anon325671: hello
devlogs: .
Magus: incoming next : CSB with tactical nuke
BIPIN_THE_KING: hello
Alex_Prog: Hi
AntiSquid: how do i remove timelimit locally from SDK ? forgot
AntiSquid: nvm found something
AntiSquid: nope that wasn't it, damn it ... :/
binjn: hi everyone
binjn: does anyone know a pythonista community
FriendlyKh: let me see
FriendlyKh: Discord is an option
binjn: oh thx
KatMan911: is it just me, or CG just slowed down HARD?
k-space: basically not working at all for me
69razer69: its working fine for me
k-space: seems back now
Hunter64TheOne: fr
Hunter64TheOne: #fr
KatMan911: quick question - if I got out of the chat room for the current COC, how would I get back in to talk to other guys?
Wontonimo: know their user names
Wontonimo: and pm them
KatMan911: Ah, yes.
KatMan911: any way to get the COC room name, though? The one that you automatically get into when COC starts?
Wontonimo: if you followed them, then they will show up in your following list in your profile
Wontonimo: it has a name and if you remembered what the room name was you can use the # to get there "#roomname"
Wontonimo: in the chat. Actually, you can use that to make arbitrary rooms like #littlemushroom
Wontonimo: or #fr
KatMan911: so everyone'd see what I'm saying, without any need for PMs
KatMan911: yeah, that's the thing - they're all "COC<insert mchuge number here>"
KatMan911: oki
Wontonimo: type /help here to see some other options
KatMan911: thanks
Wontonimo: :thumbsup:
Hunter64TheOne: #fr
Hunter64TheOne: il y a des fr
Hunter64TheOne: ?
Hunter64TheOne: #fr
Hunter64TheOne: 000000000000000000 0000000 000 0000000000
Hunter64TheOne: pourquois on m'exclue?
Astrobytes: English in World please, talk French in #fr, don't spam 0's
Hunter64TheOne: dacodac
Hunter64TheOne: yes
Hunter64TheOne: yes
Hunter64TheOne: oui
Hunter64TheOne: yes
Astrobytes: Do you want a ban?
Hunter64TheOne: no
Hunter64TheOne: mais pourquois
StepBack13: lag in clash? or just me?
Astrobytes: Someone else complained on discord so I'm guessing it's running a little slow.
Wontonimo: when CoC is lagging, play a multi like https://www.codingame.com/multiplayer/bot-programming/tic-tac-toe/discuss
Wontonimo: when CoC isn't lagging, play a puzzle like https://www.codingame.com/training/easy
Astrobytes: Good shout :)
sBlip: hello world
KiwiTae: Astrobytes o/
Astrobytes: hey KiwiTae :)
AntiSquid: someone can talk in chuck norris encoding :O
N413: wow
N413: so cool
linjoehan: AntiSquid: yes
KiwiTae: AntiSquid yes in #chucknorris room
Westicles: ugh. CN is impossible if you suck at both bash and perl
Lucky30_: anyone know if it is possible to build a nodejs api using a script in package.json
Lucky30_: if you know about it, please message me in private so that i can see your reply even after i log out
nthd3gr33: i have been rank 1 in wood 1 league in coders strike back for a while now
nthd3gr33: any ideas on why i'm not getting promoted?
Counterbalance: battles: 96%, nthd3gr33
nthd3gr33: what does that mean?
Counterbalance: that it wasn't done yet.. but now it is
Counterbalance: so you should get a promotion soon
nthd3gr33: Oh, I just got promoted
nthd3gr33: thanks
Astrobytes: congratulations
nthd3gr33: collision time!
Wontonimo: congrats nthd3gr33
Wontonimo: hey nthd3gr33, anyone tell you about the -3v heuristic for Coders Strikes Back?
Zenoscave: How long has dbd_r been 1st?
jacek: dbdr? dunno
Zenoscave: dbdr when did ya get the lead on euler?
Westicles: ah good, the gang's all here so we can talk about CN Bash
whatevericando4you: Failure
Found: 2End of line (\n)
Expected: Nothing
Zenoscave: CN Bash?
Westicles: chuck norris
Zenoscave: did they change validators?
Westicles: nah, just wandering if you really did bash or if it is perl or ruby wrapped
Zenoscave: perl
Zenoscave: well some bash
Westicles: yeah, that's what I thought. I'm trying to do it all in bash but this xxd stuff is too messy
Zenoscave: lol I have a full bash one let me see what it's length is
jacek: the suspense is killing me
AntiSquid: he lost count :P
Westicles: the answer is you need to learn perl, and I have no interest in doing that
Wontonimo: i knew perl. i used to teach it.
