mlpack IRC logs, 2020-03-18

Logs for the day 2020-03-18 (starts at 0:00 UTC) are shown below.

March 2020
--- Log opened Wed Mar 18 00:00:33 2020
01:10 -!- gitter_mostafana [gittermost@gateway/shell/] has joined #mlpack
01:10 -!- gitter_mostafana is now known as MostafaNabiehGit
01:10 < MostafaNabiehGit> Hello ,
01:10 < MostafaNabiehGit> I interested Application of ANN Algorithms Implemented in mlpack
01:10 < MostafaNabiehGit> and Reinforcement learning
01:10 < MostafaNabiehGit> With the requirements of working with you
01:56 < rcurtin> MostafaNabiehGit: hi there, have you seen and Those pages should be helpful
03:01 < chopper_inbound4> Hi
03:01 < chopper_inbound4>
03:01 < chopper_inbound4> This needs just one more approval :)
03:50 < hemal[m]> chopper_inbound: The 2nd approval is usually provided automatically by mlpack_bot after 24 hours.
03:50 < hemal[m]> *after 24 hours of 1st approval
04:30 < chopper_inbound4> hemal : don't you think it's 1 day in total? ;)
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04:44 -!- M_slack_mlpack16 is now known as RudraPatil[m]
04:44 < RudraPatil[m]> I am Rudra, 2nd year CS student and machine learning enthusiast. I am interested in contributing to the project idea of " Application of ANN Algorithms Implemented in mlpack ". I have been contributing to open source and this is my first season of GSoC. While writing my idea proposal , should I be including a lot of technical specifications about implementing my idea or a brief overview of the idea and a proposed
04:44 < RudraPatil[m]> timeline
04:45 < RudraPatil[m]> I am Rudra, 2nd year CS student and machine learning enthusiast. I am interested in contributing to the project idea of " Application of ANN Algorithms Implemented in mlpack ". I have been contributing to open source and this is my first season of GSoC. While writing my idea proposal , should I be including a lot of technical specifications about implementing my idea or a brief overview of the idea and a proposed
04:45 < RudraPatil[m]> timeline ?
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06:22 < hemal[m]> Rudra Patil:
06:22 < hemal[m]> Should be helpful
06:39 < jenkins-mlpack2> Project mlpack - git commit test build #358: UNSTABLE in 1 hr 20 min:
07:25 < jenkins-mlpack2> Project docker mlpack nightly build build #645: STILL UNSTABLE in 3 hr 11 min:
07:43 < jenkins-mlpack2> Yippee, build fixed!
07:43 < jenkins-mlpack2> Project mlpack - git commit test build #359: FIXED in 1 hr 0 min:
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09:27 < MostafaNabiehGit> @matrixbot Thank you so much
09:27 < MostafaNabiehGit> I will start now
09:35 < MostafaNabiehGit> I am start learning with mlpack
09:35 < MostafaNabiehGit> this is very useful for everyone here
09:35 < MostafaNabiehGit>
09:37 < MostafaNabiehGit> i'am finished first lesson
09:48 * MostafaNabiehGit sent a long message: < >
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10:20 < favre49> Testing irssi
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10:22 < PrinceGuptaGitte> Hi @zoq , I had a query. I was thinking for transfer learning purposes, wouldn't it be better to have models in main repo of MLPack, so that we can do `#include<mlpack/methods/ann/models/lenet.hpp>` in our programs, but all models are in "models" repo.
11:06 < MostafaNabiehGit> This lesson is very useful
11:06 < MostafaNabiehGit>
11:06 < MostafaNabiehGit>
11:07 < MostafaNabiehGit> @matrixbot I will start with issues today after finish all tutorial
11:07 < MostafaNabiehGit> thank you so much for this tutorial
11:14 < kartikdutt18Gitt> @prince776, That point will be resolved as part of refactoring. I think that's the main reason I wrote cmake for models folder else they could have been included using "./../models/lenet.hpp". Also I think Adding models to main repo isn't a good idea, as we may have some dependencies associated with the code that isn't needed to build mlpack. You can also refer to the discussion in the models repo.
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11:28 < favre49> testing irssi again
11:28 < PrinceGuptaGitte> Oh so we'll be able to make install models right?
11:28 < PrinceGuptaGitte> that
11:29 < PrinceGuptaGitte> (edited) that => that's good
11:49 < kartikdutt18Gitt> So the current plan is that the current models repo will renamed and it will have simple tutorial like code for user to copy and paste. There will be a different repo which will be a submodule of mlpack for models that we are building. The example repo (or to be named something different) will be made extremely simple i.e. remove unnecessary files so that a user can implement his first model just by looking at the
11:49 < kartikdutt18Gitt> code. Hopefully what I said makes sense. I think the discussion offers more detailed idea.
12:39 < Manav-KumarGitte> Hi I am Manav Kumar 3rd year CSE student. I would like to contribute by participating in GSOC. I am installing it in my local system (Mac OS) by following this guide : but while doing cmake ../ i am getting the output as :
12:40 * Manav-KumarGitte sent a long message: < >
12:41 < Manav-KumarGitte> Can anybody help me with it?
12:46 < zoq> Manav-KumarGitte: Any chance you can use the macOS compiler and not the one that comes with anaconda?
12:47 < zoq> You could use "cmake -DCMAKE_C_COMPILER=/path/to/clang -DCMAKE_CXX_COMPILER=path/to/clang++ .."
13:24 < Manav-KumarGitte> It worked by using /usr/bin/gcc and g++ but after make command on certain specific libraries i am getting error like make[2]: *** [CMakeFiles/Makefile2:442: src/mlpack/CMakeFiles/mlpack.dir/all] Error 2
13:24 < Manav-KumarGitte> make[1]: *** [CMakeFiles/Makefile2:6060: src/mlpack/methods/pca/CMakeFiles/mlpack_pca.dir/rule] Error 2
13:24 < Manav-KumarGitte> make: *** [Makefile:1696: mlpack_pca] Error 2
13:28 < zoq> Manav-KumarGitte: I think there is something wrong the anaconda setup.
13:29 < Manav-KumarGitte> Do i need to uninstall the whole software?
13:34 < zoq> Manav-KumarGitte: I don't think so, not particular familiar with anaconda, but I guess you are missing some package.
13:35 < Manav-KumarGitte> I have installed all the dependencies with their appropriate versions.
13:37 < rcurtin> Manav-KumarGitte: I'd strongly suggest *not* using the compiler provided by anaconda. anaconda is a third-party package and likely won't integrate with anything correctly *outside* your anaconda install
13:38 < rcurtin> you might be able to hack around the error you are seeing by adding the CMake flag -DCMAKE_LINKER_EXE_FLAGS="-lSystem" or something like this
13:38 < rcurtin> but again, it would be better to use a compiler not from anaconda
13:38 < zoq> But I guess if you stay in the anaconda world you are good?
13:39 < zoq> Looking at:
13:39 < rcurtin> yeah, I imagine there is some additional amount of configuration that's needed, but it's certainly possible
13:39 < zoq> I guess, they use anaconda compiler as well.
13:39 < rcurtin> yeah, I think it all works in a chroot or something like this, I'm not sure
13:40 < rcurtin> when I met with the conda-forge folks at the NumFOCUS summit, they were able to help me get a shell to a conda environment, and it basically behaved like a chroot with anaconda tools in it
13:40 < rcurtin> I have to say... it's a bit disappointing how hard it has gotten to compile C++ programs on modern systems because of the mess of package managers that are available!
13:40 < zoq> Yeah no idea, I guess if Manav-KumarGitte is up for a challenging go for it :)
13:40 < rcurtin> indeed, it will be a challenge for sure I think :)
13:42 < jeffin143[m]> Are you all on leave , wfh ???
13:42 < jeffin143[m]> Anything
13:42 < rcurtin> I work for a remote company so life is kind of unchanged for me :)
13:42 < rcurtin> I have an office in a coworking space about a mile away, but basically I am just staying home
13:42 < rcurtin> went to the grocery store today... there was no bread for some reason. didn't even check the toilet paper aisle, I just assumed that people had hoarded it :)
13:43 < rcurtin> but for the most part, at least for me, things are fairly normal except that I'm not going out in the evenings anymore to restaurants or anything. and traffic is really great when I do have to drive somewhere :-D
13:43 < zoq> Same for me.
13:44 < jeffin143[m]> Can you post a pic of your wfh setup ???
13:44 < jeffin143[m]> I mean your desk
13:44 < rcurtin> sure, let me take a picture ...
13:47 < rcurtin>
13:48 < rcurtin> the cats are supposed to sleep on the blanket that's partially in the lower right hand corner of the picture but they don't tend to actually do that ...
13:49 < rcurtin> note also the Jupyter notebook on the desk and the 5.25" floppy drive :-D
13:49 < jeffin143[m]> That's a good one
13:49 < rcurtin> that particular cat also hates my zoom meetings:
13:49 < favre49> I especially like the picture on your wall :)
13:50 < rcurtin> ha! that was my "pfunk graduation picture":
13:50 < favre49> Also wow, the triple vertical monitor is certainly uncommon. Why so?
13:50 < rcurtin> after you defend you get to put on the hat and sunglasses
13:50 < rcurtin> favre49: well, basically, I used to have three 4:3 1600x1200 monitors, and I was pretty happy with that
13:51 < rcurtin> one day, I saw that these LG 27" 4k monitors were on sale, and so I said "sweet! time to replace my monitors"
13:51 < Manav-KumarGitte> Your desk set up is really cool, fan..
13:51 < rcurtin> when I got home, well, I realized I had bought *way* too much monitor
13:51 < rcurtin> so I had to turn them sideways, and even now I get lost figuring out what to look at
13:52 < favre49> Oh wow, never though you could have too much monitor. Then again, I only use a laptop
13:52 < rcurtin> when I travel I only have a little chromebook, it's a big change from the home setup :)
13:52 < favre49> Planning to buy an external monitor some time, it would probably save hours of time of mindless workspace switching over the years
13:53 < rcurtin> yeah, definitely 1->2 monitors was a huge change for me that was totally worthwhile. 2->3 was unnecessary...
13:53 < favre49> The good thing about this break is I finally have the time to fix all the Arch weirdness and do all the cool ricing I've wanted to
13:53 < rcurtin> :)
13:53 < rcurtin> next thing you know you'll be running Gentoo :-O
13:53 < jeffin143[m]> I am guessing who will be having the funckiest of setup
13:54 < favre49> I found another old laptop at home, I'm planning slackware :P
13:54 < rcurtin> awesome, that should be fun :) I ordered some IDE cables for that 5.25" floppy, and some disks, so I can get ancient Debian installed on my 386
13:55 < rcurtin> since I am not going anywhere on the weekends anymore, I should be able to do that soon, I think :)
13:55 < favre49> Oh I found an old Ubuntu installation CD in a lab at college
13:55 < favre49> I should have taken it just to try... I don't think I have any hardware that could run it though
13:55 < rcurtin> nice, was it one of the official printed disks?
13:55 < favre49> The version number was in the single digits I think
13:56 < favre49> Yup, still had the packaging too
13:56 < rcurtin> nice! now that is a cool artifact
13:56 < SriramSKGitter[m> It's usually the web developers with the vertical monitors :)
13:56 < rcurtin> SriramSKGitter[m: ha, true. sometimes I am forced to be a web developer but I'm not very good at it :(
13:57 < favre49> Honestly my whole inspiration for GUI and PCs is from reddit. Once you see r/unixporn you can't go back
13:58 < favre49> Probably wouldn't be spending days on my system if not for it :)
13:58 < jeffin143[m]> It's rare to find setup in india which are funky , it cost to much to setup one
13:58 < jeffin143[m]> It's rare to find setup in india which are funky , it cost to much to setup one
13:58 < rcurtin> favre49: nice, I should not have opened that up :)
13:58 < jeffin143[m]>
13:59 * jeffin143[m] uploaded an image: image_from_ios.jpg (94KB) < >
13:59 < jeffin143[m]> One of my colleagues have me the pic
13:59 < jeffin143[m]> Check this out :)
13:59 < rcurtin> jeffin143[m]: nice, lots of room for lots of terminals :)
14:00 < favre49> I hope their neck is ok, seems like a huge strain :D
14:00 < rcurtin> ha, I was thinking the same thing. my neck definitely hurts if I am doing work primarily on the left or right monitors... I have to move the "main" thing I'm doing to the middle
14:00 < jeffin143[m]> :)
14:01 < jeffin143[m]> He has 8 😂
14:01 < rcurtin> reminds me of The Matrix!
14:01 < rcurtin> I guess he is an Iron Man fan :)
14:02 < jeffin143[m]> They are insane people
14:02 < jeffin143[m]> :)
14:45 < LakshyaOjhaGitte> Hey guys
14:45 < LakshyaOjhaGitte> Wanted a little help.....
14:46 < LakshyaOjhaGitte> I was wondering if there is some doc or something to understand how images are stored in ml pack
14:47 < rcurtin> LakshyaOjhaGitte: in mlpack, everything has to be represented in an Armadilo matrix, so images (and everything) are typically flattened into one column of a matrix
14:47 < LakshyaOjhaGitte> Like in pytorch they use n layered matrice or something
14:47 < LakshyaOjhaGitte> yeah that I am familiar with
14:47 < LakshyaOjhaGitte> But I wanted to dig deeper into this
14:48 < rcurtin> yeah, unfortunately, there is no concept of higher-dimensional tensor in Armadillo so we are kind of forced to represent higher-dimensional objects as vectorized one-dimensional objects
14:48 < LakshyaOjhaGitte> like How height, width and channel is stored in matrix
14:48 < LakshyaOjhaGitte> Ok
14:48 < rcurtin> for images, we have the data::Load() overload for images that also takes an ImageInfo, which stores some metadata about the image
14:48 < rcurtin> and can then be used again when data::Save() is called
14:49 < rcurtin> so, e.g., you load from disk, get an Armadillo vector and an ImageInfo; then use that Armadillo vector, and when you're done processing, save with the same ImageInfo (or a modified ImageInfo if you, e.g., changed the resolution)
14:49 < rcurtin> there are two PRs dealing with image support open that I know of right now (maybe there are more): #2312 and #2019
14:49 < LakshyaOjhaGitte> ohh
14:49 < rcurtin> perhaps some of the changes in there might be clarifying?
14:50 < LakshyaOjhaGitte> Thats interesting it is almost similar to python type that I searched recently, also looks like something I can understand if i give it sometime
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14:52 < LakshyaOjhaGitte> These pr is exactly what I was looking for, thank you so much
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14:53 < LakshyaOjhaGitte> I was too bored to read research papers at this moment XD
14:54 < LakshyaOjhaGitte> Also by any chance is there a reference in the mlpack docs regarding use of images?
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14:56 < rcurtin> there's some documentation in ; but it can always be improved if you see anything wrong or unclear :)
15:16 < LakshyaOjhaGitte> Thanks very helpful
15:16 < LakshyaOjhaGitte> :)
15:30 < MostafaNabiehGit> @matrixbot What is the best way to contribute with you now ?
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16:04 < Saksham[m]> ryan Hi should we send a draft of the proposal to you before submitting it on the GSOC website ?
16:05 < rcurtin> Saksham[m]: I probably don't really have time to look at proposals this year, unfortunately, things are really busy at my company, so likely the best idea is just to submit the proposal
16:05 < rcurtin> if we have any questions as we review it, we can always get in touch and ask
16:08 < Saksham[m]> That makes sense, thanks a lot
16:20 < AbishaiEbenezerG> x-special/nautilus-clipboard
16:20 < AbishaiEbenezerG> copy
16:20 < AbishaiEbenezerG> file:///home/abishai/Pictures/Screenshot%20from%202020-03-18%2021-49-33.png
16:21 < AbishaiEbenezerG> [![Screenshot from 2020-03-18 21-49-33.png](](
16:21 < AbishaiEbenezerG> hey mlpack , got a question here
16:22 < AbishaiEbenezerG> especially for @joeljosephjin @zoq
16:23 < AbishaiEbenezerG> so the code that @joeljosephjin shared here a few days earlier which served as a short q learning test for the mountain car env
16:26 < AbishaiEbenezerG> my understanding of the error is that the number of parameters in the policy( ) function call do not match. am i right?
16:26 < AbishaiEbenezerG> i also know that there's something more i'm missing here. but i can't exactly find it.
16:27 < AbishaiEbenezerG> [q_mountain_car.cpp](
16:28 < AbishaiEbenezerG> this is the implementation as shared by @joeljosephjin
16:29 < AbishaiEbenezerG> i tried to get through this myself, but i've already spent a couple of days on this . would like to use some help
16:30 < AbishaiEbenezerG> sorry if this is stupid. but i think it would help me alot as i try to understand the rl codebase which is what i'm aiming for....
16:43 < PrinceGuptaGitte> I've provided a temporary solution to the issue #2310 in PR #2316 . Let me know if it's a good thing.
17:02 < AbishaiEbenezerG>
17:02 < AbishaiEbenezerG> same code as above...
