<zoq[m]>
Hello Naman Jain in case you haven't seen it already https://www.mlpack.org/community.html has a getting involved section, that should get you started.
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<shrit[m]>
heisenbuug (Gopi M Tatiraju): Let us have a meeting today
<shrit[m]>
I did not have time yesterday, I was too busy
<shrit[m]>
Let me know if this works for you
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<zoq[m]>
<jonpsy[m]> "like, making it a column and set" <- Maybe I don't get what you are trying to do, I thought you have some vector and want to bring it into the format you mentioned.
<shrit[m]>
rcurtin: I was thining instead of inlining functions inside the dists/ directory, we can convert the class to template classes that takes a MatType and a VecType? What do you think?
<shrit[m]>
* rcurtin: I was thining instead of inlining functions inside the dists/ directory, we can convert the class to template class that takes a MatType and a VecType? What do you think?
<rcurtin[m]>
yeah, absolutely, that seems totally reasonable to me 👍️
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<jonpsy[m]>
> Maybe I don't get what you are trying to do, I thought you have some vector and want to bring it into the format you mentioned.
<zoq[m]>
Looks like there are three instances from the first row and 2 for the second one?
<zoq[m]>
* I see, I don't think we have a direct function to do that, maybe a combination of `repmat` and a for loop or only a for loop could work just fine?
<jonpsy[m]>
oh dont mind that
<jonpsy[m]>
<zoq[m]> "Looks like there are three insta" <- dont mind the count hhe, was jst lazy typin the last one
<zoq[m]>
I see, but still there is no armadillo function that would format it right away.
<jonpsy[m]>
nw
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<jonpsy[m]>
i've a question on the ```Forward``` thing
<jonpsy[m]>
based on our last disucssion, how do we calculate Loss?
<jonpsy[m]>
because we do ```target_Q - Q``` right/
<jonpsy[m]>
* because we do `Q - gamma * targetQ `
<zoq[m]>
Correct, since we use `Forward` we you need to calculate the loss yourself. Since the output layer is skipped.
<jonpsy[m]>
not suer what's hapening in the code ..... hehe
<zoq[m]>
I mean the function I just referenced, performs a forward step, gets the loss, with the given target and performs the backward step using the calculated loss.
<zoq[m]>
on the learning network
<jonpsy[m]>
ah!!!
<jonpsy[m]>
wow, okay
<jonpsy[m]>
very roundabout way, but i geti t
<jonpsy[m]>
* very roundabout way, but i get it.
<jonpsy[m]>
<zoq[m]> "So you could save the `Q` before" <- so, he's putting ```gamma*targetQ``` in ```Q``` right? but its only put for the selected action. The pass with backward would automatically find the loss and get gradients, perfect!
<ABHINAVANAND[m]>
zoq If the PR is failing due to gradient explosion then it should happen in Ctest, but the PR is failing in the buidl itself.
<ABHINAVANAND[m]>
Not sure what is happening
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<zoq[m]>
Do you have a link?
<heisenbuugGopiMT>
Sorry @shrit:matrix.org I went somewhere today, didn't saw your message
<heisenbuugGopiMT>
Can we have it tomorrow if you are free
<heisenbuugGopiMT>
Also I started making the project report, I will send it to you soon
<jonpsy[m]>
zoq: ping me when you're free
<zoq[m]>
jonpsy: ping
<jonpsy[m]>
pong
<jonpsy[m]>
can you check the diary once?
<jonpsy[m]>
the very latest one
<zoq[m]>
"How does mlpack handle this?" this one?
<jonpsy[m]>
yeah, i think you understood what i was saying
<zoq[m]>
yep
<jonpsy[m]>
okay, now im going to explain the dilemma with EQL
<jonpsy[m]>
in the doc
<jonpsy[m]>
zoq: hey, sorry i need one small detail in our current Backward()
<rcurtin[m]>
I know it may reduce the humor in the codebase but one of my biggest hopes about making mlpack header-only is that we can remove that file 😃
<rcurtin[m]>
There was once some code inside of mlpack where we did `#define private public` to test some internal functionality. I suppose it *might* still be there 😱
<shrit[m]>
do you remember where it was?
<shrit[m]>
I just open this one https://github.com/mlpack/mlpack/pull/3037/files, I thought it might take me an hour to convert all the dists/ dir, but I ended up several hours for only one file 😂