Closed dselivanov closed 5 years ago
Yes! I will update the docs. I had to do this in travis too (https://github.com/dfalbel/torch/blob/master/.travis.yml#L17).
Did you figure out how to build the package with cuda support?
It builds just fine if you have CUDA installed and uncomment these lines in configure. But I haven't had a chance to test CUDA tensors - it seems we need to add CUDA tensors to pkg wrapper.
Actually I forgot one thing - for cuda lib path should be -L/$LIBCUDA/lib64
, not -L/$LIBCUDA/lib
. I will send PR with fix.
BTW interesting idea, mb try to put wget
and unzip
to configure script to fully automate installation (this won't be possible on CRAN, but I believe pkg doesn't have goal to be released on CRAN)... I will experiment.
It's too early to think about releasing on CRAN, but I wouldn't discard it. However from the arrow mailing list:
So we can make the R package to work on Windows and Mac, however, for the R package to be eligible for publication on CRAN, the required Linux libs (i.e. libarrow-dev, arrow-devel) need to be available from the official Debian and/or Fedora repository.
We would need libtorch on apt/yum and this don't depend on us.
TLDR I am for a fully automated installation.
In my case I had to download
mkl-dnn
from https://github.com/intel/mkl-dnn/releases and putmklml_mac_2019.0.1.20181227/lib/*
to/usr/local/lib/libtorch/lib
Also I haven't found (yet) how to build package with cuda support. Will keep posted.
relevant pytorch issue - https://github.com/pytorch/pytorch/issues/14165