@dambo:
Thanks for bringing up this issue.  I think your characterization that LibTorch is neglected, at least in comparison to areas like the Python Frontend and TorchScript, is very fair.  We certainly don’t have a policy that allocates more resources to some questions over others; as @albanD suggests, we rely on the expertise of the community and our internal developers in order to answer questions, and that naturally (but unfortunately) skews away from LibTorch currently.
Let me talk about our current investment in LibTorch / C++ API and what we plan to change.  By far our largest current investment in this area is with the Variable/Tensor merge in C++ – you may have seen https://github.com/pytorch/pytorch/pull/17072 13, for example.  We decided to invest in this way because: 1) it was the largest complaint we heard about the C++ API, particularly from our internal power users, 2) it unblocks performance gains that will affect all of PyTorch (python, C++, JIT).  However, this has unfortunately crowded out other investments in LibTorch/ C++, as you noted.
Our plan to remedy this is two-fold:

The Variable/Tensor merge project is a one-time cost, so we will be able to naturally shift attention to LibTorch / C++ more generally once it is complete (should be soon).
We are also ramping up more people on LibTorch / C++ internally, so we can provide better and broader coverage of issues.

Again, thanks for bringing this up, and hopefully this gives you some insight into our process and investments in this area.