mlpack IRC logs, 2018-05-12

Logs for the day 2018-05-12 (starts at 0:00 UTC) are shown below.

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--- Log opened Sat May 12 00:00:15 2018
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07:46 < manish7294> rcurtin: Thanks! the algo you suggested helped gaining significant speedups. 50k data points -> 43.53secs :)
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08:54 < travis-ci> ShikharJ/mlpack#133 (Deconv - f27f79f : Shikhar Jaiswal): The build has errored.
08:54 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/e708df9bdcca...f27f79fb5d75
08:54 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/378033868
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09:36 < travis-ci> ShikharJ/mlpack#134 (Deconv - 4b31aef : Shikhar Jaiswal): The build has errored.
09:36 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/f27f79fb5d75...4b31aef05dc0
09:36 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/378035137
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15:18 < travis-ci> ShikharJ/mlpack#135 (AtrousConv - 78e126c : Shikhar Jaiswal): The build has errored.
15:18 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/acf54f4614e1...78e126c5c790
15:18 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/378112192
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15:21 < ShikharJ> rcurtin: zoq: You There?
15:21 < zoq> ShikharJ: yes
15:21 < ShikharJ> Hi, I wanted to discuss regarding the dilated convolution layer. Is this a good time to talk?
15:22 < zoq> about to step out, but I can stay a little bit longer
15:24 < ShikharJ> Ah, sure, just a small doubt. Aarush (in his PR) had created a separate NaiveAtrousConvolution rule for the additional dilation parameter. But I think we can incorporate that in the existing naive_convolution implementation
15:24 < ShikharJ> would this be a good idea?
15:25 < ShikharJ> That way, there'd be no need for an additional file, and we can just provide the default dilation parameter as 1 for the existing layers.
15:26 < zoq> Right, I don't think anyone is going to use something like a NaiveAtrousConvolution rule for another method anyway.
15:28 < ShikharJ> Yeah, also, we can then use a combination of parameters to obtain something like a Dilated Transposed Convolution layer, and so on (something that Tensorflow provides as separate methods).
15:29 < zoq> hm, does anyone use a Dilated Transposed Convolution layer?
15:30 < ShikharJ> I'm not sure, never came across any paper that explicitly used that, but theoretic examples of such a convolution wouldn't be hard to find.
15:39 < zoq> not sure, it makes sense to combine both, one captures a larger receptive field and the other one is mainly used for upsampling, have to think about it. But, if I remember right, I saw a paper that used both methods in a network.
16:00 < ShikharJ> Agreed. This sounds plausible to me :)
16:03 < ShikharJ> Pushed in the changes, for now, only the additional tests for Layer Normalization and Dilated Convolutions are remaining.
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16:45 < travis-ci> ShikharJ/mlpack#136 (AtrousConv - 876a786 : Shikhar Jaiswal): The build has errored.
16:45 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/78e126c5c790...876a786b1bd3
16:45 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/378126462
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17:31 < travis-ci> ShikharJ/mlpack#137 (AtrousConv - bd1ad3d : Shikhar Jaiswal): The build has errored.
17:31 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/876a786b1bd3...bd1ad3ddd2ae
17:31 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/378127145
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--- Log closed Sun May 13 00:00:17 2018