verne.freenode.net changed the topic of #mlpack to: http://www.mlpack.org/ -- We don't respond instantly... but we will respond. Give it a few minutes. Or hours. -- Channel logs: http://www.mlpack.org/irc/
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< adam__> i have build mlpack and installed it on my system. I am at the input and output tab in tutorials. can anyone tell me what command should I type to run the simple logging example.
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< adam__> Hi
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< nilay> Hi
< nilay> I need some help.
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< juanmont> hi
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< zoq> nilay: Hello, we are here to help :)
< Jayaganesh> Hi sir,
< Jayaganesh> I'm very much interested in working @ "Approximate Nearest Neighbor Search"
< Jayaganesh> My mail to march@gatech.edu has failed. could somebody help me on how to reach him?
< Jayaganesh> Further could somebody help me on how to start off with the same?
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< nilay> hello zoq, I am trying to compile a sample mlpack program, but when I compile it I am getting errors like undefined reference to `mlpack::CLI::ParseCommandLine(int, char**)'
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< nilay> I have compiled and installed mlpack successfully. But can you guide me, how should I compile a sample program like the one given here: http://www.mlpack.org/doxygen.php?doc=iodoc.html
< zoq> nilay: Can you show me the command you used to compile?
< nilay> g++ -I/usr/include/libxml2 1.cpp
< nilay> this is because I was first getting error of not including libxml2.
< zoq> oh, do you use an older version of mlpack?
< nilay> i have tried adding to my CPLUS_INCLUDE_PATH the following: /usr/local/include/mlpack
< zoq> something like that: g++ foobar.cpp -o foobar -lmlpack -std=c++11
< zoq> since version 2.0.0 you don't need to link against libxml, but mabye you use an older version of mlpack
< nilay> yes i think i downloaded 1.0.12 version
< zoq> Can you download and build the latest version?
< nilay> Yeah sure. and yes I can get the sample program to work now by giving the libxml2 path. Thanks :)
< nilay> one more thing I wanted to ask, I have to give this command export LD_LIBRARY_PATH=/usr/local/lib/ , everytime i want to run a program. Is there any way around this?
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< nilay> and do i have to remove this version before downloading and installing the new one?
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< zoq> Add LD_LIBRARY_PATH to your runtime linker search path e.g. by setting export LD_LIBRARY_PATH=/usr/local/lib/ in your .bashrc file.
< zoq> You can just build/install the new version.
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< nilay> ok thank you.
< zoq> You should probably delete the mlpack binaries in your path. Instead of e.g allknn the binary is now mlpack_allknn.
< nilay> how can I do that?
< zoq> e.g. rm /usr/local/bin/allknn
< nilay> and I'll have to do this for all the binaries separately?
< zoq> Unfortunately yes, if you are using the new naming schema you could use 'rm mlpack_*''
< nilay> ok.
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< nilay> zoq, can you also tell me what things should I start reading up on, if I want to submit a gsoc proposal on a project related to deep learning?
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< zoq> nilay: I'm not sure I can recommend something without knowing what you like to do. I guess a good first step would be to discuss with us your idea :)
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< nilay> I am interested in "Essential Deep Learning Modules" or "We need to go deeper - GoogLeNet" Project. I am not sure which one, as of now. I am familiar with neural nets as I have taken an introductory class on ML in our college, and one coursera class. What do you think should be my next step given I want to do any one of these projects?
< ranjan123> hii
< ranjan123> Is there anybody to help me out about the src code ?
< ranjan123> ranjan@ecsulab1 ~/gsoc/mlpack/src/mlpack $ ls bindings CMakeLists.txt core core.hpp methods prereqs.hpp tests
< rcurtin> ranjan123: I am only here for a minute so I can't help for too long
< rcurtin> you asked where to find the SGD implementation... look in src/mlpack/core/optimizers/sgd/
< rcurtin> (or src/mlpack/core/optimizers/minibatch_sgd/ for mini-batch SGD)
< ranjan123> yes.. thanks . let me check it out
< rcurtin> I have to go now, I will be back later
< ranjan123> ok
< ranjan123> :)
< rcurtin> you might also consider taking a look at the doxygen documentation:
< rcurtin> that may be helpful for figuring out what is in the codebase
< ranjan123> hmm
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< zoq> nilay: Ah, okay I thought you would like to propose a new project idea. I've responded to a mail on the maillinglist that contains a bunch of papers and links you can read to get a better understanding about the essential network modules idea
< zoq> nilay: A good way to start with the "we need to go deeper" idea, is to read the paper mentioned in the project description.
