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< travis-ci> mlpack/mlpack#591 (master - a69871c : Ryan Curtin): The build passed.
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< Guest19631> hello guys
< Guest19631> I'm Rohit Patwa from India. I am interested in deep learning projects of mlpack for GSOC-2016
< Guest19631> please guide me how to get started
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< kirizaki> Hi there!
< kirizaki> First You can check "about" MLPACK: http://www.mlpack.org/help.html
< kirizaki> make the tutorials and get to know little bit with code: http://www.mlpack.org/help.html
< kirizaki> and here You can find some information about GSoC: https://github.com/mlpack/mlpack/wiki
< kirizaki> ;)
< kirizaki> hope it help
< kirizaki> always You can use mlpack mailing list and ask here
< kirizaki> for sure someone will help You :)
< Guest19631> thanks for the prompt response kirizaki :)
< rebeka> Hello. I am Rebeka Mukherjee from India. I am interested to take part in GSoC 2016. Some of the topics I have studied previously and am intersted to work on are k-center algorithm, k-nn algorithm, neighbourhood-based collaborative filtering, decision trees, deep learning modules. Could someone please get back to me with more information on these projects so that I can decide my topic for the proposal?
< kirizaki> no problem, I'll be out right now 'cause I'm sick but: We don't respond instantly... but we will respond. Give it a few minutes. Or hours. -- Channel logs: http://...
< kirizaki> Hi rebeka
< kirizaki> if You want to get started You can check http://www.mlpack.org/help.html
< kirizaki> some tutorials: http://www.mlpack.org/help.html
< kirizaki> some info about GSoC https://github.com/mlpack/mlpack/wiki
< kirizaki> and that's all for now with which I can help You, because I'm not the one who knows a lot about those algorithms
< rebeka> Thank you. I have gone through the github link for GSoC. I will now delve into the tutorials :)
< kirizaki> but Your question will be responded because "rcurtin" is the main guru xD
< kirizaki> go ahead ;)
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< Nilabhra> anyone here?
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< mentekid> I am here but I am a GSoC student not a developer :P
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< Nilabhra> mentekid: hi, have you chosen a project?
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< mentekid> Nilabhra: I am thinking about the Approximate Nearest Neighbors one, I've worked with such algorithms before. How about you?
< Nilabhra> mentekid: thinking about working on collaborative filtering
< Nilabhra> mentekid: do you know how many tickets did mlpack get for 2016?
< mentekid> Nilabhra: by tickets you mean applications? I have no idea
< Nilabhra> mentekid: okay :)
< mentekid> Nilabhra: the ML seems quite active though, so if everyone sending emails is applying I guess they will get a lot of them
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< mentekid> have you compiled the system? I am looking around for documentation and stuff, I've run a few algorithms but haven't found a way to properly run test code
< Nilabhra> no google allows organizations to let only a few students to work on gsoc. I was asking if anyone knows the number of students google will allow for mlpack.
< Nilabhra> No I just saw mlpack today, will download and compile soon enough.
< Nilabhra> mentekid: ^
< mentekid> Nilabhra: Ah, I didn't know that, this is my first time in the programme. I assumed that #ideas = #students, probably I was wrong. I should read the programme information more carefully :P
< Nilabhra> mentekid: :P yep totally
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< kirizaki> mentekid: "but haven't found a way to properly run test code" if You mean to run mlpack test
< kirizaki> You shoud do: ./build/bin/mlpack_test -p
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< Nilabhra> kirizaki: so how to get started? Should I first do some bug fixing?
< kirizaki> You can familiarize Your self with Issue list at github ;)
< kirizaki> pick Difficulty: ease
< kirizaki> I understand You finish with tutorials?
