Hi, thank you for your help. What do you mean by Note that de/dc will have an explicit concrete value without needing to know dc/da or dc/db as we traverse backward through the graph.
Do you mean: if g() here is multiplication, then pytorch knows that the derivative of multiplication must be de/dc =b, so  grad_fn stores b?