< nilay> ok thanks. :)
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< arkham> I am interested in working for mlpack through GSOC, please provide me list of easy bugs to start with
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< Jayaganesh> could anybody help me on how to go about in "Approximate Nearest Neighbor Search" proj.
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< zoq> Jayaganesh: It's probably a good idea, to write on the mailing list, you could also wait for rcurtin to get back
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< rcurtin> Jayaganesh: I'll respond to your email in a little while
< rcurtin> lots of emails to respond to so there is a little lag, sorry about that :)
< zoq> rcurtin: Is there an easy way to tell CMake to build against C++14, I've modified the CX11.cmake file, to use C++14 instead of C++11? I'm not going to change that, just wanted to reply to one the issues.
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< Jayaganesh> Sure sir. thanks
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< rcurtin> zoq: do we require C++14 features to compile now?
< rcurtin> probably modifying CXX11.cmake to CXX14.cmake is the easiest way to do it
< rcurtin> but it's probably also worth checking that whatever C++14 support is needed is supported by Visual Studio so that people can compile on Windows
< serban_M> Hi all
< rcurtin> serban_M: hello
< serban_M> I was trying to make a build and I noticed that the option "PROFILE=(ON/OFF): compile with profiling symbols" exists
< rcurtin> zoq: it seems like VS2015 has a good handful of C++14 features, hopefully that is good enough
< rcurtin> I wouldn't worry about earlier than VS2015, I think VS2013 doesn't compile mlpack anyway
< serban_M> at least that the doc says, so profiling is done at compile time or not? :D cause I noticed this as a gsoc project and it looked interesting
< zoq> rcurtin: No, but sudarshan85 (#531) builds against mlpack using some C++14 features so I was wondering what's the easiest way for me to test something out.
< rcurtin> zoq: okay, yeah, probably just changing line 45 of CXX11.cmake is the easiest thing
< rcurtin> serban_M: the "PROFILE" option means that all mlpack programs will be compiled with -pg
< rcurtin> so that you could use something like gprof or other profilers to find when things are slow
< rcurtin> the project (which I don't think is still listed, I think maybe it was too easy) was something a little different
< rcurtin> I think there's a github issue open, so if you take a look, you can find some more details there
< rcurtin> probably searching for "profiling" in the issues will give the right results
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< serban_M> yep, found it, thx :D
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< rcurtin> kirizaki: indeed, I don't think there have ever been this many people in the channel
< rcurtin> oh
< rcurtin> well that's stupid
< rcurtin> I responded to a message while scrolled way back in my scrollback buffer :)
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< wasiq> hey people. while i was building mlpack i got this error.
< wasiq> ARMADILLO_INCLUDE_DIR-NOTFOUND/armadillo_bits/config.hpp not found!
< serban_M> get armadillo devel package
< wasiq> i checked the dependencies i need and it wasnt in that
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< rcurtin> wasiq: it looks like you don't have Armadillo installed or configured correctly
< wasiq> Oh right. Yeah i got the mistake. Super silly.
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< palashahuja> hello
< palashahuja> Since you guys follow a certain coding style as per your documents, is there any tool (similar to pep8) for coding conventions ?
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< rcurtin> palashahuja: I think some time back someone made a configuration of something like cpplint or something to do that, but I forget where it is
< rcurtin> maybe somewhere on github if you searched?
< rcurtin> I'm sorry I can't be more helpful than that
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< travis-ci> mlpack/mlpack#555 (master - 1bedf15 : Marcus Edel): The build was fixed.
