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/
< rcurtin>
birm[m]1: for now we added an azure workaround in #2306, so if branches merge from master then they should trigger azure for a rebuild
< jeffin143[m]>
Rcurtin : how do we create variable length columns in armadillo ???
< rcurtin>
jeffin143[m]: that's not possible with arma::mat, to do that would require the use of arma::field
< rcurtin>
(alternately, consider 'std::vector<arma::vec>' or something?)
< rcurtin>
if this is about the column-major string encoding, I do think that whatever you're doing now can just be transposed with no issue
< jeffin143[m]>
Because in string encoding we give output as without padding , that means variable length rows , but how do we that in vectors
< jeffin143[m]>
Ok I will just take a look
< jeffin143[m]>
Then
< rcurtin>
hmm, I think we would need padding in this case
< jeffin143[m]>
Can we follow this approach ,. Merge string encoding as this and then refactor ? If you don't mind
< rcurtin>
in this case I think I'd rather wait, since the current string encoding is "backwards" and wouldn't give results that are ready to use with other mlpack code
< rcurtin>
really there's no hurry---we can easily release another one as soon as those are in
< rcurtin>
(I say this a lot, so I hope it still means something, but I really would like to have significantly more frequent releases for mlpack)
< rcurtin>
(perhaps not quite every PR, which is basically the ensmallen release cycle, but certainly every couple weeks. the 3.3.0 release has been slow since it was held up on Julia)
< jeffin143[m]>
Ok , then I will take time and see into this issue
< rcurtin>
yeah, there is no hurry, don't worry :)
< rcurtin>
anyway, it's late here---I'm going to head to bed. 'night!
< jeffin143[m]>
Good night
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< favre49>
I really like arch, but what's not fun is spending your afternoon fixing some obscure bug that unfortunately breaks some part of your system :)
< favre49>
Well I think it's fixed... I've probably jinxed it now though
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< hemal[m]>
I've shared my proposal draft for review through GSoC portal. @zoq @rcurtin please provide your reviews whenever you get time.
< pickle-rick[m]>
rcurtin: Should I send an email to the mailing list with a summary of my proposal? Or should we just submit the proposal through the GSoC portal, and hope for the best, since everyone will be busy with reviewing PRs and stuff?
< hemal[m]>
rcurtin: thanks for letting me know
< hemal[m]>
I'll Review some PRs to reduce some of the workload. 🙂
< zoq>
pickle-rick[m]: You can directly send it to the GSoC portal, we we have time we can provide feedback over there.
< zoq>
hemal[m]: Please feel free, any help is very much appreciated.
< pickle-rick[m]>
<zoq "pickle-rick: You can directly se"> zoq: Thanks! Good to know.
< zoq>
PrinceGuptaGitte: Maybe t he kernel size is wrong, did you build with DEBUG=ON, also might be good to step through the code with gdb.
< PrinceGuptaGitte>
I didn't build with DEBUG=ON, should I do that while building mlpack?
< zoq>
PrinceGuptaGitte: Yes, that enables bounds checks.
< zoq>
So with #2278 merged the macOS build should be fixed, great work Yashwant!
< rcurtin>
agreed, thank you!
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< himanshu_pathak[>
zoq (@freenode_zoq:matrix.org): I have sent a message on mailing list can you please reply
< zoq>
himanshu_pathak[: Will do later.
< himanshu_pathak[>
OK
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< LayMann>
hey are there qualification rounds or should i debug and PR something
< zoq>
LayMann: Hello, what do you mean with qualification rounds?
< LayMann>
i meant sometimes there are tasks given by an organization to filter the students
< zoq>
We don't require a contribution to be considered for GSoC.
< zoq>
There are some open issues, if you find something intersting, please feel free to work on it.
< LayMann>
so i should just write a proposal then
< LayMann>
?
< zoq>
Also there are open PR's that are waiting for a review, so if you like to help with a review, that's another great way to get familiar with mlpack.
< zoq>
You can, submit your proposal right away yes, it's certainly a great idea to get familiar with the codebase as well.
< zoq>
One question we often ask is how does this integrate into the codebase, that's difficult to answer if you haven't looked into the project.
< LayMann>
reinforcement learning is still an active project right?
< zoq>
LayMann: yes
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< M_slack_mlpack13>
I'm interested in working on reinforcement learning project and would like to contribute for ACKTER and Persistent Advantage Learning DQN algorithm. In the proposal should I need to mention all the technicalities after going through the required code base or should I need to mention brief workflow about how I'm going to implement in 12 weeks time?
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< zoq>
M_slack_mlpack13: Hello there, ideally you can find a good balance; perhaps you can point out some details that are important to know for the project or what key element makes the method stick out etc.; noo need to explain everything in detail.