mlpack IRC logs, 2017-03-04

Logs for the day 2017-03-04 (starts at 0:00 UTC) are shown below.

March 2017
--- Log opened Sat Mar 04 00:00:27 2017
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06:56 < NarayanSrinivasa> Hello people . I went through the ideas list and quite a few intrigued me , Deep Learning , Reinforcement Learning the most.But i feel i can try adding the Cross Validation Feature back to ML-Pack . There are no readings given in ideas page
06:57 < NarayanSrinivasa> I am not new to ML and i have already completed the Andrew Ng Course and did a project in BioInformatics.
06:58 < NarayanSrinivasa> Could someone tell me what all aspects i should be familiar with to contribute to this project.I have compiled ML-Pack from source and implemented a few simple programs to familiarise myself
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09:41 < rob> hi
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14:27 < zoq> kris: HasParametersCheck<T, P&(T::*)()>::value is a Type Trait and combined with SFINAE really powerfull.
14:27 < zoq> T is the type of the object we like to test against and P&(T::*)() is the function definiton e.g. in this case we like to figure out if for example the a given layer has a Parameters function.
14:27 < zoq> How does the Parameters() function look like: 'OutputDataType& Parameters() { return weights; }' so, let me write the expression a little bit different:
14:27 < zoq> RETURNTYPE_OF_FUNCTION(T::*)(FUNCTION_ARGUEMTNS)::value, RETURNTYPE_OF_FUNCTION = OutputDataType& and since the Parameters function has no arguments it's empty.
14:27 < zoq> Another example let's say we like to figure out if the given object has double& Alpha(const size_t a, double b) { return alpha; } the trait looks like: HasAlphaCheck<T, double&(T::*)(const size_t, double)>::value; RETURNTYPE_OF_FUNCTION = double&, FUNCTION_ARGUEMTNS = const size_t, double.
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14:45 < zoq> kris: See my comments on the gist.
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14:58 < zulfiqarjunejo> Hello
14:59 < zoq> zulfiqarjun: Hello there!
15:00 < zulfiqarjunejo> how are you zoq?
15:01 < zulfiqarjunejo> I am here looking for mailing list for GSoC 2017. Can you guide me what to write in subscription email?
15:02 < zoq> We are talking about:
15:04 < zulfiqarjunejo> Oh yes. Earlier when I went to mailing list from GSoC, it redirected me to 'mailto:....'
15:04 < zulfiqarjunejo> Thanks zoq :)
15:05 < zoq> ah, I see, yeah, you have to subscribe first to be able to send a mail to the list.
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17:06 < chvsp> Hi zoq, as I asked you yesterday about adding a batchnorm layer, I was wondering about how would we proceed to write tests for it. As I have read that the effect of such a layer is only prominent in deep networks with several layers. It is not possible for us to train a large network in the test module.
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17:15 < zoq> chvsp: I can think of two test right now: 1. Test that checks the gradient; 2. We can use a pre trained network and run it only for a number of iterations, and see if the error changes over time.
17:33 < chvsp> zoq: 1. The gradient wouldn't be deterministic, as we choose a random minibatch everytime. Are you hinting at taking the same minibatch everytime?
17:34 < zoq> Yeah, we have to make it deterministic, but that should be a problem.
17:37 < chvsp> Right. Then we would have to engineer this batches to cater to every corner case I guess.
17:37 < chvsp> *these batches
17:40 < zoq> We can start with a simple example, but I agree creating an worst case input would be even better.
17:51 < chvsp> Cool, I will look into it.
17:52 < chvsp> Could you please review my PR about the Kathirvalavakumar Subavathi tests. It would be great if it is merged.
17:54 < zoq> I agree that would be great, I'm trying to review a couple of PR's later today.
17:55 < chvsp> Sure. Whenever you are free. :)
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18:08 < chvsp> zoq: About the PR review, can we as participants, contribute to the review in any way to reduce the burden on you? If any, do let us know, will be happy to help.
18:23 < zoq> chvsp: It's definitely not a burden; what we like to do is to give everyone helpful comments or start a discussion over code parts that could be tackled differently, etc. and that sometimes takes some more time as pointing out failures without any direction to solve the issue.
18:24 < chvsp> zoq: Cool, just a random thought...