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< palashahuja> rcurtin: maybe I could create tool if you'd like
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< rcurtin> palashahuja: you should look through github to see what others have done in the past
< rcurtin> I'm sure someone did something, I just can't remember who or where it is
< rcurtin> maybe it was stereomatchingkiss who did it? I am not sure though
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< rcurtin> oh, there it is! I should have just looked... https://github.com/mlpack/mlpack/issues/420
< rcurtin> that's the ticket that was originally referenced, and then I think somewhere else someone mentioned they wrote a script to do it
< rcurtin> that's the part that I don't remember :(
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< palashahuja> oh .. okay ..
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< palashahuja> It will be really wonderful if you could add the reference to the cpplint code in the github docs .. so it is easier for new comers to write adaptive code
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< palashahuja> rcurtin: I am planning to solve issue #443 https://github.com/mlpack/mlpack/issues/413
< palashahuja> According to me, the weights have to be zeroed out, corresponding to each connection for dropconnect.
< palashahuja> But this can be accomplished during the training phase, (I am sorry I am being stupid right now)..
< zoq> palashahuja: No you are not stupid, you are absolutely right. DropConnect is a generalization of Dropout. Dropout drops entire rows or columns of the weight matrix. DropConnect is more fine grained and drops individual weight matrix elements.
< zoq> palashahuja: So, I guess you can create a new DropConnectLayer which takes another layer as input and then drop (set to 0) random weights.
< palashahuja> zoq: Ok, got it ... :) ..
< palashahuja> Also, please do something about the code static analysis tool ..
< palashahuja> If necessary, I could write it ..
< rcurtin> palashahuja: I'll see if I can find that post I was referencing but it may take a few days and I may not find it
< rcurtin> I always look over contributions to make sure the style is right, so it's never any problem to fix simple issues
< rcurtin> we won't reject a PR if its style is wrong, we'll just fix it. no need to throw away good code if it works and is well documented :)
< palashahuja> rcurtin: do you manually analyse the code ? Which tool do you use btw ?
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< travis-ci> mlpack/mlpack#557 (master - bb8507c : marcus): The build has errored.
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< rcurtin> palashahuja: I check all code in all PRs manually; static analysis tools can be nice, but if you don't look over every line of the code then it's easy to miss subtle bugs
< palashahuja> ok cool ..
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< ach_> #KLUG
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< ach_> hi everyone
< zoq> rcurtin: any idea, why jenkins didn't build the latest version?
< kirizaki> hi
< zoq> ach_: Hello
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< anveshi> hello everyone :)
< anveshi> I am getting this error while compiling second code (Nearest Neighbor) from
< anveshi> /usr/bin/ld: /tmp/ccT3jpVt.o: undefined reference to symbol '_ZTIN5boost13serialization13typeid_system27extended_type_info_typeid_0E'
< anveshi> /usr/lib/x86_64-linux-gnu/libboost_serialization.so.1.54.0: error adding symbols: DSO missing from command line
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< anveshi> any idea, What went wrong ?
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< zoq> anveshi: Can you show us the command you are using to build the code?
< anveshi> g++ A.cpp -lmlpack -larmadillo -lboost_program_options
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< travis-ci> mlpack/mlpack#561 (master - 8ffa470 : marcus): The build passed.
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< zoq> anveshi: Does this work: g++ A.cpp -llmlpack -std=c++11?
< anveshi> no, i have already aliased g++ as 'g++ -std=c++11' in .bashrc
< zoq> the same output?
< anveshi> yes same error
< zoq> can you link against -lboost_serialization
< anveshi> Wow ! It worked
< anveshi> Thanks :)
< zoq> anveshi: Glad it worked :)
< anveshi> I should have asked earlier was struggling from 3-4hrs
< zoq> Maybe next time :) we are here to help, "We don't respond instantly... but we will respond."
< anveshi> for sure
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< wasiq> Is there a specific place i should save my *.csv input file in,or can i save it in the base mlpack directory?
< rcurtin> wasiq: your datasets can be anywhere you like
< wasiq> i just need to reference it if its outside the mlpack directory then?
< zoq> asiq: right
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< wasiq> rcurtin, im interested in the parallel stochastic optimization methods idea,where would you suggest i begin?
< wasiq> i found a couple of papers on SGD AND SCD.