2018-11-12 22:39
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/
01:41
<
zoq >
rcurtin[m]: Looks like dealgood is busy :)
01:42
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rcurtin[m] >
wow, that makes the build queue display on ci.mlpack.org really really long... sorry for any inconvenience š
01:43
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zoq >
Yeah, it's quite long, I guess it will take some time until we will see an empty list again.
01:45
<
rcurtin[m] >
Oh, I think that I actually need to cancel and restart. All the builds have to be done sequentially, so that they can use the cache for the previous build
01:47
<
rcurtin[m] >
that also has the nice benefit of not polluting the build queue :)
03:42
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AyushSingh[m] >
(edited) ... am a sharing a draft GSoC proposal. Looking forward for review, specifically in 'Project ... => ... am sharing a draft GSoC proposal. Looking forward for it's review, specifically of the 'Project ...
05:07
<
OleksandrNikolsk >
<ABHINAVANAND[m] "The implementation of ceil_mode "> ABHINAV ANAND already fixed this 10 days before in PR#2865 š¬
05:08
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OleksandrNikolsk >
> <@_slack_mlpack_U01RJC8AB2M:matrix.org> ABHINAV ANAND already fixed this 10 days before in PR#2865 š¬
05:08
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OleksandrNikolsk >
> Test values needed to be fixed also
05:08
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OleksandrNikolsk >
But I just did the Backward method
06:29
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jonpsy[m] >
finally! able to connect to Appveyor agent through my linux ;D
07:21
<
ABHINAVANAND[m] >
<OleksandrNikolsk "> <@_slack_mlpack_U01RJC8AB2M:ma"> I totally missed this. You can complete the work on your pr. After it gets merged I can merge with the master.
07:26
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OleksandrNikolsk >
<ABHINAVANAND[m] "I totally missed this. You can c"> The Backprop in my fix is ready.
08:00
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OleksandrNikolsk >
I would like to try to teach my computer to play Breakout in Atari by optimizing weights of convolutional network with cma es (not sure if it is a good idea, because cma es requires nĀ² space, where n is number of params. It did good on a one-hidden layer - percepron for Cartpole)
08:00
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OleksandrNikolsk >
So here's a question: what is the best way to define a 3d convolution kernel? Convolution layer just has width and height params
08:01
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OleksandrNikolsk >
(edited) ... convolution kernel? Convolution layer just has width ... => ... convolution kernel in mlp?
08:01
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OleksandrNikolsk >
Should the conv layer be extended?
08:01
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OleksandrNikolsk >
Currently Convolution layer seems to have only width ...
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09:06
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AakashkaushikGit >
Hey @zoq is the ann/util/gradient_update used in place of gradient_set_visitor ?
11:36
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11:38
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challenger13 >
Hello I am Neeraj. I am new to IRCs and mlpack and I would like to understand both :)
11:59
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RishabhGargGitte >
Hey @rcurtin , In the decision tree implementation, we have one `Train` method for both categorical and numerical dimensions. And the other one is only assuming all dimensions as numerical.
11:59
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RishabhGargGitte >
My question is why do we have a dedicated `Train` method for dataset containing all numerical attributes ?
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19:19
<
zoq >
wrong window :)
19:22
<
OleksandrNikolsk >
Hi zoq, I am testing the gym_api,
19:22
<
OleksandrNikolsk >
the step method requires a vec. So if I want to perform an action ,say i , do i just make a 1-element vector `[i]` and pass it?
19:30
<
zoq >
OleksandrNikolsk: matrix with size (1xn) yes.
19:31
<
OleksandrNikolsk >
so I can pass multiple actions in one turn (because of n)?
19:36
<
zoq >
Yes, e.g. to jump and move forward at the same time.
20:10
<
zoq >
OleksandrNikolsk: You have to link against boost as well.
20:18
<
OleksandrNikolsk >
zoq qreat,
20:18
<
OleksandrNikolsk >
```find_package(Boost 1.49 COMPONENTS system thread iostreams)
20:18
<
OleksandrNikolsk >
target_link_libraries(example ${Boost_LIBRARIES} ${ARMADILLO_LIBRARIES})```
20:18
<
OleksandrNikolsk >
this was the solution, thanks
20:18
<
OleksandrNikolsk >
(edited) zoq qreat,
20:18
<
OleksandrNikolsk >
```find_package(Boost ... => zoq great,
20:18
<
OleksandrNikolsk >
```find_package(Boost ...
21:06
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22:56
<
rcurtin[m] >
zoq: have you used RNNs for prediction with `single` set to `true`? I was trying to debug
https://github.com/mlpack/models/issues/50 , but I'm not sure if `RNN::Predict()` properly handles when `single` is true (and if it doesn't handle that case right, I'm not sure how it should handle it š)
22:58
<
zoq >
rcurtin[m]: Ohh, I missed the dicussion on #50/
22:59
<
zoq >
I used 'single' yes,I'll take a look into the issue.
23:18
<
ABHINAVANAND[m] >
I was looking at a test case in adaptive mean pooling,
23:20
<
ABHINAVANAND[m] >
I was able to reproduce this in pytorch
23:20
<
ABHINAVANAND[m] >
But I am not sure how to reproduce the result of `delta` , it it input.grad as in the notebook. Please confirm
23:26
<
ABHINAVANAND[m] >
(edited) ... , it it ... => ... , is it ...
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23:50
<
rcurtin[m] >
awesome, thanks zoq