mlpack IRC logs, 2017-03-20

Logs for the day 2017-03-20 (starts at 0:00 UTC) are shown below.

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--- Log opened Mon Mar 20 00:00:49 2017
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11:25 < vss> anyone applying for mlpack through gsoc ?
11:28 < Trion> yeep! :D
11:28 < vss> What are you planning to work on ?
11:29 < Trion> Reinforcement Learning project, more precisely the algorithms
11:29 < vss> cool , i want to work on augmented rnn , more precisely the neural turing machine :D
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11:30 < Trion> nice! :-)
11:31 < vss> wonder if ill get in tho :/
11:33 < Trion> tay motivated to learn and give a nice honest proposal :-) And ofcourse interact with community
11:34 < Trion> stay*
12:15 < diehumblex> hi i want to create sentiment analyser using nlp. can mlpack help here?
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14:08 < rcurtin> diehumblex: I am not sure that mlpack implements many components that would be useful for NLP, so I don't know if mlpack would be the best choice
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14:08 < rcurtin> but I am also not too familiar with NLP or sentiment analysis, so maybe it is possible that there are some parts of mlpack could be useful
14:09 < diehumblex> rcurtin : Thanx
14:16 < mikeling> rcurtin: hey
14:16 < mikeling> thank you for the review :)!
14:19 < rcurtin> sure, it isn't comprehensive
14:19 < rcurtin> many more reviews to do today...
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15:19 < sagarbhathwar> Hi, I had a small doubt. When two functions share some common functionality, is it a good idea to write a private method to abstract that functionality from the two methods?
15:20 < rcurtin> sagarbhathwar: that depends a lot; what is the functionality in question?
15:22 < diehumblex> I would like to propose sentence structure analyser as a gsoc project. it would extend mlpack's support towards language processing. would it be of interest to mlpack ?
15:23 < sagarbhathwar> Say in softmax regression, I am writing an overload for Classify which computes probabilities for input dataset. Then again, the other overload of Classify Computes probabilities + uses it to classify the data points. So, a private method ComputeProbabilities sounds like an abstractions for the two methods.
15:24 < rcurtin> sagarbhathwar: why not just call the other overload of Classify()?
15:24 < rcurtin> diehumblex: you are welcome to submit a proposal about that, but be careful that you have fully thought through what the API will be and how it will fit in mlpack
15:25 < rcurtin> we need to make sure that new support to the library is well-integrated with other support, so that it doesn't feel like mlpack is many separate libraries that are all included together :)
15:25 < sagarbhathwar> rcurtin: Sure, I could do that. Just wanted to make sure it is okay to call Classify from within Classify?
15:25 < rcurtin> yes, I'm not sure why that wouldn't be okay
15:25 < sagarbhathwar> Great then :)
15:27 < diehumblex> rcurtin: who could possibly mentor this proposal ? i would like to thoroughly discuss it.
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15:30 < rcurtin> diehumblex: that would be the next problem, you would have to find a mentor. I certainly don't have time; I am not sure if anyone else does
15:35 < diehumblex> rcurtin: so all present mentors are already occupied and no new mentor can join. guess should have come earlier.
15:35 < rcurtin> diehumblex: something as different as 'adding NLP support' would have always been a long shot anyway, since it requires a huge amount of time figuring out how its API can match the rest of mlpack
15:36 < rcurtin> it's possible there may be some possible mlpack contributor would would be interested in mentoring this, but like I said I personally don't have time to mentor that
15:40 < diehumblex> Hi if anyone got interested in my proposal and would like to be mentor please let me know.
15:41 < Trion> diehumblex, have you looked into cltk organisation?
15:42 < Trion> They are based on nlp, so they will be able to provide a mentor much easily
15:44 < diehumblex> yes actually they are in python and what i proposed they already have it
15:51 < Trion> hmm.. I see, the parts of speech code shows they have support for just greek and latin at the moment and one of their project idea is to extend CLTK core to new languages.
15:55 < Trion> For mlpack, you can leave a mail in mailing list and mentors can discuss if there is a possibility for nlp in mlpack/ nlpack! :D
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15:58 < Nax> zoq: Hi, I have researched on nuget package,
15:59 < Nax> I found that, we ll need one more file (mlpack.nuspec) if we want to add automatic integration with appveyor
15:59 < Nax> It would be quite easy to integrate mlpack with nuget using appveyor
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16:05 < zoq> Nax: Yeah, it's a pretty streamlined process, I think we can still use the jenkins repo to provide the all files including the nuspec file and load all files in the build process. There is one problem I see, if we use appveyor for the package creation, how can we controll that it's not creating a new package for every PR?
16:06 < diehumblex> Trion : my bad i was talking about nltk :)
16:07 < Nax> zoq: I guess, standard method would publishing only specific branch instead of master branch
16:07 < diehumblex> cltk also looks like is in python
16:08 < Nax> besides we can also provide nightly build (pre-release) and stable release would be from specific branch
16:09 < zoq> Nax: Okay, if that works, that would be really nice.
16:14 < Nax> zoq: but still as mentioned in #919, we still need nuget for armadillo, or can we include its files in nuget for mlpack?
16:15 < Trion> diehumblex: yes it is :-) and quite similar
16:18 < zoq> Nax: I would prefer to create an independent nuget package for armadillo and use that as dependency for the mlpack package.
16:20 < Nax> zoq: ok got it, Thanks for the help!
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17:18 < vss> hi ! does anyone know what are the necessary fields for the proposal draft (Gsoc) ?
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17:21 < Trion> vss: checkout Mlpack's application guide at https://github.com/mlpack/mlpack/wiki/Google-Summer-of-Code-Application-Guide
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17:37 < yaing> Hey, guys. I'm just getting started with mlpack. Can someone tell me how can I work on mlpack codebase in codeblocks ide?? I like to do c++ development in codeblocks. Thanks
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17:42 < Trion> yaing: are you on linux or windows?
