I found some mostly unanswered questions in this forum that are months old and I just cannot get a good handle on the libtorch concept. Is libtorch going to get all the functionality of caffe2 eventually and then the deprecation will happen?
So far:
1) libtorch introduces yet another Intermediate representation with no way to load onnx or other pretrained models or convert,  other than a multi-stage conversion walking it thru python.
2) The now similar name means you CANNOT search for c++ API topics without being inundated with python only responses. Also there seems to be Torch the Lua based to show up in searches also. (Searches outside this and linking back to this forum too)
3) I am trying to find a c++ cross platform inference library/framework. I am interested in using pre-trained models from c++ in desktop and embedded environments and so learning has been done/is to be done in a bigger more capable workstation. It is very difficult to wade thru the Python-Centric Data scientist learning side and tease out the C++ production side. (On a plus side mxnet, tensorflow do not have prebuilts for windows and after 40+ hours of attempting to build them… I know why.)
So the question still stands, Is libtorch going to be a scaled down interface or is there a realistic effort to keep C++ a 1st class citizen like it was/is in caffe2.
Said another way, Can I still use the caffe2 features and models on the assumption that libtorch will have an equivalent before deprecation? or would that be shooting myself in the foot