Wontonimo: that was a couple decades ago
Wontonimo: so it is safe to say i no longer know perl
Astrobytes: perl5 is perl5
Zenoscave: 92
Astrobytes: (as much as I can tell)
Astrobytes: pewpew
Zenoscave: pewpewpew
Wontonimo: Programmers Extraction and Reporting Language ... or something like that
Astrobytes: Practical Extraction and Reporting Language
Zenoscave: Eight Megabytes And Constantly Swapping
Astrobytes: By Larry Wall
Wontonimo: yeah, that sounds right
Astrobytes: First scripting language I became proficient in, circa 2000-2001
Zenoscave: a.k.a. Escape-Meta-Alt-Control-Shift. the hot-key needed to quit after it thrashes
Astrobytes: lol
Wontonimo: first one i learnt around 97
Zenoscave: 2008 for me Started with VB6
Astrobytes: scripting though
Zenoscave: I think it was 6 might've been a different one
Zenoscave: Astro hows your chuck
Astrobytes: VB6 was like about a decade before?
Astrobytes: My what?
Zenoscave: Limited resources
Zenoscave: chuck norris golf
Astrobytes: Hmm, lemme look
Husoski: Actually, Perl is just Perl. The acronyms came later. Originally intended to be "Pearl", but there was another Pearl language.
Zenoscave: interesting
Astrobytes: best is 103 ruby, must've spent a lot of time on that one
Astrobytes: and isn't it just 'perl'
Husoski: Perl 6 is now called Raku. Wikipedia has a history section in the Perl article, and another on the name.
Astrobytes: Yeah I know about Raku
Zenoscave: 103!? Get working astro
Astrobytes: Golfing isn't my favourite thing, neither is ruby :P
Husoski: Just puttin' in my $0.02...what's that in Euros?
Zenoscave: I'm similar. golfing xor ruby is horrible.
Zenoscave: either golf in ruby or don't golf and don't use ruby
Astrobytes: No idea Husuki :D
Astrobytes: Husuki? Husoski
Zenoscave: Bueller? Bueller?
AntiSquid: it values less in Euros
AntiSquid: and probably would be rounded down to 0.01
Westicles: around 10 bob, fits right in your nose
Zenoscave: 10 bobs?
Zenoscave: Is this a currency?
Westicles: according to the beatles, yes
Zenoscave: I don't know how to process this. that's enough CG chat for a day
Astrobytes: 10 bob was a 10 shilling note? I think. back in the day in the UK
Zenoscave: Ok that helps I'll stay now
Zenoscave: got my bash down to 90
Astrobytes: bashing your bash
Zenoscave: mhm
Zenoscave: til it bashes no more
Westicles: you already have a 72 lol
Westicles: or 76 actually
Zenoscave: it's not really bash though lol
Marchete: PoZero
Marchete: https://twitter.com/robinphysics
Marchete: https://twitter.com/robinphysics/status/1283475087740612608
Marchete: sorry that link
Marchete: I don't understand anything
Wontonimo: from the article that the link references:
Wontonimo: "With this insight, we propose a variant
of AlphaZero which uses the exact solution to
this policy optimization problem, and show experimentally that it reliably outperforms the original
algorithm in multiple domains."
Astrobytes: interesting
Wontonimo: basically, they are saying that MCTS is an approximate policy and they are proposing the exact policy optimization
Marchete: and this is when I got lost
Marchete: I don't understand the notation
Marchete: like at all
Marchete: very little info about it, considering they claim a much better performance than Alphazero and muzero
Marchete: https://slideslive.com/38928110/mcts-as-regularized-policy-optimization?ref=speaker-24115-latest
Marchete: pasted for later use
Marchete: I hope https://cg.spdns.eu/wiki/Main_Page is working :D
Marchete: https://arxiv.org/pdf/2007.12509.pdf
Wontonimo: I like the background ...
Wontonimo: ". Background
Consider a standard RL setting tied to a Markov decision
process (MDP) with state space X and action space A"
Wontonimo: oh yes, i can picture it lol
Marchete: in the video they give some samples about alphazero, and nothing about the new algo...
Marchete: I can't understand those hyper mathematical papers, a pity
Marchete: btw wontonimo
Marchete: you know a lot about NN
Marchete: what's better/suitable on small NN? Batch normalization or L2 regularization?
Marchete: ....or both?
Marchete: or none
AntiSquid: 10+ epochs of testing :P
Wontonimo: i really like batch norm so long as you have a large batch.
Marchete: define large
Wontonimo: 64 would be the lower limit i'd think.
Wontonimo: but depending on the implementation, it should blend from batch to batch
Wontonimo: tensorflow batch norm?
Wontonimo: using keras?
