ChanServ changed the topic of #mlpack to: "mlpack: a fast, flexible machine learning library :: We don't always respond instantly, but we will respond; please be patient :: Logs at http://www.mlpack.org/irc/
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< kaushal[m]> <kaushal[m] "yes I am using the master branch"> "Like the latest master branch " means ??
< jonpsy[m]> <kaushal[m] ""Like the latest master branch ""> Latest master branch refers to the master branch of the original repo
< kaushal[m]> yes well I am using that but Its still showing that error
< kaushal[m]> I cloned the repo again and re-build it
< kaushal[m]> still the same
< kaushal[m]> <kaushal[m] "I cloned the repo again and re-b"> re-build the mlpack (for ubuntu)
< jonpsy[m]> Do you just want to run the example?
< jonpsy[m]> If your interest is just running the example, you can try codespaces
< kaushal[m]> I want to run the example as well as contribute to it
< jonpsy[m]> I see, pretty sure there's a prob with your specs + command you're running
< kaushal[m]> yes , I am unable to find that
< kaushal[m]> I have re-did everything
< jonpsy[m]> I think it'll be better if you create an issue :)
< RishabhGargGitte> @kaushal , can you also check if the output of cmake command shows some warning like couldn't find boost serialization. Maybe it is unable to find specifically boost serialization and thats causing the trouble.
< jonpsy[m]> With your specs + the commands you've run
< kaushal[m]> yes but zoq
< kaushal[m]> said that there is problem is some branch version I ma using
< jonpsy[m]> Which is why he suggested you use master of original repo
< kaushal[m]> <RishabhGargGitte "@kaushal , can you also check if"> ok
< kaushal[m]> <jonpsy[m] "Which is why he suggested you us"> well I am using master branch
< jonpsy[m]> I see. Try Rishabh Garg (Gitter) suggestion
< kaushal[m]> some boost dependencies is missing
< kaushal[m]> for sure
< kaushal[m]> I am using libboost-dev 1.71 (newest version )
< kaushal[m]> but @zog
< kaushal[m]> but zoq
< kaushal[m]> said that boost is not necessary if i use master branch
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< AakashkaushikGit> Hey kaushal, zoq is right we removed boost serialisation with cereal in the master branch, that means either you are not using mlpack's master branch or your master branch is not updated with mlpack's master branch.
< AakashkaushikGit> Hey Mayank your build is failing. basically you can check the error when you do the `make` command and that's why most of the test cases are failing.
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< AakashkaushikGit> > Hey kaushal, zoq is right we removed boost serialisation with cereal in the master branch, that means either you are not using mlpack's master branch or your master branch is not updated with mlpack's master branch.
< AakashkaushikGit> and swapped it with cereal*
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< kaushal[m]> <AakashkaushikGit "Hey kaushal, zoq is right we rem"> i just cloned the master branch yesterday
< AakashkaushikGit> Can you drop the complete output to something like [pastebin](https://pastebin.com/) and share the link her
< AakashkaushikGit> Also i can check your master branch if you want me to, what is your github id ?
< NippunSharmaGitt> Hi. I wanted to build mlpack from source for all its available bindings (python, julia etc.) but for that I need to install each language (of required version) as well as various dependencies (such as Gonum for Go etc.). Is there any way to make this process easy for me ?
< AakashkaushikGit> I don't think there is an automatic way to install missing dependencies when building bindings for those languages.
< RishabhGargGitte> Hey @NippunSharma , I think the easiest way could be to use a docker container with all those dependencies already installed in it. If such a thing exists then you can easily use it. But if it doesn't exists, then you can take the initiative and take some pain to make a docker container with the dependencies installed. Then we can integrate that container's configuration with the codebase and it will be very easy for
< RishabhGargGitte> others in future.
< RishabhGargGitte> Hey @shrit @zoq @rcurtin , does any such docker container already exists ?
< shrit[m]> I am not sure, but it should not hard to build.
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< rcurtin[m]> someone has made one of these already, but I don't have a link to where it was being worked on, sorry about that
< rcurtin[m]> it's not too hard to figure out all the dependencies... CMake will tell you what you're missing each time, and if you're on Debian you can use `apt-cache search` to find the right name of the package
< kaushal[m]> <AakashkaushikGit "Also i can check your master bra"> https://github.com/kaushal07wick/mlpack
< kaushal[m]> <AakashkaushikGit "Can you drop the complete output"> https://pastebin.com/
< kaushal[m]> <AakashkaushikGit "Can you drop the complete output"> https://pastebin.com/
< kaushal[m]> <AakashkaushikGit "Also i can check your master bra"> https://pastebin.com/Z3d4vhdu
< kaushal[m]> <AakashkaushikGit "Can you drop the complete output"> https://pastebin.com/Z3d4vhdu
< jonpsy[m]> Hi, I've seen @favre's [PR](https://github.com/mlpack/ensmallen/pull/120) which was great work so far! I wonder why it was closed in favor of NSGA2?
< jonpsy[m]> DLTZ, Indicators and NSGA3 shouldnt have anything to do with NSGA2 I think..
< gitter_rituraj-c> Hi everyone I've tried to build mlpack from source in Linux but my OS freezes . At first I've used up all the cores which obviously ends up bad and then I've used only half the number of cores but still it freezes. Any suggestions ??
< gitter_rituraj-c> PS: I'm using Ubuntu 20.04LTS and I have 8gb ram and AMD Ryzen 5 3550H
< zoq> gitter_rituraj-c: Hello, half the cores means -j2?
< gitter_rituraj-c> yess -j2
< kaushal[m]> <gitter_rituraj-c "PS: I'm using Ubuntu 20.04LTS an"> make j1 worked fine for me
< zoq> gitter_rituraj-c: mlpack is heavy on memory, we use a lot of templates; so I would say build with -j1
< zoq> Also, you might want to restart before the next build.
< jonpsy[m]> <kaushal[m] "make j1 worked fine for me"> +1
< gitter_rituraj-c> OKk let's try it
< MohomedShalik[m]> I use Ubuntu 18.04 with 16 Gb memory and build using all 4 cores. And my lap does freeze randomly during build
< zoq> Another quick solution is to increase SWAP.
< gitter_rituraj-c> Yaa already I had to hard shutdown :/
< kaushal[m]> <MohomedShalik[m] "I use Ubuntu 18.04 with 16 Gb me"> well actually its very heavy on the cpu , use make -j1 and it will work fine
< kartikdutt18Gitt> Hey, Also you can try building without language bindings (that you won't use) and turn off tests (if not needed) using CMake flags.
< zoq> kartikdutt18Gitt: bindings are turned off by default now.
< jonpsy[m]> Hey zoq
< jonpsy[m]> About the refactoring, I think it'll be too complex. So I've decided to stick with just algos.
< jonpsy[m]> favre did some work on NSGA III & indicators. I thought I could continue that along with SPEA. Lemme know your thoughts
< zoq> jonpsy[m]: About the PR, I think Rahul closed this one, because NSGA2 showed more potential, but if you like to continue that one, please feel free.
< zoq> jonpsy[m]: Yes, I really like NSGA III, would be nice to have it in ensmallen.
< zoq> jonpsy[m]: We can always improve things along the way, that applies to each project.
< RishabhGargGitte> Hey all, I am working on a feature and I have to raise a runtime error and warning. So, which should I prefer -- `Log::Fatal` or `std::runtime_error` ?
< zoq> RishabhGargGitte: We haven't established a standard way (https://github.com/mlpack/mlpack/issues/891) so either is fine I think, I slightly lean torwards Log::Fatal mainly because it makes refactoring easier at some point.
< jonpsy[m]> > Hey all, I am working on a feature and I have to raise a runtime error and warning. So, which should I prefer -- `Log::Fatal` or `std::runtime_error` ?
< jonpsy[m]> Voting on log:fatal =P
< RishabhGargGitte> Ok. Thanks for the info @zoq.
< RishabhGargGitte> Can you also `ResetSetings` and `TestFixture` struct in main tests ?
< RishabhGargGitte> **Can you also clarify the use of
< AakashkaushikGit> these issues mostly arise when you are using a library that was compiled with some other version, i faced the same issue today when i was using version of armadillo (10.x) and got those undefined reference issues so i went ahead and compiled the version 9.800.x and deleted all files in the build folder and recompiled mlpack that fixed the issue.
< kaushal[m]> <AakashkaushikGit "these issues mostly arise when y"> well I rebuild it yesterday
< AakashkaushikGit> Are you getting these error while building the library or while using any part of it ?
< AakashkaushikGit> (edited) ... these error while ... => ... these errors while ...
< rcurtin[m]> Rishabh Garg (Gitter): jonpsy : `Log::Fatal` actually throws a `std::runtime_error` once it receives a newline character, so that seems to me like it would be the way to go :)
< kaushal[m]> <AakashkaushikGit "Are you getting these error whil"> while trying to run examples
< jonpsy[m]> > Rishabh Garg (Gitter): jonpsy : `Log::Fatal` actually throws a `std::runtime_error` once it receives a newline character, so that seems to me like it would be the way to go :)
< jonpsy[m]> +1, besides I've learnt , always try n use stuff provided by library before considering std
< gitter_rituraj-c> Okay so finally I built mlpack on my OS I know it's too late but I was having a tough time configuring Linux. So now that I have built mlpack from source so should I implement mlpack on some sample porgrams. Sorry for the naive question.
< kaushal[m]> <gitter_rituraj-c "Okay so finally I built mlpack o"> yes u can
< kaushal[m]> <gitter_rituraj-c "Okay so finally I built mlpack o"> yes u should
< gitter_rituraj-c> Any other suggestions would be really helpful :)
< kaushal[m]> <kaushal[m] "https://www.mlpack.org/doc/stabl"> try this tutorial to get to know how to use the mlpack programs
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< rcurtin[m]> 👍️
< gitter_rituraj-c> Is there any specific command on linux to check if mlpack is installed on my system
< shrit[m]> `sudo updatedb`
< shrit[m]> `locate libmlpack.so`
< rcurtin[m]> that depends on the distribution; if you're on Ubuntu, `apt-cache policy '*mlpack*'` should tell you, and you'll have to look in the `Installed:` line for each package. shrit 's solution works just fine too
< rcurtin[m]> (and his solution will work on any distribution)
< gitter_rituraj-c> @rcurtin ap-cache policy '*mlpack*' worked for me :)
< gitter_rituraj-c> *apt
< rcurtin[m]> 👍️
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