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17:44 < yaing> I'm on linux ubuntu
17:44 < Trion> checkout http://www.learncpp.com/cpp-tutorial/a3-using-libraries-with-codeblocks/
17:47 < yaing> Thank you but its for windows. i have installed mlpack on my ubuntu desktop
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17:48 < Trion2> damn my internet.. crashes more than it works :P
17:49 < Trion2> is codeblocks interface very different in windows and ubuntu?
17:50 < yaing> interface not so much but may be paths will be different
17:50 < yaing> and i don't know how to load mlpack codebase in codeblocks :(
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17:52 < Trion3> The article seems to cover linux part too
17:52 < Trion3> the path will be something like /usr/local/include
17:52 < yaing> okay, i will try that
17:53 < yaing> can also tell me how to load the mlpack codebase in it? I want to make changes to some files and then push them in my fork on github. Is that possible?
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17:57 < yaing> does anyone use codeblocks here? Please help
18:02 < zoq> yaing: I'm pretty sure if you search for codeblocks and probably cmake you will find something helpful,; mlpack doesn't do anything special, when it comes to the project configuration.
18:05 < yaing> okay thank you zoq. i'll try to find something
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19:35 < pvskand> Can anyone tell me how to run the convolutional_network_test.cpp ?
19:37 < zoq> pvskand: bin/mlpack_test -t ConvolutionalNetworkTest
19:38 < pvskand> Thanks
19:40 < pvskand> In this issue https://github.com/mlpack/mlpack/issues/922 its mentioned that VanillaNetworkTest is failing in convolutional_network_test.cpp
19:40 < pvskand> Does that mean when you run bin/mlpack_test -t ConvolutionalNetworkTest, you dont pass the test?
19:42 < zoq> pvskand: Yes, since we use random parameters and a fixed number of iterations it's possible that the network does not converge for the current setting, so sometime the test fails.
19:51 < pvskand> I have ran the test 25 times and I find it to pass all the time! Since in cnn the weights are randomly generated, I do agree that the results might sometime fail. But it should not fail frequently right?
19:57 < zoq> pvskand: Right, not frequently, also remember to set math::RandomSeed(std::time(NULL)); if you test it multile times, so that it uses a new seed for each run: https://github.com/mlpack/mlpack/issues/922
19:59 < pvskand> Yeah! I am running the test again via shell script, so since the initial seed it set to NULL, every time I run the script it is set to null!
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20:57 < kris1> zoq: could you have a look at https://github.com/mlpack/mlpack/pull/939
20:58 < kris1> i don't understand why the appveyor test is failing
20:58 < kris1> thanks
20:58 < rcurtin> kris1: try searching for the string 'error ' in the appveyor build log
20:59 < rcurtin> the trailing space there is important to actually find the error message in the build
20:59 < rcurtin> that log is way too long to read... it's often like 100kb+ :)
20:59 < kris1> Yes it is thats..............any ways i will look for it
20:59 < kris1> thansk @rcurtin
21:00 < rcurtin> yeah, usually once you have the actual error message it makes it a lot easier to figure out what is going wrong
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21:15 < travis-ci> mlpack/mlpack#2103 (master - 62dce7a : Ryan Curtin): The build was fixed.
21:15 < travis-ci> Change view : https://github.com/mlpack/mlpack/compare/8b671eaf0612...62dce7acf424
21:15 < travis-ci> Build details : https://travis-ci.org/mlpack/mlpack/builds/213152761
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21:32 < travis-ci> mlpack/mlpack#2104 (mlpack-2.2.x - 6f2601b : Ryan Curtin): The build passed.
21:32 < travis-ci> Change view : https://github.com/mlpack/mlpack/compare/3c0a56c2080b^...6f2601bb4055
21:32 < travis-ci> Build details : https://travis-ci.org/mlpack/mlpack/builds/213157579
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21:41 < travis-ci> mlpack/mlpack#2105 (master - e46c0ec : Ryan Curtin): The build was fixed.
21:41 < travis-ci> Change view : https://github.com/mlpack/mlpack/compare/62dce7acf424...e46c0ec72950
21:41 < travis-ci> Build details : https://travis-ci.org/mlpack/mlpack/builds/213161714
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22:01 < chvsp> Hi zoq: I have completed the implementation of the BatchNorm Layer. I was writing tests for the same. Can I hardcode the input and the expected output values? I have got a python implementation of this layer and I gave both, random inputs and have compared the various parameters. Would this be a valid test?
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22:05 < zoq> chvsp: Sounds like a reasonable test as long as the python code is correct; we should also think about some other tests, but in this case it's not that easy to come up with something really useful.
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22:09 < chvsp> zoq: I got the implementation here - http://cthorey.github.io./backpropagation/ . I have crossed checked it with the theoretical formulae. I agree that we need to have some other tests but I guess these will suffice for the interim.
22:11 < zoq> chvsp: I agree, that is a good start, if you like open a PR and we can look over the code.
22:12 < chvsp> Writing the tests will take some time? Would you like me to open the PR with the implementation?
22:12 < chvsp> *time.
22:13 < zoq> Take your time to write the test, no need to open the PR without the test.
22:14 < chvsp> Okay :)
22:21 < chvsp> zoq: To check the equality of two matrices, is it sufficient to check if the sum of all elements are equal in both? This was used in almost all of the ann layer tests.
22:23 < zoq> chvsp: Depending on the matrix that is something you could do, probably a better way is to use CheckMatrices from the test_tools file.
22:26 < chvsp> Oh nice function. I will try to use that :)
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--- Log closed Tue Mar 21 00:00:51 2017