verne.freenode.net changed the topic of #mlpack to: http://www.mlpack.org/ -- We don't respond instantly... but we will respond. Give it a few minutes. Or hours. -- Channel logs: http://www.mlpack.org/irc/
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< travis-ci>
dineshraj01/mlpack#4 (rsmodel-boost-variant-visitor - 5580af2 : dinesh Raj): The build is still failing.
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< vivekp>
Hi, I'm facing a problem with build process.
< vivekp>
it appears that make doesn't build ann module along with a bunch of others e.g. amf, approx_kfn etc.
< vivekp>
I'm working on top of latest git master.
< vivekp>
Did I miss something ?
< rcurtin>
vivekp: what's the command you're using to build?
< vivekp>
make after configuring cmake inside build directory
< rcurtin>
what happens when you type 'make mlpack_approx_kfn'?
< vivekp>
okay, let me check
< vivekp>
it starts building that module
< rcurtin>
and if you type make it doesn't?
< vivekp>
and with make_ann, I get an error: make: *** No rule to make target 'mlpack_ann'.
< vivekp>
rcurtin: yes
< rcurtin>
so if you type make, it never builds mlpack_approx_kfn?
< rcurtin>
and you have not modified the CMake configuration?
< vivekp>
make mlpack_ann* -- sorry about that
< rcurtin>
there is no target mlpack_ann, that does not exist
< rcurtin>
mlpack is made up of a core library ('make mlpack'), header files ('make mlpack_headers'), and command-line programs ('make mlpack_approx_kfn', 'make mlpack_knn', etc...)
< rcurtin>
so there are some cases where a command-line program does not exist for a particular set of code in mlpack/methods/
< vivekp>
rcurtin: okay, understand
< vivekp>
and sorry about the confusion. I just had a second look and the modules that are never built are amf and ann
< rcurtin>
no worries---the AMF code does not actually get built into a command-line program either
< rcurtin>
that is used in mlpack_nmf and mlpack_cf, but there is no mlpack_amf program
< vivekp>
ok, understood. Thank you for your prompt reply
< rcurtin>
sure, sorry if it was a little short, I am dealing with a bunch of things at once
< rcurtin>
time-division multiplexing my responses causes the quality to suffer a bit :)
< vivekp>
not a problem at all. I got my doubt resolved :)
< rcurtin>
sure, glad I could help---feel free to ask any more questions if needed
< rcurtin>
I've found hosting for a system to add to our build server; it has 64 cores and 192GB RAM, so I hope it will come online in the next few weeks
< rcurtin>
there are still a few details to work out (including what it will be named, of course), but this will add to our already-overpowered build server setup :)
< rcurtin>
and when I figure out what the issue is with the three 64-core sparc64 machines is (they hang, it must be a kernel bug or something), then we'll have an even more overpowered setup
< zoq>
wow, lying around somewhere? The build setup is going to be awesome.
< sumedhghaisas>
zoq: Hey Marcus
< sumedhghaisas>
Actually I will like to work on it as a student
< rcurtin>
zoq: yeah, it was originally a system that was built for the FASTLab, but then the FASTLab kind of disbanded while I was in graduate school and nobody was left but me to take care of all the equipment
< rcurtin>
so I had to spend some time negotiating with connections I still had on campus to see if someone was willing to sponsor it, etc., and finally I heard back and the answer is yes, so hopefully it will come online soon
< zoq>
sumedhghais: ah okay, great. So yes, I think some MANN like NTM + merge + batch norm should be enough work we could also think about adding some other features like recurrent dropout.
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< travis-ci>
mlpack/mlpack#1781 (master - 28202d7 : Ryan Curtin): The build passed.
< zoq>
rcurtin: Sounds great, same location as for the benchmarks/masterblaster machines?
< sumedhghaisas>
zoq: okay. I will read about NTM and get back to you. I am confident about merge and batch normalization but I have to read about NTM a little
< zoq>
sumedhghais: Sounds good, you could also take a look at other MANN's if you like, it hasn't to be NTM.
< sumedhghaisas>
zoq: can you please refer me some papers that I can look at?
< rcurtin>
zoq: nope, this system will be hosted in atlanta; masterblaster is in Los Angeles, and the benchmarking systems are in Oregon. looks like masterblaster will have to move to Oregon, so I'll have to get that process in motion
< zoq>
sumedhghais: I would recommend to take a look at e.g. the DNC (Hybrid computing using a neural network with dynamic external memory) a successor of the NTM model or the HAM (Hierarchical Attentive Memory) paper, both papers have a lot of references to other ideas.
< zoq>
rcurtin: I guess, since you know the atlanta guys no hassle with opening ports etc.
< rcurtin>
yeah, this system will be located on the Georgia Tech campus, and I still know all the support people and their procedures, so no stupid problems with ports
< rcurtin>
Symantec IT will not be involved at all :)
< zoq>
I guess, the atlanta machine doesn't have a Nvidia GPU, just asking :)
< sumedhghaisas>
zoq: Sure. I will take a look.
< rcurtin>
unfortunately no, but I am still fighting to get some GPUs for either masterblaster or other systems
< rcurtin>
everything moves glacially slow at Symantec, so I thought we were ordering new GPUs three months ago, but it still hasn't happened
< zoq>
Maybe one day :)
< rcurtin>
yeah, we'll see...
< rcurtin>
part of the problem is that most of the company is out in mountain view and I'm here in atlanta, so I can't regularly ask the guy on our team who orders GPUs what the status is
< rcurtin>
I could send him emails every day but that might be a bit more rude and annoying than if I was asking him in person every few days :)
< zoq>
Absolutely, I'm confident that one day someone says "Hey, here is the Graphics Card you asked for".
< rcurtin>
one day in 2019 maybe :)
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< travis-ci>
mlpack/mlpack#1782 (master - 6b2d239 : Ryan Curtin): The build was broken.
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< ashk43712>
Hi, I am Ashish. I am new to mlpack and want to contribute. I have compiled and installed mlpack. I found the idea of "Alternatives to neighborhood-based collaborative filtering" very interesting for GSOC17. I have a good C++ and Machine Learning knoeledge. Can someone point me to the right direction so that I can start contributing by solving some bugs or adding new features
< rcurtin>
I know there are not many bugs open for the CF package right now, but actually I was just talking to someone yesterday and thought of a good one...
< rcurtin>
if you run mlpack_cf on the movielens dataset with the RegSVD optimizer, it performs well and gets like 0.8 RMSE
< rcurtin>
but if you use NMF or SVDCompleteIncremental or SVDIncompleteIncremental or SVDBatch, then the RMSE is very bad
< rcurtin>
I think this is because the default parameters for those optimizers are not good
< rcurtin>
so if you wanted, you could see if you can reproduce that issue, and then see if you can find parameters for the optimizers that give better results
< rcurtin>
I know that maybe that is a lot to ask as a first contribution but it's what I can think of right now :)\
< ashk43712>
okay, thanks a lot
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< rcurtin>
good to know my addition of a space to the range search code did not affect the runtime :)
< zoq>
:)
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