I think you're missing my point here. Let's say you're given a PyTorch model. You can either run it with native python or grab the golang bindings that are used by 5 people, and if you get stuck there, god help you. You'll be hitting obscure bugs in no time.
To use a Python-specific framework you're better off using Python. Well duh.
Pytorch, despite the name, is really a C++ library with well developed Python bindings. There's certainly nothing in principle about it that's Python specific.
PyTorch's C++ API is experimental and doesn't have feature parity. PyTorch is a Python lib that heavily uses C++ extensions, but I don't think it has ever been a C++ library.
Comments
To use a Python-specific framework you're better off using Python. Well duh.
Pytorch, despite the name, is really a C++ library with well developed Python bindings. There's certainly nothing in principle about it that's Python specific.
PyTorch's C++ API is experimental and doesn't have feature parity. PyTorch is a Python lib that heavily uses C++ extensions, but I don't think it has ever been a C++ library.
PyTorch is not a Python binding into a monolithic C++ framework.