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18:29 < supertramp-sid> Hello guys, I wanted to ask doubt regarding GSOC'17 . I want to work on mlpack on the cross-validation and hyper-parameter tuning module. As suggested I will look into the current code base. I wanted to ask you if you had any suggestion on how should I go about drafting a simple proposal that you guys would prefer to see. Thanks.
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20:44 < kris1> zoq:is there a way to build only ann
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20:55 < shihao> Hi there!
20:56 < shihao> If I make some changes in one of tests, I have to rebuild 'mlpack_test' for all tests? It takes a very long time.
21:03 < kris1> if you write BOOST_AUTO_TEST_SUITE(TestSuite)
21:03 < kris1> you can do this bin/mlpack_test -t TestSuite
21:04 < kris1> it will only run the test in the TestSuite
21:04 < kris1> refer to the description here
21:05 < kris1>
21:05 < kris1> shihao:
21:05 < shihao> oh, got it!
21:05 < shihao> Thank you, krisl!
21:13 -!- Netsplit *.net <-> *.split quits: sumedhghaisas
21:20 < shihao> If I want to test correctness of posteriors in nbc, can I add a new csv file which contains posteriors calculated by other tools, like sklearn ?
21:25 < kris1> zoq: a while back you suggested to add this line to std::vector<LayerTypes>& Model() { return network; } for getting the model but this is giving error while building
21:27 < kris1> shihao: hard code the posterios in the test file while check something and check_is_close(some_function(), real_value)
21:32 < shihao> krisl: got it !
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23:02 < shihao> Hi guys. I added a new test file 'testResProba.csv' to test prosteriors in nbc and Travis CI build failed since there is no such file there. How can I solve this problem?
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23:20 < kris1> @zoq are there any tests for the visitor patterns
23:20 < kris1> sorry i mean visitors
23:20 < kris1> std::cout << boost::apply_visitor(WeightSizeVisitor(), model) << std::endl;
23:20 < kris1> i was doing this and this gave a error
23:23 < kris1> saying ffn has no apply_visitor
23:29 < zoq> kris1: Make sure model is of type LayerTypes, also you said "std::vector<LayerTypes>& Model() { return network; }" results in an error, can you give me the error message?
23:31 < kris1> FFN<NegativeLogLikelihood<> > model;
23:31 < kris1> so its of FFN type
23:33 < kris1> i think ffn should also be in LayerTypes
23:33 < zoq> yeah, and the visitor works on LayerTypes, so model.Model()[0] for the first layer model.Model()[1] for the second, with the assumption that model.Model returns std::vector<LayerTypes>
23:33 < kris1> i see lstm, convolution but not ffn
23:34 < kris1> ok
23:36 < kris1> but this assumes that std::vector<LayerTypes>& Model() { return network; } this works. but it dosen't for me
23:36 < kris1> right now atleas. wait i will post the error msg
23:36 < kris1> zoq:i have to add this line to ffn.hpp right?
23:36 < zoq> yes
23:37 < zoq> Regarding the build question; You can't just build the ann code, at least not without modifying the CMake file, on the other side if you run make it should build modified files only.
23:42 < kris1> The error is something like this
23:42 < kris1> InitializationRuleType>::Model()’ cannot be overloaded
23:42 < kris1> std::vector<LayerTypes>& Model() { return network; }
23:43 < kris1> the full error
23:44 < kris1> zoq:
23:46 < zoq> strange, can you also post your ffn.hpp file?
23:46 < shihao> zoq: Hi zoq, I add a new test file and Travis CI build failed me. How can it be solved?
23:47 < shihao> I was trying to test posteriors in nbc.
23:47 < zoq> shihao: Can you send me the travis link?
23:48 < shihao> zoq:
23:49 < kris1> zoq:
23:52 < zoq> shihao: I can't see that you pushed the testResProba.csv to tests/data, also maybe we can just define the matrix, something like: arma::mat testResProba("1 2 3 4; 1 2 3 4")?
23:53 < zoq> kris1: The function is implemented twice line 173 and 49
23:54 < shihao> zoq: Oh, I forgot it. After fixing it, should I close my PR and create another one?
23:57 < shihao> zoq: I noticed that travis started to rebuild :)
23:58 < zoq> Ah, yeah every time you make a commit + push travis will rebuild the PR.
23:59 < shihao> I am curious what debugging tool or IDE you guys are using?
--- Log closed Sun Mar 05 00:00:29 2017