title: What is the difference of static Computational Graphs in tensorflow and dynamic Computational Graphs in Pytorch?
body: <p>When I was learning tensorflow, one basic concept of tensorflow was computational graphs, and the graphs was said to be static.
  And I found in Pytorch, the graphs was said to be dynamic.
  What's the difference of static Computational Graphs in tensorflow and dynamic Computational Graphs in Pytorch?</p>