IRC logs of #shogun for Friday, 2013-05-24

--- Log opened Fri May 24 00:00:15 2013
@sonney2klisitsyn, you are close - just one test fails now converter_tdistributedstochasticneighborembedding_modular00:09
lisitsynsonney2k: hmm00:10
gsomixgood night, guys00:11
@sonney2knight everyone00:28
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shogun-buildbotbuild #404 of nightly_default is complete: Failure [failed test]  Build details are at http://www.shogun-toolbox.org/buildbot/builders/nightly_default/builds/40404:10
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shogun-notifier-shogun: Soeren Sonnenburg :develop * 571ea98 / tests/integration/python_modular/generator.py: https://github.com/shogun-toolbox/shogun/commit/571ea9864dbb19e3f4b2de929739eeb6b3ce47fb08:29
shogun-notifier-shogun: disable failing tests08:29
shogun-notifier-shogun:08:29
shogun-notifier-shogun: - converter test fails for real08:29
shogun-notifier-shogun: - disable other tests failing only on travis08:29
shogun-buildbotbuild #869 of cyg1 - libshogun is complete: Success [build successful]  Build details are at http://www.shogun-toolbox.org/buildbot/builders/cyg1%20-%20libshogun/builds/86908:52
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shogun-buildbotbuild #1162 of deb3 - modular_interfaces is complete: Success [build successful]  Build details are at http://www.shogun-toolbox.org/buildbot/builders/deb3%20-%20modular_interfaces/builds/116209:09
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travis-ci[travis-ci] it's Soeren Sonnenburg's turn to pay the next round of drinks for the massacre he caused in shogun-toolbox/shogun: http://travis-ci.org/shogun-toolbox/shogun/builds/745230609:11
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lambdayGuten morgen, Доброе утро. Buenos días.09:52
@lisitsynlambday: haha09:58
@lisitsyngoing multilingual09:58
lambday:)09:58
@lisitsynlambday: morgen, wie gehts?09:58
@lisitsynlambday: ich spreche etwas deutsch09:58
lambdayshit.. (urgent help needed @google translator)09:59
@lisitsynhahaha09:59
lambdayHablo un poco de español.10:00
lambdayHeikoS: hi..10:05
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sonne|workshogun-buildbot: force build nightly_default10:19
shogun-buildbotbuild forced [ETA 50m45s]10:19
shogun-buildbotI'll give a shout when the build finishes10:19
@lisitsynsonne|work: I will have one hour buffer before that meeting so I can make it for sure10:27
sonne|worklisitsyn: sry what?10:28
@lisitsynsonne|work: #gsoc10:28
sonne|workahh oki10:28
@lisitsynI had a chance I get to that meeting just in time because of being in bus10:29
sonne|workI might not need to do 'fix my pc' support tonight so I should be around too10:29
@lisitsynahh okay10:29
sonne|workbtw 7 am UTC was the deadline right?10:29
@lisitsynyes10:29
sonne|workdid you check for last minute conflicts?10:29
@lisitsynwe have passed it I guess10:29
@lisitsynsonne|work: I see no conflicts10:30
@lisitsynsonne|work: everything seemed to be correct yes10:30
sonne|worksmooth :)10:31
sonne|workalright then it should all be no problem tonight10:31
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vgorbatisonney2k: hi, are you here?10:59
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shogun-buildbotbuild #405 of nightly_default is complete: Success [build successful]  Build details are at http://www.shogun-toolbox.org/buildbot/builders/nightly_default/builds/40511:14
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@wikingsonne|work: did u merge the prng improvement branch?11:49
@wikingoh yeah i see u did11:49
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sonne|workwiking: yeah yeah12:09
@wikinggreat :)12:29
foulwall_Hi sonne|work12:35
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foulwalldid you see my yesterday's work?12:50
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sonne|workfoulwall: yes I tried it even :)13:05
