Lurking for some transparency on grand design decisions of PyTorch and Caffe2 teams 
It seems Caffe2 is faster on introducing new neural net layers into the core, and there also seem no systematic benchmarks on speed of ops by two frameworks
Is there convergence planned for both PyTorch and Caffe2 provide the same ops running on the same backends?
Is PyTorch looking to generally port all main ops to native ATen ops?
What is the general idea of going forward for torch.script? Will it evolve into a general compiler / optimizer working on graphs or some industry-standardized IR (like what LLVM became to be; then support for future languages is easier, say Julia or even JavaScript) ?
Thanks!