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< MostafaNabiehGit> Hello ,
< MostafaNabiehGit> I interested Application of ANN Algorithms Implemented in mlpack
< MostafaNabiehGit> and Reinforcement learning
< MostafaNabiehGit> With the requirements of working with you
< rcurtin> MostafaNabiehGit: hi there, have you seen http://mlpack.org/community.html and http://mlpack.org/gsoc.html? Those pages should be helpful
< chopper_inbound4> Hi @rcurtin:matrix.org @freenode_zoq:matrix.org
< chopper_inbound4> This needs just one more approval :)
< hemal[m]> chopper_inbound: The 2nd approval is usually provided automatically by mlpack_bot after 24 hours.
< hemal[m]> *after 24 hours of 1st approval
< chopper_inbound4> hemal : don't you think it's 1 day in total? ;)
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< 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
< RudraPatil[m]> timeline
< 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
< RudraPatil[m]> timeline ?
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< hemal[m]> Should be helpful
< jenkins-mlpack2> Project mlpack - git commit test build #358: UNSTABLE in 1 hr 20 min: http://ci.mlpack.org/job/mlpack%20-%20git%20commit%20test/358/
< jenkins-mlpack2> Project docker mlpack nightly build build #645: STILL UNSTABLE in 3 hr 11 min: http://ci.mlpack.org/job/docker%20mlpack%20nightly%20build/645/
< jenkins-mlpack2> Yippee, build fixed!
< jenkins-mlpack2> Project mlpack - git commit test build #359: FIXED in 1 hr 0 min: http://ci.mlpack.org/job/mlpack%20-%20git%20commit%20test/359/
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< MostafaNabiehGit> @matrixbot Thank you so much
< MostafaNabiehGit> I will start now
< MostafaNabiehGit> I am start learning with mlpack
< MostafaNabiehGit> this is very useful for everyone here
< MostafaNabiehGit> i'am finished first lesson https://guides.github.com/introduction/flow/
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< favre49> Testing irssi
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< 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.
< MostafaNabiehGit> This lesson is very useful
< MostafaNabiehGit> @matrixbot I will start with issues today after finish all tutorial
< MostafaNabiehGit> thank you so much for this tutorial
< 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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< favre49> testing irssi again
< PrinceGuptaGitte> Oh so we'll be able to make install models right?
< PrinceGuptaGitte> that
< PrinceGuptaGitte> (edited) that => that's good
< 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
< kartikdutt18Gitt> code. Hopefully what I said makes sense. I think the discussion offers more detailed idea.
< 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 : https://github.com/mlpack/mlpack but while doing cmake ../ i am getting the output as :
< Manav-KumarGitte> Can anybody help me with it?
< zoq> Manav-KumarGitte: Any chance you can use the macOS compiler and not the one that comes with anaconda?
< zoq> You could use "cmake -DCMAKE_C_COMPILER=/path/to/clang -DCMAKE_CXX_COMPILER=path/to/clang++ .."
< 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
< Manav-KumarGitte> make[1]: *** [CMakeFiles/Makefile2:6060: src/mlpack/methods/pca/CMakeFiles/mlpack_pca.dir/rule] Error 2
< Manav-KumarGitte> make: *** [Makefile:1696: mlpack_pca] Error 2
< zoq> Manav-KumarGitte: I think there is something wrong the anaconda setup.
< Manav-KumarGitte> Do i need to uninstall the whole software?
< zoq> Manav-KumarGitte: I don't think so, not particular familiar with anaconda, but I guess you are missing some package.
< Manav-KumarGitte> I have installed all the dependencies with their appropriate versions.
< 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
< 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
< rcurtin> but again, it would be better to use a compiler not from anaconda
< zoq> But I guess if you stay in the anaconda world you are good?
< rcurtin> yeah, I imagine there is some additional amount of configuration that's needed, but it's certainly possible
< zoq> I guess, they use anaconda compiler as well.
< rcurtin> yeah, I think it all works in a chroot or something like this, I'm not sure
< 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
< 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!
< zoq> Yeah no idea, I guess if Manav-KumarGitte is up for a challenging go for it :)
< rcurtin> indeed, it will be a challenge for sure I think :)
< jeffin143[m]> Are you all on leave , wfh ???
< jeffin143[m]> Anything
< rcurtin> I work for a remote company so life is kind of unchanged for me :)
< rcurtin> I have an office in a coworking space about a mile away, but basically I am just staying home
< 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 :)
< 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
< zoq> Same for me.
