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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< AyushSingh[m]> Okay, I will again look into it and come up with a suggestion.
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< mehulkc[m]> hello , can someone please help me with setting up the mlpack environment
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< NippunSharmaGitt> Hi @mehulkc you can take a look at the [guide](https://www.mlpack.org/doc/mlpack-git/doxygen/build.html)
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< AyushSingh[m]> (edited) ... will again look into it and come up with a suggestion. => ... will look to solve the problem by some other method.
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< mehulkc[m]> Yes I have read it, Still I have some issues
< NippunSharmaGitt> If you have any issues you can ask them here
< mehulkc[m]> okay
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< mehulkc[m]> Thank you
< jeffin143[m]> ryan : you it took 8 years for the above pr
< jeffin143[m]> You are fast 😂😝
< jeffin143[m]> ryan : it took 8 years for the above pr to get merged
< jeffin143[m]> You are fast 😂😝
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< ShahAnwaarKhalid> HI! I'm trying to understand what the concat_performance layer does. Is it supposed to be used when there's a very large input and so to compute forward and backward passes for the corresponding layer, you iteratively take small sections from it and compute the foward() or backward() function and append that to the output?