17:02 < AbishaiEbenezerG> any help would be greatly appreciated
17:08 < rcurtin> PrinceGuptaGitte: did you try the fix from the PR that I suggested in #2310?
17:36 < PrinceGuptaGitte> I just tried it, it works. I missed it in the conversation. My bad.
17:36 < PrinceGuptaGitte> That was indeed the reason
17:39 < PrinceGuptaGitte> Thanks @rcurtin
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17:40 < kartikdutt18Gitt> Ahh, I think I figured why alexnet failed even after creating a copy. I had to create a copy for adaptive pooling layers as well.
17:50 < rcurtin> PrinceGuptaGItte: glad that it worked, I think there are still some memory issues to work out though perhaps
17:53 < jeffin143[m]> Rcurtin :)
17:53 < jeffin143[m]> Done resolved everything for the image converter binding :)
17:58 < rcurtin> awesome! hopefully my changes did not make it too hard :)
18:00 < himanshu_pathak[> Hey rcurtin: zoq I was working on my pr of neural turing and I noticed that in r-value refactor we changed the arguments of forward and backward function . Now if I want to add new methods to work ffn as a layer I have to follow the API but this will cause an error when we want to use use ffn as a model
18:00 < himanshu_pathak[> because of the last loss layer will give different output matrix for gy error. So I am removing const from agruments. Now, if a person pass a value for const InputType& and he is using ffn as a model not a layer it will cause an error should I add warning for this. what do you suggest??
18:02 < kartikdutt18Gitt> @rcurtin, It worked for me as well. Just had to create a copy for a layer that I had added. Thanks a lot.
18:03 < kartikdutt18Gitt> Not at all, Just had to remove true, true from the layer as you know. Finally feels good to get it working, always thought there was something wrong with my model.
18:03 < rcurtin> himanshu_pathak[: I'm not sure I understand---I marked all of the parameters that I could const, I think it should be possible to do that
18:05 < rcurtin> ohh, I think I see, you actually want to use an FFN itself as a layer... isn't there a layer that acts as a "wrapper"? I'm not 100% sure, maybe the Sequential layer?
18:08 < himanshu_pathak[> rcurtin: I thought it will be a more better addition for us to use ffn as a layer if you want I can change my implementation and use sequential layer
18:09 < jeffin143[m]> Rcurtin :
18:09 < rcurtin> himanshu_pathak[: I see what you mean; I think we should wait for zoq's input on this one. maybe we can change the FFN Backward() function to match the layer API
18:09 < jeffin143[m]> Should this output
18:09 < rcurtin> jeffin143[m]: just saw that, I'll take a pass on the PR tonight and make some comments (a handful of hours from now)
18:09 < jeffin143[m]> Sorry for bothering but I just wanted to make it sure
18:10 < himanshu_pathak[> rcurtin: Yes, I think we should wait zoq
18:11 < jeffin143[m]> No issues , I ll just work on other pr
18:11 < himanshu_pathak[> * rcurtin: Yes, I think we should wait for zoq
18:11 < jeffin143[m]> Lots of pr in my hand
18:11 < rcurtin> jeffin143[m]: no worries---the question didn't look like I could immediately answer it, I think I'll have to look at the code and understand what's going on a bit more first
18:11 < rcurtin> jeffin143[m]: yeah, definitely, tons of PRs in general. the last few weeks before the GSoC application deadline are always crazy :)
18:21 * MostafaNabiehGit sent a long message: < >
18:21 < MostafaNabiehGit> @matrixbot
18:24 < himanshu_pathak[> >
18:24 < himanshu_pathak[> nice setuprcurtin
18:25 < rcurtin> himanshu_pathak[: thanks, I just wish I spent a little less time stuck at it :)
18:28 < himanshu_pathak[> Yeah it is addictive when you work like this
18:35 < SriramSKGitter[m> @mostafanabiehMourad : Did you have a look at /`src/mlpack/methods/linear_svm` ? Perhaps there's something of help to you there :)
18:37 < MostafaNabiehGit> @sriramsk1999 Thank you so much
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19:17 < naruarjun[m]> Could someone tell me how parallelism of code occurs in mlpack and is there any explicit code I can find for that in the repo?
19:31 < bisakh[m]> Hi zoq
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21:25 < M_slack_18> Hi I've been working on my proposal for the last few weeks are there any reinforcement learning related issues I could jump on
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--- Log closed Thu Mar 19 00:00:34 2020