sonne|workfoulwall: I think I will create a couple of reasonable datasets and put them in some repository - maybe even not shogun-data (slightly big already...)13:06
foulwallsonne|work: any suggests?13:06
foulwallsonne|work: Ok13:06
sonne|workfoulwall: no just assume that you can load all *.h5 in some given dir and present them for loading13:07
sonne|workfoulwall: maybe we even have a few data sets per category - e.g. some for binary classification, multiclass, regression13:08
foulwallsonne|work: hmm13:08
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sonne|workso you would then only show the ones from that respective dir13:08
foulwallsonne|work: ok , gotcha13:08
foulwallsonne|work: I'll do some fix this night ~~~13:10
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@wikinglisitsyn: ping13:12
@lisitsynwiking: pong13:13
@wikinglisitsyn: openmp implementation...? :)13:13
@wikinglisitsyn: i can haz openmp with clang finally13:13
lambdayHeikoS: hi13:14
@HeikoSlambday: hi!13:14
@wikingvgorbati: hey you've /msg -ed me about prng13:14
@wikingvgorbati: shoot what you need if you still need it13:14
lambdayHeikoS: the initial class structure.. seems okay to you?13:14
@HeikoSlambday: yes13:14
@HeikoSso one thing I would maybe change:13:15
@HeikoSsampler as a base class13:15
lambdayHeikoS: hmm...13:15
@lisitsynwiking: openmp of?13:15
@HeikoSactually I would do this everywhere where there might be different implementations of things13:15
lambdayokay.. not the enum there...13:15
@HeikoSthen you call abstract methods and impleent them in subclasses13:15
@HeikoSonly enum if you definitely know there are just a small number of cases and not more13:16
@wikinglisitsyn: i'm writing now bagging machien and it would be nice that i  could do the training of the n machines in parallel13:16
vgorbatiwiking: yes. I did work on one integration test for random DR method (setting seed to some specified value on the beginning), and on my Mac OS it gave one result, while on build servers (travis and shogun-buildbot) the results were different13:16
lambdayHeikoS: alright... so for matrix function things, enum is fine, right?13:16
@HeikoSotherwise you will have to do all this switch(type) stuff which makes code hard to  read13:16
lambdaycause that method works for only sqrt, log and A^alpha13:16
@lisitsynwiking: so openmp is in clang?13:16
@HeikoSlambday: exactly, we will only have a few there so thats fine13:16
@wikingvgorbati: that is rather fucking intersting :)13:16
@HeikoSlet me check the rest of the mail ...13:16
lambdayHeikoS: nice idea... okay :)13:16
vgorbatiwiking: are you using linux?13:16
@HeikoSlambday: sorry for not responding too fast, I have a deadline coming btw ...13:16
@wikingvgorbati: osx13:17
@HeikoSlambday: could you  maybe create a  diagram for these things?13:17
@HeikoSjust with inheritance and who references who13:17
lambdayI've declared the enum in CContourIntegral.h instead, to avoid including unnecessary headers, in case one just want to use ContourIntegral and not RationalApproximation13:17
@wikingvgorbati: can u plz tell me where exactly you had the problem13:17
lambdayHeikoS: sure... I'll mail it, changing the sampler as the base class13:17
@wikingvgorbati: the exact reason to have our own PRNG is that we dont have this problem anymore13:18
@HeikoSlambday: and maybe a small description for every class, like one sentence13:18
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gsomixhello13:18
@HeikoSand method13:18
@wikingvgorbati: i.e. the seeded random is always the same, regardless of OS and arch13:18
@HeikoSso what does register do for example13:18
lambdayHeikoS: alright...13:18
vgorbatiwiking: ok, can you please try running "python generator.py converter_tdistributedstochasticneighborembedding_modular.py" in the "tests/integration/python_modular" and paste the file "data/testsuite/tests/converter_tdistributedstochasticneighborembedding_modular0.txt" somewhere?13:18
@HeikoSCComputation for example will also be a base class13:18
@HeikoSwhich is just used for registering problems (maybe make problem a class also)13:19
@wikingvgorbati: will do in a second13:19
@HeikoSonly the implementation knows that there are shifts in the systems13:19
vgorbatiwiking: you will need to un-blacklist the file 'converter_tdistributedstochasticneighborembedding_modular.py' in generator.py13:19
@HeikoStry to think as general as possible13:19
@HeikoSonce we have the diagram, we can start moving things around (maybe attach the dia file so that I can modify it)13:19
vgorbatiwiking: it is actually blacklisted 2 times :)13:19
@HeikoSlambday, we should spend some time on this, even before any code is written13:20
lambdayHeikoS: alright... I'll send you by tonight...13:20
@HeikoSand then we should start adding concrete implementations in the diagram13:20
@HeikoSalso before writing code13:20
@HeikoSalso, keep in mind that everything has to be defined in terms of linear operators13:21
@HeikoSso when computing the matrix logarithm for example13:21
@HeikoSwe always compute log(M)*v13:21
@HeikoSnever log(M) alone (not possible sometimes)13:21
lambdayyes...13:21
lambdayhmm..13:21
@HeikoSeven for log-dets13:21
@HeikoSsometimes one cannot even store the matrix one wants to compute the log-det of13:21
@HeikoSbut one can compute matrix-vector products of the parts for example13:22
@HeikoSso always linear operator apply, never a matrix on its own13:22
lambdayhmmm...13:22
sonne|workwiking: if you want to use multiple threads for bagging13:24
sonne|workyou should assign new SGParallel objects to the internal machine13:24
sonne|worknot that it uses multiple threads13:24
sonne|workwith nthreads = 113:25
lambdayHeikoS: since computing shifts weights etc don't depend on the rest of the things, that things can be done now, may be?13:27
@HeikoSlambday: yes, if you want to code, then this can be done now :)13:27
lambdayHeikoS: I hope I'll finish the coding for ContourIntegral thing by tonight/tomorrow.. and spend some time on designing the whole thing...13:28
@HeikoSlambday: okay,13:29
gsomixsonne|work: hi, working? :)13:29
@HeikoSlambday: again, I am slowing down things for the class structure to make it as flexible as possible13:29
lambdayHeikoS: yes.. that's the best idea.. :)13:29
sonne|workgsomix: sure :D13:30
gsomixsonne|work: me too, sitting in the Lab.13:30
lambdayHeikoS: could you please tell me what you have in mind about base CComputation class? What I thought was CSolver as a base class and then its subclasses implementing different solvers13:31
@HeikoSComputation and solver are different13:31
@HeikoScomputation class has a register method where one can register subproblems (i.e. one linear system) in some structured way (i.e. all linear systems with indices)13:32
@HeikoSthe computation class then has an abstract method compute which then solves all registered problems somehow13:32
@HeikoSnote that registering might differ in subclasses (i.e. register a shifts vector)13:32
@HeikoSthe solver class just solves a linear system13:33
@HeikoSand might be used by the computation class impleentations13:33
@HeikoSdoes that make sense?13:33
lambdayHeikoS: yes... okay13:34
lambdayHeikoS: alright... this helped a lot... I'll mail you the diagram...13:37
@HeikoSgood :)13:37
thoralfHeikoS, sonne|work: You wrote lib/DynamicObjectArray.h, right?13:42
thoralfCan you explain, why you always do SG_REF before returning a reference, e.g. in get_element()?13:42
@HeikoSthoralf: this is done everywhere in shohun13:43
@HeikoSshogun13:43
@HeikoSwhenever you get an element, you store it, so the ref-counter has to be incremented13:43
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sonne|workthoralf: in python & swig you need a way to tell whether an object is still used13:44
thoralfHeikoS: Okay, that means I can rely that a returned reference has been SG_REF and I need to care about SG_UNREF?13:44
sonne|workthoralf: this is done via reference counts13:44
sonne|workso whenever we return an object13:45
sonne|workpython & swig calls ref()13:45
@HeikoSthoralf, yes you have to unref to prevent leaks13:45
sonne|workwhen swig is done using the object13:45
sonne|workit calls unref()13:46
@HeikoSthoralf: this is done most of the time, sometimes, we forgot SG_REF, in this case, send a bug report :)13:46
sonne|workonce the refcount (via unref reaches 0)13:46
@wikingsonne|work: will check13:46
thoralfsonne|work: Maybe I don't store the reference, but only pass then to a method which cares about ref/unref by itself.13:46
thoralfsonne|work: So I always need to store the reference in a variable and UNREF it afterwards.13:46
thoralfsonne|work: Yeah, I know.  I just wasn't aware of this kind of "convention". :)13:48
sonne|workthoralf: yes13:48
sonne|workthis also works the other way round13:48
sonne|workif you create say some feature object13:49
sonne|workyou can pass this directly into some machine13:49
sonne|workthen an unref of the machine will also erase the feature object13:49
thoralfsonne|work: So I can't do calls like method_eats_ref( object->method_returns_ref() )13:49
thoralfsonne|work: I always need addional code just for ref-counting. :)13:50
thoralfsonne|work: One example: kernel->set_features( ref_to_my_features );13:51
thoralfsonne|work: Do I need to care about SG_UNREF of the passed object or not?13:51
@wikingsonne|work: for feature/label selection with replacement, can i use the subset thingy?13:51
thoralfsonne|work: I always do SG_REF() after creation and SG_UNREF() in the end - but after what you told, this is not neccessary?  Just pass into ->set_features() and stop caring?13:53
sonne|workthoralf: for kernel->set_features( ref_to_my_features ); you don't need to SG_REF(ref_to_my_features) after you created them and if you don't touch them later13:57
sonne|workso e.g. kernel->set_features(new DenseFeatures<float64_t>())13:58
sonne|workbut for your  method_eats_ref( object->method_returns_ref() ) you need to store the object and unref13:59
thoralfsonne|work: Thanks, that answers my questions.14:00
sonne|workwiking: I think not - hmmh HeikoS - maybe we have conflicts then right?14:00
sonne|workthoralf: btw we cannot return lazy copies (not SG_REF'd)14:01
sonne|workor swig interfaces will have memory leaks14:01
thoralfsonne|work: Thats alright.  I just assumed, you only count references when copying objects and I have to care about references by myself.14:05
sonne|workwiking: actually you can do it!14:07
sonne|workwiking: just do add_subset14:07
sonne|workand once done remove_subset14:07
thoralfsonne|work: Btw, I think it would make sense to initialize "new SGVector<T>(len)" with zeros in the constructor, i.e. zero(); right after the SG_MALLOC.14:09
@wikingsonne|work: mmm but can i have replacement there?14:10
sonne|workthoralf: we could use SG_CALLOC for that but it is not done to have a speed gain in case you just want to alloc some vector and assign values...14:10
thoralfsonne|work: valgrind told me something about uninitialized variables - and I think the fix would be trivial14:10
sonne|workwiking: replacement?14:10
@wikingsonne|work: or the index vector can be whatever, i.e. i can have in index vector the same index as many times as i want14:10
@wikingsonne|work: "each of size n′ < n, by sampling from D uniformly and with replacement"14:11
sonne|workwiking: sure why not!14:11
sonne|workjust the same size!14:11
@wikingok cool14:11
@wikingyeah sure ;)14:11
sonne|workno actually any n' <= n yes14:11
sonne|workwiking: if you do that better extract the sampling strategies14:12
sonne|worklike random subset / bagging etc14:12
@wiking?14:12
sonne|workno idea what the official name for sampling strategy is14:12
sonne|workmaybe heiko knows14:12
sonne|workHeikoS: ^?14:12
@wikingwell i'll just do random selection14:12
sonne|workwiking: well there are various strategies for sampling14:13
@HeikoSehm what?14:13
@wikingmmm14:13
@HeikoSsampling what?14:13
@wikingsonne|work: really?14:13
@wikingsonne|work: here it said only that uniform random with replacement14:13
@wikingHeikoS: bagging14:13
sonne|workHeikoS: wiking is building some classifier that is trained a couple of times on subsets of the data14:13
@HeikoSrandom forests?14:13
sonne|workthe way this subset is generated should be generalized14:13
sonne|workyes for that14:14
sonne|workbut it will work for anything14:14
@HeikoSwell then the samples have to be independent14:14
sonne|workand there are various strategies for sampling14:14
@HeikoSso with repetitions14:14
sonne|worklike uniform / stratified / repetitions etc14:14
sonne|workso we might want to generalize this somehow14:14
@wikingnow the only question is that whether all our CMachine implementations has clone() function implemented14:19
sonne|workwiking: surely not :D14:23
sonne|workwiking: but what do you need clone for?14:23
sonne|workohh I see14:24
@wikingsonne|work: how else i'm going to create a bag of defined machines14:24
thoralfWhat's the difference between left_features and right_features in kernel->init(left, right)?14:32
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sonne|workthoralf: well rows, columns14:39
sonne|workthoralf: so for training you do k(X,X) and for testing k(X,X_test)14:39
thoralfsonne|work: Thanks.14:39
thoralfsonne|work: That explains why the cache is only initialized for lhs.14:40
thoralf(As far as i know)14:40
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sonne|workthoralf: it is only inited for svmlight IIRC and only when training14:50
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@wikingsonne|work: any other ideas for creating a bunch of *same* machine? :)14:52
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@wikingsonne|work: and i really wonder how this should work in case of a kernel machine? :14:53
@wiking:P14:53
sonne|workwiking: ohh I realize parameters of the machine need to be set already14:54
sonne|workI mean fully14:54
sonne|workwiking: so you need in case of a kernelmachine, the kernel, its parameters and the kernel machine and its parameters already set14:55
sonne|workthen take that machine and train with different subsets14:55
sonne|workwiking: for now just do it this way but not parallel at all14:56
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@HeikoSsonne|work, wiking clone should be done via parameter framework, please dont start writing custom clone methods for all classes, this wil be a mess15:11
sonne|workHeikoS, wiking - well wikign doesn't need clone as long as he runs everything *single* threaded15:12
@HeikoSokey15:12
@HeikoSI see15:12
@HeikoSsimilar to grid-search stuff15:12
sonne|workyeah15:13
gsomix<offtop>https://dl.dropboxusercontent.com/u/19029407/results_of_raytracing.png<\offtop>15:20
gsomixahh, braces... :)15:21
@wikingsonne|work: ok but how do i save the different models?15:44
@wikingsonne|work: because later i'll have to apply the features on those different models15:44
sonne|workwiking: ohh indeed15:46
sonne|workHeikoS: any suggestions? I mean this certainly needs store_model_features15:47
@HeikoSwhat about serialising?15:48
@HeikoSto a byte stream15:48
@HeikoSah no15:48
@HeikoSsorry15:48
@HeikoSso multple subsets on the same machine15:48
@HeikoSthats not trivial15:49
@HeikoSstore_model_features has to be extended15:49
@wikingsonne|work: btw: random forest is not a simple bagging machine. as it splits the data set vertically as well not only horizontally15:51
@wikingi.e. bagging just splits the dataset into smaller bags... but random forest splits the data set by feature dim15:52
sonne|workwiking: both at once?15:53
@wikingeach tree gets n < m features where m is the feature dim of the original dataset15:53
@wiking"Each tree is trained on a bootstrapped sample of the original data set."15:54
