Unfortunately, the Pytorch team does not release binary package for Mac OS with CUDA support. This project provides off-the-shelf binary packages.
很不幸,Pytorch团队不发布 Mac OS CUDA版。本项目提供 Mac OS 上编译好、可直接安装的Pytorch CUDA版本。
【2020.02.18】I benchmarked Pytorch 1.3.1 with CUDA 10.1 and CUDNN 7.6.5 on Mac OS X 10.13.6 and Ubuntu 16.04, performance on Mac OS is around 2/3 of that on Ubuntu. In addition, it is more likey to encounter "CUDA OUT OF MEMORY" error on Mac OS since the operating system takes a large amount of GPU memory for display. Be aware of this performance difference and if you have a lot of data to process, you would better turn to Ubuntu!
The following table lists training time of MNIST image classification demo.
Settings | Single GPU | Dual GPUs |
---|---|---|
Ubuntu 1080Ti | 99.76 s | 50.99 s |
MacOS 1080Ti | 156 s | 82 s |
If you find the releases cannot meet your requirements, you can compile from source youreself.
- Guides are avaiable:
- Source pathces are availabe at
source_pathes
folder of the master branch.
You can find releases in release page.
你可以在Release页面找到发布版本。
First, ensure your CUDA driver and cudnn is installed properly, and copy dependencies in folder usr_local_lib
to path /usr/local/lib
. Also, install OpenMP using Homebrew.
首先,确保CUDA驱动和cudnn正确安装,并且将文件夹usr_local_lib
中的依赖项复制到路径/usr/local/lib
。也要通过Homebrew安装OpenMP。
sudo mkdir /usr/local
sudo mkdir /usr/local/lib
sudo cp usr_local_lib/* /usr/local/lib/
brew install libomp
brew link --overwrite libomp
Second, uninstall the previous pytorch installtion by
其次,卸载之前版本的pytorch:
pip uninstall torch
Install the wheel package from this project:
安装:
pip install torch*.whl
Install torchvision:
安装torchvision:
pip install -U torchvision
Install Python 3.x from Homebrew first, and then simply follow the guide for Python 2.7 and replace pip
command with pip3
and python
with python3
.
首先从Homebrew安装Python 3.x,然后按照Python 2.7的安装步骤执行,注意将pip
替换为pip3
,并用python3
启动python
。
Enjoy!
开始使用Pytorch吧!
Source code from: https://github.com/pytorch/pytorch
If you need Tensorflow builds for osx, go to this page: https://github.com/TomHeaven/tensorflow-osx-build
If you need MxNet builds for osx, go to this page: https://github.com/TomHeaven/mxnet_osx_build
如果你需要Tensorflow包,请看这个页面:https://github.com/TomHeaven/tensorflow-osx-build
如果你需要MxNet包,请看这个页面:https://github.com/TomHeaven/mxnet_osx_build