mlpack IRC logs, 2018-06-02

Logs for the day 2018-06-02 (starts at 0:00 UTC) are shown below.

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--- Log opened Sat Jun 02 00:00:45 2018
00:17 -!- wenhao [731bc1e7@gateway/web/freenode/ip.115.27.193.231] has quit [Ping timeout: 260 seconds]
01:07 < zoq> ShikharJ: What about writing a simple shell script that tests a couple of parameters? We can write a simple executable (gan_main.cpp) and use the serialization feature to save the network; we could also just save the weights.
01:08 < zoq> ShikharJ: About the optimization, we can add the support later with the batch support, I think there are are couple papers out there that use different optimization methods, but I don't think the difference is huge.
01:13 < zoq> ShikharJ: You can also work on the benchmark system, perhaps preparing the dataset etc. is faster that way, your call. Usually, I use a combination of tmux + mosh + vim which works quite well on a remote machine.
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10:02 < jenkins-mlpack> Project docker mlpack nightly build build #337: SUCCESS in 2 hr 48 min: http://masterblaster.mlpack.org/job/docker%20mlpack%20nightly%20build/337/
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10:46 < Atharva> zoq: In all the layer objects there is a inputParameter member but it never seems to be used anywhere. Can you tell me what I am missing here?
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12:34 < ShikharJ> zoq: I'll post the results tomorrow, then we can merge the PR.
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13:26 < travis-ci> ShikharJ/mlpack#169 (DCGAN - 96b51c1 : Shikhar Jaiswal): The build has errored.
13:26 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/1f6ee54a2196...96b51c1f8a4b
13:26 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/387085488
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15:10 < zoq> ShikharJ: I like the idea to use the existing class. I thought about the optimizer seperation. Let me comment on the PR.
15:10 < zoq> Atharva: This is meant to be used for the recurrent attention model, there is an open PR; but you are currently it's not used. And I think we could remove the parameter for the layer that aren't going to be used, if you like to.
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15:50 < Atharva> zoq: Can you please point me to the PR. Is it clear in the PR which layers require that parameter?
16:11 < Atharva> zoq: Is it okay to throw a std::error while constructing a layer object if there is some mistake we think that people might make when they use it for the first time?
16:11 < Atharva> rcurtin:
16:25 < zoq> I thought there was an open PR, let me check the code.
16:25 < zoq> okay, we need the conv and linear layer.
16:26 < zoq> yeah, this is fine, you can also use Log::Fatal
16:28 < Atharva> zoq: Okay, I will open a PR removing inputParameter from all the other layers. I guess the ones in ffn and ffn_impl are required.
16:28 < Atharva> zoq: Cool, thanks for that.
16:36 < ShikharJ> zoq: I'll prefer sticking to the plan I mentioned. Impllement GAN and DCGAN till Phase I (next 7 days), and then take up the task for optimizer separation and batch sizes together.
16:36 < ShikharJ> zoq: What is your preference?
16:45 < zoq> I do not have a preference, both is fine for me.
16:46 < ShikharJ> zoq: Ah, okay. I'll post the results tomorrow and inform you then :)
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21:26 < travis-ci> ShikharJ/mlpack#170 (DCGAN - af748b1 : Shikhar Jaiswal): The build has errored.
21:26 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/96b51c1f8a4b...af748b16f6d5
21:26 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/387213181
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--- Log closed Sun Jun 03 00:00:47 2018