MegEngine 是基于计算图的深度神经网络学习框架
MegEngine 是一个快速、可拓展、易于使用且支持自动求导的数值计算框架
Python 机器学习
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详细介绍
MegEngine
English | 中文
MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation.
Installation
NOTE: MegEngine now only supports Linux platform with Python 3.5 or higher. On Windows 10 you could try WSL(Windows Subsystem for Linux) to use Linux within Windows.
Binaries
Commands to install from binaries via pip wheels are as follows:
pip3 install megengine -f https://megengine.org.cn/whl/mge.html
Build from Source
Prerequisites
Most of the dependencies of MegEngine are located in third_party
directory, and you do not need to install these by yourself. you can prepare these repositories by executing:
./third_party/prepare.sh
./third_party/install-mkl.sh
But some dependencies should be manually installed:
- CUDA(>=10.1), cuDNN(>=7.6)are required when building MegEngine with CUDA support (default ON)
- TensorRT(>=5.1.5) is required when building with TensorRT support (default ON)
- LLVM/Clang(>=6.0) is required when building with Halide JIT support (default ON)
- Python(>=3.5), Numpy, SWIG(>=3.0) are required to build Python modules. (default ON)
Build
MegEngine prefers Out-Of-Source
flavor, and compile in a mostly-static
way. Here are the instructions:
-
Make a directory for the build.
mkdir -p build cd build
-
Generate build configurations by
CMake
.For CUDA build:
cmake .. -DMGE_WITH_TEST=ON
For CPU only build, use
-DMGE_WITH_CUDA=OFF
:cmake .. -DMGE_WITH_CUDA=OFF -DMGE_WITH_TEST=ON
For deployment with C++ only, use
-DMGE_INFERENCE_ONLY=ON
, and turn off test with-DMGE_WITH_TEST=OFF
:cmake .. -DMGE_INFERENCE_ONLY=ON -DMGE_WITH_TEST=OFF
Use
-DCMAKE_INSTALL_PREFIX=YOUR_PATH
to specify the install path. -
Start to build.
make -j$(nproc)
-
[optional] Install the library if compiled for deployment at step 2.
make install
Here are some other useful options for the build.
MGE_ARCH
specifies which arch MegEngine are building for. (default AUTO)MGE_WITH_DISTRIBUTED
if multiple machine distributed support is enabled. (default ON)MGE_WITH_PYTHON_MODULE
if build python module. (default ON)MGE_BLAS
choosesMKL
orOpenBLAS
as BLAS library for MegEngine. (defaultMKL
)MGE_CUDA_GENCODE
supplies the-gencode
option fornvcc
. (default not supply)MGE_DISABLE_FLOAT16
if disable float16 support. (default OFF)MGE_ENABLE_EXCEPTIONS
if enable exception support in C++. (default ON)MGE_ENABLE_LOGGING
if enable logging in MegEngine. (default AUTO)
More options can be found by:
cd build
cmake -LAH .. 2>/dev/null| grep -B 1 'MGE_' | less
How to Contribute
- MegEngine adopts Contributor Covenant to maintain our community. Please read the Code of Conduct to get more information.
- Every contributor of MegEngine must sign a Contributor License Agreement (CLA) to clarify the intellectual property license granted with the contributions. For more details, please refer Contributor License Agreement
- You can help MegEngine better in many ways:
- Write code.
- Improve documentation.
- Answer questions on MegEngine Forum, or Stack Overflow.
- Contribute new models in MegEngine Model Hub.
- Try a new idea on MegStudio.
- Report or investigate bugs and issues.
- Review Pull Requests.
- Star MegEngine repo.
- Reference MegEngine in your papers and articles.
- Recommend MegEngine to your friends.
- ...
We believe we can build an open and friendly community and power humanity with AI.
How to contact us
- Issue: github.com/MegEngine/MegEngine/issues
- Email: megengine-support@megvii.com
- Forum: discuss.megengine.org.cn
- QQ: 1029741705
- OPENI: openi.org.cn/MegEngine
Resources
License
MegEngine is Licensed under the Apache License, Version 2.0
Copyright (c) 2014-2020 Megvii Inc. All rights reserved.