For fun, I decided Wolfrat Bot needed a bit more, err, personality. So, I set off to make him one. After training an RNN for a few hours on my desktop’s GPU, I had interesting results but ultimately failed at achieving quite what I wanted.
Anyway, I encountered some huge hurdles I found out AFTER training for ~8 hours that the way I was encoding the characters for the network input (and thus, the way I was decoding the network output) behaved non-deterministically between Python 3.5 runtimes! I was constructing a set out of the input dataset, and making a dictionary out of it. In Python 2.7, it behaved the same way every time. Now, I don’t expect sets to store the elements in any order (that’s kinda the point), but I had at least expected the order to be consistent, though I guess that was awfully presumptious of me.
To demonstrate, running
python3 -c 'print(set("test"))'
more than once yields different results
for me. On the other hand, running
python2 -c 'print(set("test"))'
more than once always yields the same results.
The results were about what I expected from the character RNN model that I used - it generates messages, but it doesn’t generate replies. The following exchange demonstrates what I mean:
Me: How are you? RNN: Yes. Me: What are you up to? RNN: u suit the lack of empires Me: Do you hate me? RNN: we could do is that the guy who dont see a student Me: Who am I? RNN: we still don't know if they wanted to other people equivale won't tell us a strategy free episodes of distributed stuff in the CVRL and i3status integes, desktop gram Me: That didn't even make any sense. RNN: it's confusing it Me: me too RNN: https://twitter.com/NDLibraries/status/721324222115053512166284272434243135-281642214/01130-0082826177215_n.jpg
OK, that last one is the interesting - up until ‘status’ that link is perfectly valid. Regardless, it doesn’t seem to care what was said previously - it just says whatever it feels like. It is clear that a different approach might be necessary for achieving good results - a character level RNN might be insufficient for generating relevant conversation.