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< jenkins-mlpack2> Yippee, build fixed!
< jenkins-mlpack2> Project docker mlpack nightly build build #706: FIXED in 3 hr 28 min: http://ci.mlpack.org/job/docker%20mlpack%20nightly%20build/706/
< HimanshuPathakGi> Hey @saksham189 are you there?? I want to ask some questions regarding gradients
< saksham189Gitter> I am here now.
< saksham189Gitter> We can have a meeting if you want
< saksham189Gitter> Feel free to drop your questions here or on the PR and I will try to answer them as soon as possible
< HimanshuPathakGi> Oh good can we meet today at 4pm
< HimanshuPathakGi> My question is just about how should I calcute the values of gradients in linear layer we are doing this by by vectorising the error * input.t() but in the case of rbf what should I do I can't able to understand?? How should I find these values I am little confused about that just need some advice over it.
< jenkins-mlpack2> Project docker mlpack weekly build build #107: FAILURE in 3 days 11 hr: http://ci.mlpack.org/job/docker%20mlpack%20weekly%20build/107/
< jenkins-mlpack2> Project docker mlpack monthly build build #18: STILL FAILING in 3 days 1 hr: http://ci.mlpack.org/job/docker%20mlpack%20monthly%20build/18/
< nishantkr18[m]> @zoq
< nishantkr18[m]> zoq: favre49 is it just me or does http://lab.mlpack.org/ take a longer time to run? It actually is causing a problem as i use agent.Step() inside the testing loop.
< nishantkr18[m]> When i comment out agent.Step(), the env is able to run the simulation and give out the video..
< zoq> nishantkr18[m]: the lab runs a docker image with limited resources, so it should be slower.
< zoq> nishantkr18[m]: I could increase the number of CPU's and memory.
< nishantkr18[m]> zoq: I think we'd have to do that, as any computation related tothe agent slows down the process, so rendering causes issues, thats what my guess is..
< zoq> nishantkr18[m]: The think the problem is that the notebook drops the connections after some time, e.g. if agent.step takes a long time.
< nishantkr18[m]> @zo
< nishantkr18[m]> zoq: Yeah, could be
< saksham189Gitter> Hey @zoq , there are several different approaches to learning RBF networks based on k-means clustering, gradient descent etc. Is there any specific learning approach that you want to implement?
< saksham189Gitter> (edited) ... that you want to ... => ... that we should try to ...
< saksham189Gitter> > My question is just about how should I calcute the values of gradients in linear layer we are doing this by by vectorising the error * input.t() but in the case of rbf what should I do I can't able to understand?? How should I find these values I am little confused about that just need some advice over it.
< saksham189Gitter> I read some papers on RBFN and seems like there are numerous learning approaches for RBF. So, I will discuss with @zoq and let you know which approach we move ahead with.
< saksham189Gitter> (edited) ... we move ... => ... we should move ...
< HimanshuPathakGi> Yeah in some paper's they are using random data as centres and in some kmeans,
< HimanshuPathakGi> So I was also confused due to this.
< saksham189Gitter> yup, I saw that too :)
< zoq> nishantkr18[m]: Done, but that doesn't solve the issue, I'm not sure this is a timeout issue, because I added: #include <boost/thread/thread.hpp> and boost::this_thread::sleep( boost::posix_time::seconds(5) ); instead of step and it still works.
< HimanshuPathakGi> We have to wait for @zoq for this. Thanks for pointing out.
< zoq> nishantkr18[m]: Did you test agent.State().Data() = on you local system?
< zoq> nishantkr18[m]: Maybe that one already fails?
< zoq> nishantkr18[m]: I mean in combination with agent.Step();
< nishantkr18[m]> zoq: Yes, the code works with no errors on my machine
< nishantkr18[m]> zoq: Yeah, I've tried the combination as well..
< zoq> nishantkr18[m]: OKay, increased the timeout as well, can you test again?
< nishantkr18[m]> zoq: yeah sure
< zoq> saksham189Gitter: I think k-means would be interesting.
< zoq> nishantkr18[m]: Hm, maybe I did something wrong ...
< nishantkr18[m]> zoq: hmm, still not working ☚ī¸Ž
< zoq> nishantkr18[m]: Not sure, I set the timeout to 10 seconds, maybe sometimes we need more.
< nishantkr18[m]> @zo
< nishantkr18[m]> zoq: We'll need to try and find out
< zoq> nishantkr18[m]: Does it work?
< nishantkr18[m]> zoq: Now, it seems to be working.. I think the best way to test would be to get https://github.com/mlpack/mlpack/pull/2413 merged, and then test the trained agent
< zoq> nishantkr18[m]: Right, if you can handle the comment on the PR I think it's ready.
< nishantkr18[m]> zoq: Done 👍ī¸
< zoq> nishantkr18[m]: :)
< kartikdutt18Gitt> Hey @rcurtin, Could we upload separate csv for mnist train and test (as done for iris) as well as one for bodyfat.tsv on mlpack.org?
< rcurtin> kartikdutt18Gitt: I don't have an issue with it; we used the local processing idea because shrit[m] pointed out that using other servers can help save any bandwidth costs
< rcurtin> (I'm not near the bandwidth limit for mlpack.org, but it doesn't hurt to try and save bandwidth :))
< rcurtin> adding bodyfat.tsv seems just fine for me, let me know where the file is and I'll put it on mlpack.org/datasets/
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< zoq> rcurtin: If we ever run into any traffic concers let me know I have unlimited traffic.
< jeffin143[m]> Unlimited traffic
< jeffin143[m]> Woh
< rcurtin> zoq: sounds good; the bandwidth limits for me are quite generous too, so it would probably be a pretty crazy amount of traffic before we had any issues :)
< rcurtin> not as generous as "unlimited" though :-D
< jeffin143[m]> rcurtin (@freenode_rcurtin:matrix.org) : is it ok to add protobuf as dependancy in mlpack
< jeffin143[m]> Or do we need a separate dashboard ???
< zoq> They restricted to 10 Mbit/s after 10TB.
< rcurtin> jeffin143[m]: I would really strongly prefer not to add another dependency
< jeffin143[m]> Repository*
< jeffin143[m]> Ohk
< zoq> jeffin143[m]: About the jupyter notebook service looks interesting, we should test it on the examples/models repo.
< jeffin143[m]> <jeffin143[m] "Ohk"> zoq (@freenode_zoq:matrix.org): yes indeed , I am not sure if that works with xesus
< zoq> I think they just render the notebook, just like github does
< jeffin143[m]> Rcurtin is it ok to add one more repo for vis tool which has proto buf as dependancy ??
< zoq> Maybe we should merge https://github.com/mlpack/mlpack/pull/2405 as a temporary solution?
< zoq> nishantkr18[m]: With #2413 merged let me rebuild the jupyter docker, will take some time.
< nishantkr18[m]> zoq: 👍ī¸
< zoq> nishantkr18[m]: I have to rebuild mlpack in the docker image to use the functions added in: https://github.com/mlpack/mlpack/pull/2413
< zoq> nishantkr18[m]: After that I can push it to dockerhub and pull the new image on the lab.mlpack.org nodes.
< nishantkr18[m]> oh.. sounds lengthy
< zoq> nishantkr18[m]: We should automate the process, but it's just make wait for the build to finish, docker tag && docker push && docker pull.
< nishantkr18[m]> zoq: Yeah, automating will make it easy to work with lab.mlpack.org..
< zoq> nishantkr18[m]: updated
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