- install webdriver.sh
brew tap vulgo/repo
brew install webdriver.sh
- install lastest driver
webdriver
installed version 387.10.10.10.40.133
- install cuda via brew:
brew tap homebrew/cask-drivers
brew cask install nvidia-cuda
- add the following to your file ~/.bash_profile:
export PATH=/Developer/NVIDIA/CUDA-9.0/bin${PATH:+:${PATH}}
export DYLD_LIBRARY_PATH=/Developer/NVIDIA/CUDA-9.0/lib${DYLD_LIBRARY_PATH:+:${DYLD_LIBRARY_PATH}}
- verify installation
nvcc --version
installed version 418.105
Install cuDNN
- download cuDNN v7.6.5 (November 5th, 2019), for CUDA 10.1
- untar
tar -xzvf cudnn-10.1-osx-x64-v7.6.5.32.tgz
- copy the files into the CUDA Toolkit directory, and change the file permissions
sudo cp cuda/include/cudnn*.h /usr/local/cuda/include
sudo cp cuda/lib/libcudnn* /usr/local/cuda/lib
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
installed version 7.6.5
Build PyTorch from source
- install anaconda
- remove previous versions of pythorch
conda remove pytorch torchvision -y
pip uninstall torch -y
pip uninstall torch -y # yes twice
conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing_extensions future six requests
git clone --recursive https://github.com/pytorch/pytorch
cd pytorch
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
MACOSX_DEPLOYMENT_TARGET=10.13 CC=clang CXX=clang++ python setup.py install
error when linking
libtorch_cuda.dylib
on macOS 10.13.6 fix
- build
torchvision
from source
git clone --recursive https://github.com/pytorch/vision
cd vision
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
MACOSX_DEPLOYMENT_TARGET=10.13 CC=clang CXX=clang++ python setup.py install
- verify installation
import torch
print(torch.__version__)
import torch
assert torch.cuda.is_available()
assert torch.randn(20).cuda().is_cuda
import torch
assert torch.backends.cudnn.enabled
installed version 1.7.0a0+eeb43ff
@brokeyourbike, what versions of the dependencies and what version of Python did you use? Can you capture your exact environment in pip or conda? Can you share the result of
conda list --explicit
?