You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
In gran_mixture_bernoulli.py A_pad = input_dict['adj'] if 'adj' in input_dict else None
My question is during testing, is it possible to send the the adjacency matrix of an incomplete graph as A_pad and see if it gets regenerated again? If yes, is there any thing that I should keep in mind?
The text was updated successfully, but these errors were encountered:
Yes, it is doable to generate the graph conditioned on some existing partial adjacency matrix. I think you need to replace the all-zero pre-allocated the full adjacency matrix with your input adjacency matrix and slightly modify the sampling function.
In gran_mixture_bernoulli.py
A_pad = input_dict['adj'] if 'adj' in input_dict else None
My question is during testing, is it possible to send the the adjacency matrix of an incomplete graph as A_pad and see if it gets regenerated again? If yes, is there any thing that I should keep in mind?
The text was updated successfully, but these errors were encountered: