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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< zoq> theSundayProgram: Hello, looks like, I fixed the rnn issue.
< theSundayProgram> Thanks. I'll take a look.
< zoq> theSundayProgram: I'll have to test it before I make a commit.
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< Divyam> i am compiling simple program using g++ but it is giving error
< wasiq> what's the error?
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< ranjan1234> Hi!
< ranjan1234> where is the implementation of scd ?
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< will__> Hi, I'm a student of Central South University, China, and intend to participate in the Google Summer of Code project.
< will__> I wonder how many people do you need for one specific project
< will__> for example, I am interested in Neuroevolution algorithms.
< will__> Do I have to compete with other applicant?
< Divyam> what are steps to compile simple program
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< ranjan1234> Divyam: install the package
< ranjan1234> g++ your_prog.cpp -lmlpack -std=c++11
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< travis-ci> awhitesong/mlpack#8 (HardTanH - 7de1645 : Dhawal Arora): The build is still failing.
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< travis-ci> awhitesong/mlpack#9 (LeakyReLU - 4bde5a9 : Dhawal Arora): The build was broken.
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< yvtheja_> zoq, I see that s = 4.59 for sigmoidal function in the paper.
< yvtheja_> zoq, Could you please have a look :)
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< rcurtin> ranjan1234: there is not an SCD implementation in mlpack
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< travis-ci> mlpack/mlpack#583 (master - fc5a4ac : marcus): The build was broken.
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< zoq> yvtheja_: The value used in that particular test has nothing to do with the value from the paper.
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< yvtheja_> zoq, And also does FFN use sigmoid activation function??
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< yvtheja_> zoq, sorry, but the terminology is completely different than what I used to :)
< zoq> yvtheja_: If you use the SigmoidLayer which is an alias for BaseLayer<LogisticFunction>: https://gist.github.com/zoq/c95fe0b63c640b011828
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< yvtheja_> zoq, I am little confused with layer terminology
< yvtheja_> zoq, With Iris dataset, we have 5 input units including bias right?
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< yvtheja_> zoq, LinearLayer<> inputLayer(5, 2); BiasLayer<> inputBiasLayer(2);
< yvtheja_> zoq, Could you please help me understand how we considered inputLayer(5,2) and BiasLayer(2) ?
< zoq> yvtheja_: The iris dataset uses 4 features for each sample. So the input layer should be LinearLayer<> inputLayer(4, 2);
< zoq> yvtheja_: the bias layer is correct.
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< yvtheja_> zoq, Why it is (4,2) ? The 2 signifies the number of hidden units in hidden layer?
< zoq> yvtheja_: Yes, its the number of units in the hidden layer.
< yvtheja_> zoq, And for the biasLayer, do we provide two bias units?
< yvtheja_> zoq, Or it's indicating the entire bias units used in the network?
< zoq> The bias layer has one input unit, and connects to two hidden units. You can specify the bias value with the second parameter.
< zoq> The same two hidden units as for the input layer.
< yvtheja_> zoq, Got it :)
< yvtheja_> zoq, Thanks a lot :)
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< travis-ci> mlpack/mlpack#584 (master - cff6a98 : marcus): The build was fixed.
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< christie> hi
< christie> i wanted to apply to gsoc 2016
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< christie> hoping to do something on neuroevolution algorithms
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< christie> are the topics specified under "relevant tickets" the only stuff you can do ? (for Gsoc)
< zoq> christie: Hello, there's been some talk about this project in other threads on the
< yvtheja_> zoq, Why don't we use KathirvalavakumarSubavathiInitialization as default??
< zoq> mailing list. Here is a link (be sure to take a look at the replies):
< zoq> christie:: I'll see if I can add some more "easy" issues in the next couple of
< zoq> days. On the other side, you are always welcome to just poke around the library
< zoq> and try to fix any problems you find, or improve the speed of various parts.
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< zoq> yvtheja_: The default parameter are not necessarily good for a given problem, so it is suggested that the values used be tailored to the task at hand. If you think we should prefer KathirvalavakumarSubavathiInitialization over the other rules, I'm open, maybe we can run some tests.
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< palashahuja> zoq, for the test case of dropconnect network, could you give me an example how should the structure look like ?
< yvtheja_> zoq, The paper shows that the proposed method performs better than random weight initialization method and Nguyan-Widrow weight initialization. So, I just got a doubt that why we are using Nguyan-Widrow instead of using KathirvalavakumarSubavathiInitialization.
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< yvtheja_> zoq, yeah, I think I can implement some tests on it. Will carry with it after I finish test on KathirvalavakumarSubavathiInitialization.
< yvtheja_> :P
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< zoq> palashahuja: Take a look at the DropoutNetworkTest test. Instead of using the DropoutLayer in line 203 you could use the DropConnectLayer with the hiddenLayer1 (line 205). Does that make sense?
< zoq> yvtheja_: I guess, we can modify every layer that uses the Nguyan-Widrow rule in favor of KathirvalavakumarSubavathiInitialization. Afterwards we can run all ann tests and see if the results are the same or better.
< palashahuja> but we would still need an extra parameter for dropconnect layer ..
< palashahuja> ?
< yvtheja_> zoq, yup :)
< zoq> palashahuja: With extra parameter do you mean:
< zoq> LinearLayer<> hiddenLayer1(hiddenLayerSize, trainLabels.n_rows);
< zoq> DropConnectLayer<> dropoutLayer0(hiddenLayer1);
< zoq> ?