< jeffin143[m]> Can you post a pic of your wfh setup ???
< jeffin143[m]> I mean your desk
< rcurtin> sure, let me take a picture ...
< 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 ...
< rcurtin> note also the Jupyter notebook on the desk and the 5.25" floppy drive :-D
< jeffin143[m]> That's a good one
< rcurtin> that particular cat also hates my zoom meetings: http://ratml.org/misc_img/frank_zoom.jpg
< favre49> I especially like the picture on your wall :)
< rcurtin> ha! that was my "pfunk graduation picture": https://www.cc.gatech.edu/~isbell/iai/people.shtml
< favre49> Also wow, the triple vertical monitor is certainly uncommon. Why so?
< rcurtin> after you defend you get to put on the hat and sunglasses
< rcurtin> favre49: well, basically, I used to have three 4:3 1600x1200 monitors, and I was pretty happy with that
< rcurtin> one day, I saw that these LG 27" 4k monitors were on sale, and so I said "sweet! time to replace my monitors"
< Manav-KumarGitte> Your desk set up is really cool, fan..
< rcurtin> when I got home, well, I realized I had bought *way* too much monitor
< rcurtin> so I had to turn them sideways, and even now I get lost figuring out what to look at
< favre49> Oh wow, never though you could have too much monitor. Then again, I only use a laptop
< rcurtin> when I travel I only have a little chromebook, it's a big change from the home setup :)
< favre49> Planning to buy an external monitor some time, it would probably save hours of time of mindless workspace switching over the years
< rcurtin> yeah, definitely 1->2 monitors was a huge change for me that was totally worthwhile. 2->3 was unnecessary...
< 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
< rcurtin> :)
< rcurtin> next thing you know you'll be running Gentoo :-O
< jeffin143[m]> I am guessing who will be having the funckiest of setup
< favre49> I found another old laptop at home, I'm planning slackware :P
< 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
< rcurtin> since I am not going anywhere on the weekends anymore, I should be able to do that soon, I think :)
< favre49> Oh I found an old Ubuntu installation CD in a lab at college
< favre49> I should have taken it just to try... I don't think I have any hardware that could run it though
< rcurtin> nice, was it one of the official printed disks?
< favre49> The version number was in the single digits I think
< favre49> Yup, still had the packaging too
< rcurtin> nice! now that is a cool artifact
< SriramSKGitter[m> It's usually the web developers with the vertical monitors :)
< rcurtin> SriramSKGitter[m: ha, true. sometimes I am forced to be a web developer but I'm not very good at it :(
< favre49> Honestly my whole inspiration for GUI and PCs is from reddit. Once you see r/unixporn you can't go back
< favre49> Probably wouldn't be spending days on my system if not for it :)
< jeffin143[m]> It's rare to find setup in india which are funky , it cost to much to setup one
< jeffin143[m]> It's rare to find setup in india which are funky , it cost to much to setup one
< rcurtin> favre49: nice, I should not have opened that up :)
< jeffin143[m]> https://ibb.co/sqRM6z1
< jeffin143[m]> One of my colleagues have me the pic
< jeffin143[m]> Check this out :)
< rcurtin> jeffin143[m]: nice, lots of room for lots of terminals :)
< favre49> I hope their neck is ok, seems like a huge strain :D
< 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
< jeffin143[m]> https://ibb.co/ncKZds1 :)
< jeffin143[m]> He has 8 😂
< rcurtin> reminds me of The Matrix!
< rcurtin> I guess he is an Iron Man fan :)
< jeffin143[m]> They are insane people
< jeffin143[m]> :)
< LakshyaOjhaGitte> Hey guys
< LakshyaOjhaGitte> Wanted a little help.....
< LakshyaOjhaGitte> I was wondering if there is some doc or something to understand how images are stored in ml pack
< 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
< LakshyaOjhaGitte> Like in pytorch they use n layered matrice or something
< LakshyaOjhaGitte> yeah that I am familiar with
< LakshyaOjhaGitte> But I wanted to dig deeper into this
< 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
< LakshyaOjhaGitte> like How height, width and channel is stored in matrix
< LakshyaOjhaGitte> Ok
< rcurtin> for images, we have the data::Load() overload for images that also takes an ImageInfo, which stores some metadata about the image
< rcurtin> and can then be used again when data::Save() is called
< 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)
< rcurtin> there are two PRs dealing with image support open that I know of right now (maybe there are more): #2312 and #2019
< LakshyaOjhaGitte> ohh
< rcurtin> perhaps some of the changes in there might be clarifying?