< kirizaki> if not You can check: http://www.mlpack.org/about.html
< kirizaki> and here: http://www.mlpack.org/help.html
< kirizaki> always can ask via mailing list or here at IRC
< kirizaki> " We don't respond instantly... but we will respond. Give it a few minutes. Or hours"
< kirizaki> ;)
< kirizaki> and to make it clear, I'm just a newbie here too so just passing by main info ;)
< kirizaki> so questions about ML or DeepL. You should forward to "rcurtin" or "zoq"
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< ankur> hi
< ankur> I am trying to compile simple logging example from http://www.mlpack.org/doxygen.php?doc=iodoc.html
< ankur> but I am getting some errors
< kirizaki> please, paste some log, what errors do You have ;)
< kirizaki> pastebin.com will be good
< ankur> main.cpp:(.text+0x2cc): undefined reference to `mlpack::CLI::ParseCommandLine(int, char**)'
< ankur> main.cpp:(.text+0x2d6): undefined reference to `mlpack::Log::Debug'
< ankur> main.cpp:(.text+0x2f2): undefined reference to `mlpack::Log::Info'
< ankur> main.cpp:(.text+0x2cc): undefined reference to `mlpack::CLI::ParseCommandLine(int, char**)'
< ankur> main.cpp:(.text+0x2d6): undefined reference to `mlpack::Log::Debug'
< ankur> main.cpp:(.text+0x2f2): undefined reference to `mlpack::Log::Info'
< ankur> main.cpp:(.text+0x2f7): undefined reference to `mlpack::util::PrefixedOutStream::operator<<(char const*)'
< ankur> main.cpp:(.text+0x304): undefined reference to `mlpack::util::PrefixedOutStream::operator<<(std::ostream& (*)(std::ostream&))'
< ankur> main.cpp:(.text+0x30e): undefined reference to `mlpack::Log::Warn'
< ankur> main.cpp:(.text+0x313): undefined reference to `mlpack::util::PrefixedOutStream::operator<<(char const*)'
< ankur> main.cpp:(.text+0x320): undefined reference to `mlpack::util::PrefixedOutStream::operator<<(std::ostream& (*)(std::ostream&))'
< ankur> main.cpp:(.text+0x32a): undefined reference to `mlpack::Log::Fatal'
< ankur> main.cpp:(.text+0x32f): undefined reference to `mlpack::util::PrefixedOutStream::operator<<(char const*)'
< ankur> main.cpp:(.text+0x33c): undefined reference to `mlpack::util::PrefixedOutStream::operator<<(std::ostream& (*)(std::ostream&))'
< ankur> main.cpp:(.text+0x346): undefined reference to `mlpack::Log::Warn'
< ankur> main.cpp:(.text+0x34b): undefined reference to `mlpack::util::PrefixedOutStream::operator<<(char const*)'
< ankur> main.cpp:(.text+0x358): undefined reference to `mlpack::util::PrefixedOutStream::operator<<(std::ostream& (*)(std::ostream&))'
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< kirizaki> ok, do You add -lmlpack while compiling?
< ankur> while compiling program?
< kirizaki> yes
< kirizaki> i.e.:
< ankur> no I used g++ -std=c++11 main.cpp
< kirizaki> exactly
< kirizaki> You should add -lmlpack
< kirizaki> g++ main.cpp -lmlpack -std=c++11
< ankur> yes now its compiles
< kirizaki> great!
< kirizaki> happy to help You :)
< ankur> but what was the problem and how would I know that I had to use -lmlpack?
< Nilabhra> kirizaki: thanks will get on to it
< kirizaki> the problem was You didn't say to linker that he must use mlpack library
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< ankur> ya I got that'
< kirizaki> implementations
< ankur> thanks a lot kirizakiv:)
< kirizaki> no problem ;)
< kirizaki> btw. next time You should paste Your log to www.pastebin.com
< kirizaki> it's easier to read ;)
< ankur> yes sure. :D
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< tafodinho> hello everyone am a computer engineering student who wish to participate in the 2016 GSoC program with mlpack as my mentoring organization please hw do i get started
< rcurtin> tafodinho: have you read http://www.mlpack.org/involved.html?
< tafodinho> rcurtin: not yet. i should get on to it now
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< tafodinho> rcurtin: please how to i install this dependency on ubuntu 15 ''Armadillo''
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< rcurtin> tafodinho: you need to install the armadillo-dev package
< tafodinho> rcurtin: ok please i have tried but failed hw do i do it please
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< mentekid> tafodinho: have you tried sudo apt-get install libarmadillo-dev? That worked for me
< tafodinho> mentekid: thanks
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< tafodinho> please i have this error when i run cmake http://pastebin.com/dSk63Lt5 can anyone help with with it
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< mentekid> tafodinho: are you following the readme? have you created the build directory, cd into it etc?
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< dixitshaunak> Hey I'm new here can anyone help me get started on how to contribute.
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< tafodinho> mentekid: please hw do i nw install the boost libraries
< wasiq> dixitshaunak, welcome.. go through this http://www.mlpack.org/involved.html? its a starting point.
< dixitshaunak> ok thanks a lot sir
< wasiq> cheers
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< wasiq> tafodinho, are you running ubuntu or linux?
