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< manish7294>
rcurtin: Did you get the chance to look at LMNN tests?
< rcurtin>
manish7294: ack, I did not realize I needed to do that! but it is very late here... I will handle it tomorrow morning if that is okay
< manish7294>
rcurtin: sure, no worries!
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< ShikharJ>
zoq: I have pushed the changes to the PR, and most of the debugging has been done. The only issue I'm facing is with the call for Generator's Gradient call, for which I'm unable to determine the point of error origin. I would appreciate any help with that.
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< haritha1313>
zoq: What would be the right layer to use as flatten layer in a FNN? While writing proposal I guess I did find some layer existing in mlpack, but now I can't recollect exactly.
< ShikharJ>
haritha1313: I think Linear (with / without bias) would be the way to go. Better to get confirmation from zoq, though.
< haritha1313>
ShikharJ: Thanks! I'll check it out. I haven't worked much with the ann module so it gets confusing at times :D.
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< rcurtin>
manish7294: if you'd like a shell on a system for benchmarking the LMNN code just let me know, we can use some of the mlpack build systems for that
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< zoq>
ShikharJ: I'll take a look at the code.
< zoq>
haritha1313: ShikharJ is right, Linear is the equivalent.
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< manish7294>
rcurtin:Thanks, that will be great. I can also try doing that on AWS, maybe you can advise me about the required configuration that will be sufficient for benchmarking.
< manish7294>
rcurtin: I have commented on PR about SGD issue, please try to have a look at it.
< manish7294>
Or, maybe I should just write it here.
< rcurtin>
sure, let me send a private message with account details
< manish7294>
Currently we are getting good enough results with L-BFGS but that's not true with SGD
< rcurtin>
right, I'll answer in the PR, hang on
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< zoq>
ShikharJ: Do you know where preTrainedGAN does come from?