< palashahuja> But the extra parameter for dropconnectlayer for the layertype .. ?
< palashahuja> or should I go with what you just said ?
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< palashahuja> the above statement means that you are making two connections ..
< palashahuja> one with hiddenlayer and one with hiddenlayer as a dropconnect layer, right ?
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< zoq> palashahuja: Ah right, this just works if you specified the LinearLayer as default LayerType. you could also write DropConnectLayer<decltype(hiddenLayer1)> dropoutLayer0(hiddenLayer1) or DropConnectLayer<LinearLayer< > > dropoutLayer0(hiddenLayer1).
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< zoq> Yeah, I used the LinearLayer as parameter for the DropConnectLayer, but I build the network model withput the linear layer.
< zoq> palashahuja: Ah right, this just works if you specified the LinearLayer as default LayerType. you could also write DropConnectLayer<decltype(hiddenLayer1)> dropoutLayer0(hiddenLayer1) or │ DropConnectLayer<LinearLayer< > > dropoutLayer0(hiddenLayer1).
< palashahuja> zoq, so, if I don't have to insert hiddenLayer1 in modules, right ?
< zoq> yes, right
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< zoq> palashahuja: Something like this: https://gist.github.com/zoq/09bca043092e8ede472b
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< palashahuja> zoq, there is no dropout layer 0 I guess ?
< zoq> palashahuja: ah, yes
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< Lokesh> I am new to mlpack
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< Lokesh> so can anybody explain how to compile program
< ashutosh> I have cloned repo from github but not able to proceed further please help me
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< rcurtin> Lokesh: ashutosh: please see the mlpack tutorials: http://www.mlpack.org/tutorials.html
< Lokesh> i am not getting it?? is it same as how we compile using cpp code using g++ in ubuntu
< Lokesh> but it is giving error
< ashutosh> rcurtin: I'm going through it now ... thank you ...
< rcurtin> Lokesh: you need to read the build instructions
< Lokesh> if i want to run the simple program of timer in which directory should the program be kept and i want to save in cpp format am i right
< Lokesh> using g++ in ubuntu to compile the program
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< travis-ci> mlpack/mlpack#587 (master - a3a4656 : Ryan Curtin): The build is still failing.
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< ranjan123_> hello
< ranjan123_> please help me to compile the package with OpenMp support
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< ranjan123_> I have changed the in /mlpack/CMakeLists.txt like this ---> set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fopenmp -Wall -Wextra -ftemplate-depth=1000")
< ranjan123_> I am not sure will it work or not
< ranjan123_> please correct me if I am wrong!
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< rcurtin> ranjan123_: there is already OpenMP support in CMakeLists.txt...
< rcurtin> if OpenMP is found then -fopenmp is automatically appended to the compiler options
< ranjan123_> ohhk ! thank you rcurtin
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< ashutosh> Make is working only for 2%...
< ashutosh> After this make is failed and build exit without getting completed please help
< rcurtin> ashutosh: you need to provide actual information about what is failing
< rcurtin> did you read the error messages?
< rcurtin> if I can't see what problem you are having, then I can't help out
< ashutosh> May I send you the picture of terminal ?
< ashutosh> When it is getting failed
< rcurtin> paste the errors into pastebin please
< rcurtin> or some similar service
< rcurtin> no need to encode text errors as an image...
< ashutosh> Okay rcurtin
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< palashahuja> for the backward function of dropconnect, should the implementation be layer.Backward(layer.outputDataType(), error, delta)
< zoq> No, once you constructed the DropConnect layer, you should save the layer, so that you can used it inside the Forward and Backward function.
< palashahuja> I am talking about the saved layer over here ..
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< ashutosh> It's virtual memory exhaust error rcurtin
< rcurtin> ashutosh: I'm not surprised, that would have been my guess
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< travis-ci> mlpack/mlpack#588 (master - 4fa67e5 : Ryan Curtin): The build was fixed.
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< travis-ci> mlpack/mlpack#589 (master - a2deb0c : marcus): The build was fixed.
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< mehulsr> I want to contact the mlpack team for GSoC
< mehulsr> How do I get in touch?
< mehulsr> I mailed the mlpack owner
< rcurtin> mehulsr: what do you mean? who is the "mlpack owner"?
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< mehulsr> I mailed the mailing list but I got a failure notice
< rcurtin> did you read the failure notice?
< mehulsr> Yeah
< rcurtin> okay... what did it say?
< mehulsr> Non members cannot post
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< rcurtin> okay... so... you should become a member of the list, like it says!
< mehulsr> But my request got rejected
< rcurtin> your request to join the list was rejected?
< mehulsr> Yes :/
< rcurtin> what is your email?
< mehulsr> Umm..this is IRC
< mehulsr> Anyway, it's mehul.raje@gmail.com
< rcurtin> if you didn't want to share it publicly, you could have PM'ed me, but I can't check to see whether you are a member of the list without it
< rcurtin> how did you attempt to subscribe?
< mehulsr> Here
< rcurtin> and the mailing list rejected your attempt to subscribe? can you forward me the email that it gave you for why you could not be subscribed?
< rcurtin> ryan@ratml.org
< mehulsr> ok
< rcurtin> thanks
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< rcurtin> ah... maybe he left too soon... I haven't seen his forwarded email yet...
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< travis-ci> mlpack/mlpack#590 (master - f45c17b : marcus): The build passed.
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