Conda installs a cpu version of pytorch and torchvision

Conda installation (tested on Ubuntu 20.04) installs a cpu version of pytorch and torchvision. In my own project, the only remedy I’ve found was to hardcode the pytorch package to use. Poor solution. Hoping to find an alternative.

Related to #527

result from conda list in torchgeo environment:

[ashnair1]

@ashnair1 @calebrob6 this relates to #295. I believe both pytorch-cpu and pytorch-gpu satisfy pytorch, but it’s always been unclear to me how to decide which conda actually uses. I wonder if running conda install pytorch-gpu explicitly after installing the environment would help.

Just tried installing pytorch-gpu (conda install pytorch-gpu -c pytorch) on top on my pre-existing conda environment (on Ubuntu 20.04 again), and it seems to be working. Don’t know how this could be elegantly done without having to add a step in the installation process. Ideally, conda could check if there’s a gpu or not and install accordingly, but I don’t think we’re close to having that feature.

I believe conda does have a way to determine if your device has a gpu or not via virtual packages. Refer here. But I’m still not clear on the details.

[ashnair1]

For what it’s worth I’ve opened conda-forge/pytorch-cpu-feedstock#102 to look into this. I didn’t observe this when I pushed #295 so I’m not sure if it’s a new development but I can reproduce this now.