OneFlow
OneFlow is a performance-centered and open-source deep learning framework.
Latest News
- Version 0.5.0 is out!
- First class support for eager execution. The deprecated APIs are moved to
oneflow.compatible.single_client
- Drop-in replacement of
import torch
for existing Pytorch projects. You could test it by inter-changingimport oneflow as torch
andimport torch as flow
. - Full changelog
- First class support for eager execution. The deprecated APIs are moved to
Install OneFlow
System Requirements
-
Python 3.6, 3.7, 3.8, 3.9
-
(Highly recommended) Upgrade pip
python3 -m pip install --upgrade pip #--user
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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==0.5.0+cu102
-
To install nightly release of OneFlow with CUDA support:
python3 -m pip install 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==0.5.0+[PLATFORM]
- Nightly
python3 -m pip install 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
- Stable
-
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
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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 directorywheelhouse
-
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
- on Ubuntu 20.04, run:
-
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
The Team
OneFlow was originally developed by OneFlow Inc and Zhejiang Lab.