inp = torch.randn(3,3, requires_grad=True)
another = torch.randn(3, 3, requires_grad=True)
inter = inp * 3
inter2 = inp * 4
result = torch.matmul(inter, inter2)

We knew that result was created using matmul in forward prop, but autograph should also record the information about the parent node inter, inter2 and their corresponding values in order to do backprop rite? Are those dependency and edge information available through python?. For eg in custom autograd function we have ctx for saving info for backward, are those ctx information exposed in python?