I must admit I’m not much of a conda user, but so I think for pip the dependency versioning is very difficult, more so by the mix of release/nightly and cpu/various cuda version/rocm… In Debian/Ubuntu, you’d be able to express this type of dependency, but it seems difficult to do in pip. I don’t know about conda.
Another option might be to warn in TorchVision if the major version of PyTorch is higher than what TorchVision was built with.
Fun fact: A long time ago, installing pip would downgrade PyTorch.
Best regards
Thomas