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/
< chopper_inbound[> How can I get/set the `weight` of the linear layer (`linear.hpp`)? There is such method for `bias` and for concatenated form of `weight` and `bias` but not just `weight`. I can get the `weight` from `weights` but that would only increase the lines of code or make the expression complex. Is this something intentional? I require to initialize the `weight` of that particular layer with different initialization rule than
< chopper_inbound[> that of the network's. Is there any other way to do this?
< walragatver[m]> jeffin143 : Let's have a meet day after tomorrow? Let me know what you think about it.
< walragatver[m]> Also, I hope you have seen the mail I have sent you two days ago. If you have any doubts feel free to ask about it.
< walragatver[m]> chopper_inbound : There is no direct way to access the `weight` of a layer directly
< walragatver[m]> I think you need to use the extra lines of code for that
< walragatver[m]> Regarding change in intialization rule. I am sure whether it is possible currently or not.
< walragatver[m]> But I think it can be done or atleast we can expose that feature inorder to make it possible.
< walragatver[m]> It would be great if you could open an issue for it. I think zoq would be knowing about it in detail.
< chopper_inbound[> @walragatver:matrix.org: Right. Let me open an issue for that.
< jeffin143[m]> walragatver: oops , I have no clue why did that mail was not In my inbox and was in social section ,
< jeffin143[m]> Just happened to look
< jeffin143[m]> I am on it
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< jenkins-mlpack2> Project docker mlpack nightly build build #702: UNSTABLE in 3 hr 23 min: http://ci.mlpack.org/job/docker%20mlpack%20nightly%20build/702/
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< KhizirSiddiquiGi> nevermind, I did a clean build and it works as expected, thanks. :thumbsup:
< yashwants19[m]> Happy to hear, clean build worked. :)
< KhizirSiddiquiGi> thanks :)
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< HimanshuPathakGi> Hey @saksham189 When you get time time take a look at my RBFN pr now it is giving right prediction and tests are passing now. I have to add multiple non-linear activation functions I will open a separate PR for that
< jenkins-mlpack2> Project mlpack - git commit test build #411: UNSTABLE in 1 hr 12 min: http://ci.mlpack.org/job/mlpack%20-%20git%20commit%20test/411/
< zoq> Hm, we might habe to slightly increase the tolerance for SoftmaxRegression test.
< HimanshuPathakGi> zoq are you talking about my pr ??
< zoq> HimanshuPathakGi: No, about the last jenkins-mlpack2 message
< HimanshuPathakGi> Oh got it sorry for the vague question
< zoq> No worries :)