I wonder if there are any tested recipes available to compile LibTorch from sources that result in the exactly same ready-to-use package as one that is linked on the main page here?
Instructions mentioned here don’t really work well. For example, for the image nvidia/cuda:11.7.1-cudnn8-devel-ubuntu20.04 while trying to build a release branch:
installation won’t results all the shared libraries created, e.g. libnvfuser_codegen.so is missing, etc.
There are a few related and still un-answered questions: this and this.
Well, before doing so I’d need to find our why the docker cmake command mentioned above leads to the libtorch build with which on a simple toy example I get:
what(): Type c10::intrusive_ptr<LinearPackedParamsBase> could not be converted to any of the known types.
Exception raised from operator() at /workspace/pytorch/aten/src/ATen/core/jit_type.h:1793 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0x60 (0x7fca98ab29a0 in /app/libs/libc10.so)
frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11:
issue ? This one looks to be similar but already fixed…