@wiking"Each time a leaf is split, only a randomly chosen subset of the dimensions are considered for splitting."15:54
@wikinganyhow for bagging we need to be able to clone machines or something like that15:54
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@lisitsynyes RF does both16:02
@wikinganybody expert in VS?16:03
@wikingi would need to link a static library into a dll16:03
@wikinghow the hell do i do it?16:04
@lisitsynwiking: visual studio?16:04
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@wikinglisitsyn: yes16:07
@wikinglisitsyn: any ideas?16:09
@lisitsynwiking: no not really16:12
@wiking:S16:12
@wikingyeah i'm having trouble to figure out this shit as well16:12
@lisitsynwiking: I did something about it while ago16:12
@lisitsynbut can't remember any way out16:12
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* wiking hates vs 16:26
@wikingi cannot believe that doing this can be so fucking complicated...16:26
@wikingok i'll use cmake now ;)16:37
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@sonney2kwiking, life is tough17:07
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pickle27sonney2k: working on QDA now17:50
pickle27sonney2k: going through and making it consistent with MCLDA and updating the styling17:51
pickle27sonney2k: Eigen3 can also be used in more places that in currently is17:53
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shogun-notifier-shogun: Roman Votyakov :develop * fdac479 / src/shogun/regression/gp/ (4 files): https://github.com/shogun-toolbox/shogun/commit/fdac479aac844e368aa977caf0be7b87e556823018:43
shogun-notifier-shogun: Removed unused fields from inference method classes18:43
shogun-notifier-shogun: Heiko Strathmann :develop * ffa6cd0 / src/shogun/regression/gp/ (4 files): https://github.com/shogun-toolbox/shogun/commit/ffa6cd015103ad6003f8758887788be996dbbda618:43
shogun-notifier-shogun: Merge pull request #1128 from votjakovr/develop18:43
shogun-notifier-shogun:18:43
shogun-notifier-shogun: Removed unused fields from inference method classes18:43
votjakovrHeikoS: Very fast merge, thanks :)18:47
@HeikoSwelcome :)18:47
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pickle27sonney2k: sent the qda pr, let me know if its all good18:57
pickle27sonney2k: there is still room for better use of Eigen3 there which I may play with in the next bit but theres some things I need to wrap up for school atm18:57
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@sonney2kpickle27, yeah one can *always* improve19:21
pickle27sonney2k: very true!19:21
@sonney2kpickle27, could you please remove all the SG_PRINT functions still?19:23
@sonney2kor is this covered in debug macros?19:23
pickle27sonney2k: sure, why do we not want the print statements?19:23
@sonney2kohh it is19:23
pickle27sonney2k: yeah the alg doesn't print unless the debug flag is set19:24
@sonney2kpickle27, it is annoying for people using it19:24
@sonney2kso all good!19:24
@sonney2klets merge19:24
pickle27sonney2k: let the fun begin ... jk should be smooth19:24
shogun-notifier-shogun: Kevin Hughes :develop * 0c4934b / / (6 files): https://github.com/shogun-toolbox/shogun/commit/0c4934b5cd89e9ecd896b57b425b469149ca05c519:25
shogun-notifier-shogun: fixed QDA with Eigen3 for merge, also added a unit test for QDA and fixed a bad tab in the MCLDA code19:25
shogun-notifier-shogun: Soeren Sonnenburg :develop * 6255686 / / (6 files): https://github.com/shogun-toolbox/shogun/commit/6255686e857d4d044e6c241168f45914e89cf3ae19:25
shogun-notifier-shogun: Merge pull request #1129 from pickle27/qda19:25
shogun-notifier-shogun:19:25
shogun-notifier-shogun: QDA with Eigen3 for merge thanks monalisag & ozanser for their work!19:25
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travis-ci[travis-ci] it's Heiko Strathmann's turn to pay the next round of drinks for the massacre he caused in shogun-toolbox/shogun: http://travis-ci.org/shogun-toolbox/shogun/builds/746860819:36