< 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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< LakshyaOjhaGitte> These pr is exactly what I was looking for, thank you so much
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< LakshyaOjhaGitte> I was too bored to read research papers at this moment XD
< LakshyaOjhaGitte> Also by any chance is there a reference in the mlpack docs regarding use of images?
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< rcurtin> there's some documentation in https://www.mlpack.org/doc/mlpack-git/doxygen/formatdoc.html ; but it can always be improved if you see anything wrong or unclear :)
< LakshyaOjhaGitte> Thanks very helpful
< LakshyaOjhaGitte> :)
< MostafaNabiehGit> @matrixbot What is the best way to contribute with you now ?
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< Saksham[m]> ryan Hi should we send a draft of the proposal to you before submitting it on the GSOC website ?
< 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
< rcurtin> if we have any questions as we review it, we can always get in touch and ask
< Saksham[m]> That makes sense, thanks a lot
< AbishaiEbenezerG> x-special/nautilus-clipboard
< AbishaiEbenezerG> copy
< AbishaiEbenezerG> file:///home/abishai/Pictures/Screenshot%20from%202020-03-18%2021-49-33.png
< AbishaiEbenezerG> hey mlpack , got a question here
< AbishaiEbenezerG> especially for @joeljosephjin @zoq
< 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
< AbishaiEbenezerG> my understanding of the error is that the number of parameters in the policy( ) function call do not match. am i right?
< AbishaiEbenezerG> i also know that there's something more i'm missing here. but i can't exactly find it.
< AbishaiEbenezerG> this is the implementation as shared by @joeljosephjin
< 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
< 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....
< PrinceGuptaGitte> I've provided a temporary solution to the issue #2310 in PR #2316 . Let me know if it's a good thing.
< AbishaiEbenezerG> https://codeshare.io/2BLeVb
< AbishaiEbenezerG> same code as above...
< AbishaiEbenezerG> any help would be greatly appreciated
< rcurtin> PrinceGuptaGitte: did you try the fix from the PR that I suggested in #2310?
< PrinceGuptaGitte> I just tried it, it works. I missed it in the conversation. My bad.
< PrinceGuptaGitte> That was indeed the reason
< PrinceGuptaGitte> Thanks @rcurtin
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< 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.
< rcurtin> PrinceGuptaGItte: glad that it worked, I think there are still some memory issues to work out though perhaps
< jeffin143[m]> Rcurtin :)
< jeffin143[m]> Done resolved everything for the image converter binding :)
< rcurtin> awesome! hopefully my changes did not make it too hard :)
< 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 https://github.com/mlpack/mlpack/blob/e4d6715ce1c14a1bb88abbd86ffaa1e6845113b2/src/mlpack/methods/ann/ffn.hpp#L382 . 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
< 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??
< kartikdutt18Gitt> @rcurtin, It worked for me as well. Just had to create a copy for a layer that I had added. Thanks a lot.
< 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.
< 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
< 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?
< 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
< 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
< jeffin143[m]> Should this output
< 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)
< jeffin143[m]> Sorry for bothering but I just wanted to make it sure
< himanshu_pathak[> rcurtin: Yes, I think we should wait zoq
< jeffin143[m]> No issues , I ll just work on other pr
< himanshu_pathak[> * rcurtin: Yes, I think we should wait for zoq
< jeffin143[m]> Lots of pr in my hand
< 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
< rcurtin> jeffin143[m]: yeah, definitely, tons of PRs in general. the last few weeks before the GSoC application deadline are always crazy :)
< MostafaNabiehGit> @matrixbot
< himanshu_pathak[> nice setuprcurtin
< rcurtin> himanshu_pathak[: thanks, I just wish I spent a little less time stuck at it :)
< himanshu_pathak[> Yeah it is addictive when you work like this
< SriramSKGitter[m> @mostafanabiehMourad : Did you have a look at /`src/mlpack/methods/linear_svm` ? Perhaps there's something of help to you there :)
< MostafaNabiehGit> @sriramsk1999 Thank you so much
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< 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?
< bisakh[m]> Hi zoq
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< 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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