nvidia-docker run -it --ipc=host --rm -v $(pwd):/remote soumith/conda-cuda bash
pushd remote/conda
./build_csprng.sh 9.0
./build_csprng.sh 10.0
./build_csprng.sh cpu
# copy packages over to /remote
# exit docker
# anaconda upload -u pytorch torchcsprng*.bz2# create a fresh anaconda environment / install and activate it
conda install -y conda-build anaconda-client
./build_csprng.sh cpu
# copy packages over to /remote
# exit docker
# anaconda upload -u pytorch torchcsprng*.bz2# Open `Git Bash` and change dir to `conda`
./build_csprng.sh 9.0
./build_csprng.sh 10.0
./build_csprng.sh cpu
# copy packages to a output directory
# anaconda upload -u pytorch torchcsprng*.bz2pushd wheel
nvidia-docker run -it --ipc=host --rm -v $(pwd):/remote soumith/manylinux-cuda90:latest bash
cd remote
./linux_manywheel.sh cu90
rm -rf /usr/local/cuda*
./linux_manywheel.sh cpunvidia-docker run -it --ipc=host --rm -v $(pwd):/remote soumith/manylinux-cuda100:latest bash
cd remote
./linux_manywheel.sh cu100wheels are in the folders cpu, cu90, cu100.
You can upload the cu90 wheels to twine with twine upload *.whl.
Which wheels we upload depends on which wheels PyTorch uploads as default, and right now, it's cu90.
pushd wheel
./osx_wheel.shset PYTORCH_REPO=pytorch
pushd windows
call build_csprng.bat 90 0.3.0 1
call build_csprng.bat 100 0.3.0 1
call build_csprng.bat cpu 0.3.0 1wheels are in the current folder.
You can upload them to twine with twine upload *.whl