Hi,
I try to run nevae and find something confusing.
In the model.py file, the get_lossfunc function only contains KL and likelihood losses, but the paper states that there are four losses including KL, likelihood, log(pλn), log(pλm). Should I need to implement log(pλn) and log(pλm) by myself?
In the model.py file, the implementation of masked_gen function is a little bit complex, so I can't understand it clearly. Could you give me some related papers or information to read?
In the utils.py file, the code of line 135 is edgelist which appends same all edges of compound graph many times in the loop of G.nodes(). I think that line135 should be put outside the scope of loop of G.nodes() to avoid duplicate contents. If I make mistakes, please let me know.
Thank you for your patience to read my questions. I'll appreciate it if anyone can answer my questions.
Hi, I try to run nevae and find something confusing.
In the model.py file, the get_lossfunc function only contains KL and likelihood losses, but the paper states that there are four losses including KL, likelihood, log(pλn), log(pλm). Should I need to implement log(pλn) and log(pλm) by myself?
In the model.py file, the implementation of masked_gen function is a little bit complex, so I can't understand it clearly. Could you give me some related papers or information to read?
In the utils.py file, the code of line 135 is edgelist which appends same all edges of compound graph many times in the loop of G.nodes(). I think that line135 should be put outside the scope of loop of G.nodes() to avoid duplicate contents. If I make mistakes, please let me know.
Thank you for your patience to read my questions. I'll appreciate it if anyone can answer my questions.