I have some questions about sp_gat model's bias_mat input.
I notice that it is process from utils/process.py
function preprocess_adj_bias()
indices = np.vstack((adj.col, adj.row)).transpose() # This is where I made a mistake, I used (adj.row, adj.col) instead
I just don't understand your comment here: the return values of the function is feed to tf.sparse_placeholder then, and (adj.row, adj.col) is standard input for tf.SparseTensor , So why you use (adj.col, adj.row) instead ? In other words, I will make the same mistake with you! Could you explain? Many thanks!
Hi, Petar
Thanks for your great works!
I have some questions about sp_gat model's bias_mat input. I notice that it is process from utils/process.py function preprocess_adj_bias()
indices = np.vstack((adj.col, adj.row)).transpose() # This is where I made a mistake, I used (adj.row, adj.col) instead
I just don't understand your comment here: the return values of the function is feed to tf.sparse_placeholder then, and (adj.row, adj.col) is standard input for tf.SparseTensor , So why you use (adj.col, adj.row) instead ? In other words, I will make the same mistake with you! Could you explain? Many thanks!