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shogun-buildbotbuild #1164 of deb3 - modular_interfaces is complete: Failure [failed test python_modular]  Build details are at http://www.shogun-toolbox.org/buildbot/builders/deb3%20-%20modular_interfaces/builds/1164  blamelist: Roman Votyakov <votjakovr@gmail.com>19:48
shogun-buildbotbuild #1165 of deb3 - modular_interfaces is complete: Failure [failed test python_modular]  Build details are at http://www.shogun-toolbox.org/buildbot/builders/deb3%20-%20modular_interfaces/builds/1165  blamelist: Soeren Sonnenburg <sonne@debian.org>, Kevin Hughes <kevin@kevin-M3920.(none)>20:15
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lambdayHeikoS: hi...20:44
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* shogun_sonney2k dedup meeting in gsoc going on...21:09
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gsomixgood evening21:21
@shogun_sonney2kgsomix, any idea where lisitsyn is?21:21
gsomixshogun_sonney2k, on the road to home. probably. but it's too late...21:22
@shogun_sonney2kthought he will join the meeting...21:23
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gsomixshogun_sonney2k, what's the nick?21:23
gsomixshogun_sonney2k, I can call him.21:24
@shogun_sonney2kit is close to over21:24
gsomixshogun_sonney2k, ok21:25
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lisitsyndamn!21:26
lisitsynsonney2k: is it ok?21:26
@sonney2klisitsyn, jsut over21:26
lisitsynmy ISP went crazy21:26
@sonney2kall good21:26
lisitsynsonney2k: no conflicts?21:27
@sonney2kyup21:27
lisitsynsonney2k: I am using 3G :D21:27
lisitsynping is 8s hah21:28
lisitsynok will wait my ISP' repairing of my connection21:29
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@sonney2kpickle27, have you seen?21:30
@sonney2kclassifier_qda_modular.py setting 1/2                        ERROR21:30
@sonney2kpython: /usr/include/eigen3/Eigen/src/Core/CwiseBinaryOp.h:146: Eigen::CwiseBinaryOp<BinaryOp, Lhs, Rhs>::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op<double, double>; Lhs = const Eigen::ArrayWrapper<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false, true> >; Rhs = const Eigen::Map<Eigen::Array<double, -1, 1> >]: Assertion `lhs.rows() == rhs.rows() && lhs.co21:30
@sonney2kls() == rhs.cols()' failed.21:30
@sonney2kAborted21:30
pickle27sonney2k: I did see that21:31
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pickle27sonney2k: I wasn't totally sure what it meant21:31
@sonney2kpickle27, well qda crashes :D21:31
pickle27sonney2k: was waiting for it to pop up in here so we could discuss21:31
@sonney2kpickle27, you should be able to reproduce it by running the python_modular example21:32
pickle27sonney2k: the crash came from python, but the c++ example didn't crash, I bet there is a leak in the c++ code too then21:33
pickle27sonney2k: there was some code I wasn't crazy about around where the svd is done21:33
@sonney2kdoesn't look like a leak more like some shape of some matrix is wrong21:33
pickle27sonney2k: thats sort of what I meant I guess, c++ is getting away with it though21:34
pickle27sonney2k: I know roughly where this has got be from21:34
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pickle27sonney2k: curious, the example just ran on my system21:37
@sonney2kpickle27, go to tests/integration/python_modular21:48
@sonney2kthen run ./tester.py classifier_qda_modular.py21:48
pickle27sonney2k: I had the debug flag on so I rebuilt21:52
pickle27sonney2k: but it looks like I lost the python interface some how21:52
pickle27I'll rebuild and take a look into this21:52
pickle27sonney2k: I need to head out for a bit though so I'll get into this a bit later21:53
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gsomixneed to sleep22:52
gsomixgood night, guys22:52
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--- Log closed Sat May 25 00:00:16 2013

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