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Hey, congrats on the paper, I read it a while ago and thought it was really interesting. I tried implementing it, and the samples generated by the Teacher seem
by gcucurull 7y ago
Hey, congrats on the paper, I read it a while ago and thought it was really interesting.
I tried implementing it, and the samples generated by the Teacher seem to suffer from mode collapse (as if the generator is ignoring the random vector z but not the label condition). Do you recall having that issue at some point?
I have to say I'm using a simpler generator than the one in the paper, and I'm not changing the learner architechture at each batch, only its weights.
Thanks!
- felipepsuch 7y agoThanks, I'm glad you liked it! Mode collapse was actually the one thing I never encountered during my exploration (which was the reason we looked into using GTNs as a mode-collapse solution for GANs). That said, I found meta-learning to be surprisingly hard to implement efficiently and ran into more bugs in both PyTorch and TensorFlow than I can count. Changing the learner architecture is not that important actually so that's probably not your problem.
- gcucurull 7y agoOk, I'll keep digging to figure out where the problem might be, thanks!