Open gordicaleksa opened 7 months ago
A directed acyclic graph is a directed graph that has no cycles. A vertex v of a directed graph is said to be reachable from another vertex u when there exists a path that starts at u and ends at v. As a special case, every vertex is considered to be reachable from itself (by a path with zero edges).
It's a nit that won't matter most of the time but the topo sort implementation doesn't work in case you have cycles in the graph.
i.e. there is a hard assumption you're operating over a DAG.
It's correct. On the other hand, if it is a Dag, can we simply write the backward function as
def backward(self):
self._backward()
for child in self._prev:
child.backward()
It's a nit that won't matter most of the time but the topo sort implementation doesn't work in case you have cycles in the graph. i.e. there is a hard assumption you're operating over a DAG.
It's correct. On the other hand, if it is a Dag, can we simply write the backward function as
def backward(self): self._backward() for child in self._prev: child.backward()
No. Your implementation is essentially a DFS, while topological sort requires a BFS. For this simple case your code could be wrong:
b = 2*a
c = a + b
with topological sort, it's guaranteed that the back propagation goes in the order of c -> b -> a. With your code, the order could be c -> a -> b, which is wrong.
@gordicaleksa Could you please provide an example when the computational graph is not a DAG?
It's a nit that won't matter most of the time but the topo sort implementation doesn't work in case you have cycles in the graph.
i.e. there is a hard assumption you're operating over a DAG.