Like tensorflow uses Static Computation graphs. When you define your network, it prepares the whole graph data structure before running. Whereas, pytorch uses Dynamic CG, where CG is prepared dynamically when the interpreter runs the code line by line.

My questions are: 1. Is there anything conceptually wrong in the above paragraph? 2. How does Caffe2 does it?