< wasiq> tafodinho, http://www.mlpack.org/doxygen.php?doc=build.html install all the packages listed under "dependencies of mlpack"
< tafodinho> wasiq: ok thanks
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< wiking> rcurtin: ping ping
< wiking> i see you have the gsoc fever here as well :)))
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< rcurtin> wiking: yep, lots of interest :)
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< wiking> rcurtin: can you remind me of the benchmark fw? :)
< wiking> where can i find it :)
< rcurtin> the repo is at https://github.com/zoq/benchmarks
< rcurtin> the paper we got into a NIPS workshop is at http://ratml.org/pub/pdf/2014automatic.pdf
< wiking> nips ws :D
< wiking> nice :)
< rcurtin> and some benchmarks are at https://www.mlpack.org/benchmarks.html (for a preselected benchmark or two)
< rcurtin> and then the interactive interface at http://www.mlpack.org/benchmark.html
< rcurtin> oops, that link to the preselected one should be http not https
< rcurtin> thanks :)
< rcurtin> I think that all the benchmarks need to be run again for new versions of mlpack and other libraries, but our build server setup is in a state of transition right now
< wiking> mmm
< wiking> i was just about to ask
< wiking> what is the version
< wiking> of the libraries
< wiking> ?
< wiking> is that the version?
< wiking> *are the versions of libs
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< zoq> wiking: yeah, but I'm not sure we actually used that version ...
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< rcurtin> yeah, let me try and figure out what the versions were for the displayed benchmarks
< wiking> cool
< wiking> thnx
< wiking> we are thinking about extending
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< wiking> and setting up a buildbot for it
< rcurtin> absolutely, that would be great
< rcurtin> sooner or later I will have some dedicated systems for benchmarking that will be able to get accurate numbers
< wiking> :)
< wiking> cool
< wiking> do we have option for mem bechmarking?
< rcurtin> but I am waiting on my company to set up the build servers correctly first...
< rcurtin> yeah, I think it uses massif... I don't remember the configuration options offhand, maybe zoq does
< wiking> zoq: can you bootstrap me on this? :)
< rcurtin> I'm looking on our build system, I think that the benchmarks you're looking at were done with shogun 3.2.0
< rcurtin> I can see that the command used was this:
< rcurtin> make CONFIG=config.yaml BLOCK=shogun LOG=True run PYTHONPATH=/opt/scikit-learn/scikit-learn-0.13.1/lib/python3.3/site-packages/:/opt/mlpy/mlpy-3.5.0/lib/python3.4/site-packages/:/usr/local/lib/python3.4/dist-packages/ MS_PRINT_BIN=/usr/bin/ms_print VALGRIND_BIN=/usr/bin/valgrind LD_LIBRARY_PATH=/usr/local/lib/ LIBRARY_PATH=/usr/local/lib/ UPDATE=False
< rcurtin> but that only specifies versions of other libraries and doesn't seem to specify the shogun version... so my guess is that the config.yaml you linked to before is the version that was used
< wiking> kk
< wiking> so yeah we need updates :)
< wiking> we should create a dedicated site for this
< wiking> benchmarks.ml
< wiking> :)
< wiking> and generate there the outputs
< zoq> wiking: yeah, right, we use massif to run a memory benchmark for mlpack ... but it should be straightforward to run memory benchmarks for the rest of the libs ... I'm here to help you out :)
< rcurtin> this would definitely be possible, and the existing benchmarking system would be good for this
< rcurtin> I'm happy to supply dedicated benchmarking systems, but it'll be a little while until I can do that
< wiking> that's alright
< wiking> i'll put together couple of bots
< wiking> and i'll ping if i'm stuck
< rcurtin> one of the problems with using something like EC2 for benchmarking is that it'll be a VM running on a system that's running lots of other VMs, so depending on the load of the whole system, you may get noisy benchmarks
< wiking> thanks so much for the help
< wiking> aws is a shit :)
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< rcurtin> sure, I'm happy to help if you have any issues :)
< wiking> i mean for benchmarking
< rcurtin> yeah
< wiking> those fake qemu things
< zoq> :)
< wiking> sometimes dont even have the power they say they have
< wiking> did some benchmarks
< rcurtin> it's really nice because it's free for open-source projects (at least some amount is), but you can't really use it for benchmarking or timing
< wiking> actually rackspace is giving you much better vps
< wiking> free?
