oneflow

cuda deep-learning deep-neural-networks distributed machine-learning ml neural-network

Last synced: 3 months ago
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OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.

Host: GitHub
URL: https://github.com/Oneflow-Inc/oneflow
Owner: Oneflow-Inc
License: apache-2.0
Created: 2017-02-11T06:09:53.000Z (almost 8 years ago)
Default Branch: master
Last Pushed: 2024-04-10T11:31:40.000Z (9 months ago)
Last Synced: 2024-04-10T12:30:09.704Z (9 months ago)
Topics: cuda, deep-learning, deep-neural-networks, distributed, machine-learning, ml, neural-network
Language: C++
Homepage: http://www.oneflow.org
Size: 82 MB
Stars: 5,706
Watchers: 145
Forks: 647
Open Issues: 501
Metadata Files:
- Readme: README.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS

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README

        # OneFlow

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

- program a model with [**PyTorch-like API**](https://oneflow.readthedocs.io/en/master/)

- scale a model to n-dimensional-parallel execution with the [**Global Tensor**](https://docs.oneflow.org/en/master/cookies/global_tensor.html)

- accelerate/deploy a model with the [**Graph Compiler**](https://oneflow.readthedocs.io/en/master/graph.html).

[![Simple CI](https://github.com/Oneflow-Inc/oneflow/actions/workflows/simple.yml/badge.svg)](https://github.com/Oneflow-Inc/oneflow/actions/workflows/simple.yml)

[![Nightly Docker Image](https://github.com/Oneflow-Inc/docker-images/actions/workflows/oneflow-nightly.yml/badge.svg)](https://github.com/Oneflow-Inc/docker-images/actions/workflows/oneflow-nightly.yml)

[![Nightly Release](https://github.com/Oneflow-Inc/oneflow/actions/workflows/release.yml/badge.svg)](https://github.com/Oneflow-Inc/oneflow/actions/workflows/release.yml)

[![Documentation](https://readthedocs.org/projects/oneflow/badge/?version=master)](https://oneflow.readthedocs.io/en/master/?badge=master)

## Latest News

- Version 1.0.0 is out!

  - [Full changelog](https://github.com/Oneflow-Inc/oneflow/releases/tag/v1.0.0)

## Publication

- [OneFlow: Redesign the Distributed Deep Learning Framework from Scratch](https://arxiv.org/abs/2110.15032)

## System Requirements

### General

- Linux

- Python 3.7, 3.8, 3.9, 3.10, 3.11

### CUDA

- CUDA arch 60 or above

- CUDA Toolkit version 10.0 or above

- Nvidia driver version 440.33 or above

  OneFlow will work on a minimum supported driver, and any driver beyond. For more information, please refer to [CUDA compatibility documentation](https://docs.nvidia.com/deploy/cuda-compatibility/index.html).

## Install

### 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:

  ```bash

  python3 -m pip install oneflow

  ```

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

  ```bash

  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:

  ```bash

  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](https://mirror.tuna.tsinghua.edu.cn/help/pypi/)

### Install from Source

Clone Source Code

- #### Option 1: Clone source code from GitHub

  ```bash

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

  ```

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

  ```bash

  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](https://github.com/Oneflow-Inc/conda-env) or use the docker image by:

  ```bash

  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

  ```

  

### Troubleshooting

Please refer to [troubleshooting](docs/source/troubleshooting.md) for common issues you might encounter when compiling and running OneFlow.

## Getting Started

- Please refer to [QUICKSTART](https://docs.oneflow.org/en/master/basics/01_quickstart.html)

- 中文版请参见 [快速上手](https://docs.oneflow.org/master/basics/01_quickstart.html)

## Documentation

- [API Reference](https://oneflow.readthedocs.io/en/master/)

- [Usage & Design Docs](http://docs.oneflow.org/)

- [System Design](https://docs.oneflow.org/en/v0.4.0/basics_topics/essentials_of_oneflow.html)

## Model Zoo and Benchmark

- [Libai(Toolbox for Parallel Training Large-Scale Transformer Models)](https://github.com/Oneflow-Inc/libai)

  - [BERT-large](https://libai.readthedocs.io/en/latest/tutorials/get_started/quick_run.html)

  - [GPT](https://libai.readthedocs.io/en/latest/modules/libai.models.html#id5)

  - [T5](https://libai.readthedocs.io/en/latest/modules/libai.models.html#id4)

  - [VisionTransformer](https://libai.readthedocs.io/en/latest/modules/libai.models.html#id1)

  - [SwinTransformer](https://libai.readthedocs.io/en/latest/modules/libai.models.html#id2)

- [FlowVision(Toolbox for Computer Vision Datasets, SOTA Models and Utils)](https://github.com/Oneflow-Inc/vision)

- [OneFlow-Models(Outdated)](https://github.com/Oneflow-Inc/models)

  - [ResNet-50](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/resnet50)

  - [Wide&Deep](https://github.com/Oneflow-Inc/models/tree/main/RecommenderSystems/wide_and_deep)

- [OneFlow-Benchmark(Outdated)](https://github.com/Oneflow-Inc/OneFlow-Benchmark)

## Communication

- [GitHub issues](https://github.com/Oneflow-Inc/oneflow/issues): any install, bug, feature issues.

- [www.oneflow.org](http://www.oneflow.org): brand related information.

- ### 中文

  - QQ 群: 331883

  - 微信号（加好友入交流群）: OneFlowXZS

  - [知乎](https://www.zhihu.com/org/oneflow-17)

- ### International

  - [Discord](https://discord.gg/4kpjGA5bZY)

  - [Twitter](https://twitter.com/OneFlowNews)

  - [LinkedIn](https://www.linkedin.com/company/oneflow-inc)

  - [Medium](https://oneflow2020.medium.com)

## The Team

OneFlow was originally developed by [OneFlow Inc](http://www.oneflow.org) and [Zhejiang Lab](http://www.zhejianglab.com/).

## License

[Apache License 2.0](LICENSE)