Soumith Chintala

yes, you can set RPATH with CMake and also in setup.py where relevant. You can look at pointers from the PyTorch repo: - CMake: https://github.com/pytorch/pytorch/blob/3bdc4a37ed802f69a032179c1540aee6529eb2c1/torch/lib/libshm/CMakeLists.txt#L35 and https://github.com/pytorch/pytorch/blob/ff21b156246e16e939b4f87fe20964e2dbb40dc8/cmake/Dependencies.cmake#L3-L8 - setup.py: https://github.com/pytorch/pytorch/blob/ff21b156246e16e939b4f87fe20964e2dbb40dc8/setup.py#L639...

the `conda-build` patchelf hacks we have in the PyTorch builder repos, I wrote them before we fixed the build system correctly. They can, I believe removed now, but we never...

this can be closed. if you install the latest binaries with instructions from http://pytorch.org this issue will be fixed now. Sorry for the trouble.

@selous123 can you paste the code that gave a segfault in the terminal?

@clived2 I've followed up with you here: https://discuss.pytorch.org/t/pytorch-0-2-0-python-3-5-issue-which-seems-quite-common/7288 and let's discuss there.

from the migration guide, the most matching option seems to be a loopback IP address -- so cyberduck temporarily listens on some localhost+port and that is given as the redirect_uri...

@godmoves if you are using Volta, please use this command to install pytorch-nightly: `conda install -c pytorch pytorch-nightly cuda90` (I've updated readme). The previous command installed cuda 8.0 version which...

yes, unfortunately there's no good way to install this on windows. You could maybe try it via Docker or VirtualBox

try controlling the GPU to be used via CUDA_VISIBLE_DEVICES environment variable instead.

you can find `slerp` code in this comment https://github.com/soumith/dcgan.torch/issues/14#issuecomment-199171316