< wiking> aws is free for open source?: )
< wiking> yeah we have some dedicated machines
< wiking> found that to be the most cost efficienct solution
< rcurtin> I thought AWS was free for some open-source use, I forget
< rcurtin> I don't remember, that was years ago I think
< rcurtin> could be different now :)
< wiking> ah dunno
< wiking> never used it for such purposes
< wiking> anyhow
< rcurtin> neither did I, I think I just read it somewhere
< wiking> let's see how we can get some nice updates on this :)
< rcurtin> yeah, I have always wanted to put more time into this project but never had the time
< wiking> hehehe
< rcurtin> there's a lot of potential for a really slick setup :)
< wiking> yeah time time
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< mizari> <wiking> nice :)
< mizari> sorry, some copy-paste HexChat error
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< travis-ci> mlpack/mlpack#594 (master - d5841b1 : marcus): The build was broken.
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< kirizaki> zoq: I'm filling little bit better
< kirizaki> could I use tomorrow Your FreeBSD?
< kirizaki> or even tonight, just for a while tonight, to check what else should I do to make mlpack work
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< rcurtin> ah right we should check that on FreeBSD before I merge it in
< rcurtin> it's tested on OS X (I tested it), and I guess we can test on Windows with AppVeyor once it's merged in
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< kirizaki> ok, let's wait then on zoq, he wanted to prepare FreeBSD, soo we can test it and then merge it
< rcurtin> sounds good
< rcurtin> the code looks great to me, thanks again for going to all the work to write it and test it :)
< kirizaki> nah
< kirizaki> it wasn't so difficult :P
< kirizaki> it took some time due to that I had plenty work with plenty interviews xD
< rcurtin> :)
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< palashahuja> zoq, I have been trying to run the tests
< palashahuja> But I just can't get it seem to run for dropconnect ...
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< zoq> kirizaki: Nice to hear that you feeling better. Haven't had time to configure the system, probably tomorrow. Anyway, I tested the code on FreeBSD and it builds without any problems.
< zoq> palashahuja: Hello, can you point me to the test you are using?
< palashahuja> Sure, I will create the gist if you'd like
< zoq> palashahuja: Sounds good.
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< zoq> palashahuja: You can't build the code using the test right? Or did you get unexpected results?
< palashahuja> yes ..
< palashahuja> The implementation seems correct ..
< zoq> So unexpected results?
< palashahuja> yes
< zoq> okay
< zoq> Can you show me the rest of the test, I can't see the dataset you are using.
< palashahuja> Sure ..
< palashahuja> it is the thyroid dataset from feedforward_network_test file ..
< palashahuja> very similar to the dropout network test
< zoq> ah, okay
< kirizaki> zoq, but You build it after I put CMAKE_SYSTEM_NAME ?
< zoq> kirizaki: ah, let me check that in a couple of minutes or hours
< kirizaki> ok
< kirizaki> I'm out for today
< kirizaki> bye!
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< zoq> palashahuja: Can you point me to the DropConnectLayer code?
< zoq> palashahuja: Perfect, thanks!
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< rcurtin> zoq: if it works on freebsd, feel free to go ahead and merge the PR (or let me know and I'll merge it)
< rcurtin> ideal output should be that it compiles, and there's nothing about libbfd or libdl in the cmake output
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< zoq> palashahuja: Are you sure this is the latest version? I can't compile the code.
< zoq> rcurtin: okay, I'll check that later.
< palashahuja> what's the error ?
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< zoq> palashahuja: "no matching function for call to 'randu'" -> mask = arma::randu < arma::Cube < eT > > (baseLayer.Weights().n_rows, baseLayer.Weights().n_cols);
< zoq> palashahuja: That's just one error. I can fix everything, but maybe I don't have to do that.
< palashahuja> that should be Mat instead of cube
< palashahuja> My bad ...
< palashahuja> I'll update the code
< zoq> palashahuja: Another error is: "dropconnect_layer.hpp:141:17: error: no matching member function for call to 'Backward'" -> baseLayer.Backward(gy, g);
< palashahuja> I am sending the updated code ..
< zoq> palashahuja: okay, great.
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< travis-ci> mlpack/mlpack#597 (master - fd84f3a : marcus): The build was fixed.
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< palashahuja> zoq,
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< palashahuja> I think this one works ! :)
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< zoq> palashahuja: Yeah, once you modify the LayerTraits to use the DropConnectLayer instead of DropoutLayer it builds.
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< travis-ci> awhitesong/mlpack#10 (LeakyReLU - 611eeb6 : Dhawal Arora): The build was fixed.
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