Marchete: keras
Wontonimo: yeah, so your batch size i don't think matters
Wontonimo: sorry for the red herring
Marchete: I've tried x=tf.keras.layers.BatchNormalization(epsilon=0.00001,scale=True)(x)
Marchete: nothing different
Wontonimo: yeah, batch norm is just really nice at regularization. try adding it liberally, like between every 3 layers
Marchete: maybe batch was small
Marchete: every 3?
Wontonimo: or 2
Marchete: I added in all :D
Wontonimo: haha ... sure
Marchete: no I mean, where should I?
Marchete: right now I was testing input->Dense1->Dense2-><split>->Policy &value
Wontonimo: "Batch normalization applies a transformation that maintains the mean output close to 0 and the output standard deviation close to 1." and you can specify the axis to use
Marchete: I added it on Dense1 and Dense2
Wontonimo: which means, it will output values close to 0 with a STD ~ 1
Marchete: but my weights went a bit higher
Wontonimo: and if the receiving network requires values in the range of -.01 to +0.01 or -10.0 or +10.0, they will struggle
Marchete: maybe I need a bigger batch size
Marchete: I thought it was based on samples, and it's on batch size
Marchete: 128/256?
Wontonimo: wait ... we got 2 threads of conversation going. i'm going back to this
Wontonimo: input->Dense1->Dense2-><split>->Policy &value
Wontonimo: with where to put regularization
Marchete: yes
Marchete: I->D1->Batch->Relu->D2->B->Relu.....
Wontonimo: input->batchNorm->D1->D2->[P,V]
Marchete: hmm
Marchete: before?
Marchete: inputs are one hot
Wontonimo: that's pretty classic, it's like white balancing a picture before processing
Wontonimo: oh, 1 hot!
Wontonimo: nvm
Wontonimo: thanks for clarifying
Wontonimo: if input is 1 hot then dense1 is effectively an embedding lookup
Wontonimo: input drives the embeddings the will be retrieved from D1
Wontonimo: you don't need to batchnorm that
Marchete: ahh
Marchete: good
Wontonimo: let's say you did ... what it would do would be to make all the embeddings have the same distribution
Wontonimo: 0 +- 1 for all values
Marchete: I have no idea, I just saw "batchnorm is good for learning speed"
Wontonimo: in the D1 (embedding) layer
Marchete: the same for L2 regularization
Marchete: but I have no idea when to use them
Wontonimo: input is just 1 1-hot, or a couple 1-hots ?
Marchete: 14x one hots
Wontonimo: how bit is the 1hot
Wontonimo: *big
Marchete: 14x28 more or less
Marchete: <400
Wontonimo: 14 1hots, each 1hot having 28 values. okay.
Wontonimo: then flatten all those values to go to D1
Marchete: they are already flat
Wontonimo: D1 is then a linear addition of 14 embeddings with an activation function after the addition.
Marchete: yes, and I optimized it that way
Marchete: bias + 14*weights from each activation
Marchete: so is faster
Wontonimo: thanks for sharing.
Wontonimo: hmm
Wontonimo: what would batch norm between I and D1 do ... let me think
Marchete: I see it after D1, because it's where you need more normalization
Wontonimo: effectively it would transform your input into more like a probability output, because one of the
Wontonimo: outputs that is very infrequently 1 will be +3 with it fires, and -0.1 when not firing
Wontonimo: where as an output that is frequent may only reach +.8 when firing and -0.4 when not firing
Wontonimo: and so placing batchnorm over I will convert it to a signal amplifier of how frequent that option is seen
Wontonimo: just an idea. i'm not suggesting using it , but that is my intuition
Wontonimo: adding it to after D1 will help D2 learn faster
Marchete: ok
atomprods: hello
Wontonimo: the rational is that having batchnorm after a layer makes that layer always conform to act within a range, and later layers don't have to readjust to a changing range
Marchete: in fact after batchnorm I had a clipped relu
Wontonimo: and since D1 is taking in more than just 1 1hot, it is more than just an embedding lookup and can benefit from batchnorm
Marchete: 0..1 range only
Marchete: maybe it's not a good fit for batchnorm
Wontonimo: inside your network?
Marchete: I need to make more tests
Wontonimo: i can see that for final output possibly
Marchete: clipped relu is for some quantization methods
atomprods: I said hello.
Wontonimo: hello
Wontonimo: all values (and connections) outside the clip are effective treated as if block_backprop was applied to them
Wontonimo: and so there is no learning outside the range of 0-1
Wontonimo: i've seen ReLU being used by concating it with the negative of the previous layout pushed through ReLU also. It seems like
Wontonimo: youd have the same info, but it is nicely divided between positive values and negative values
Marchete: https://github.com/glinscott/nnue-pytorch/blob/master/docs/nnue.md#clippedrelu
Wontonimo: and learning can happen in all ranges
Wontonimo: ah
Wontonimo: i don't see a need for batchnorm with something like Clipped ReLU.
Wontonimo: i really don't know how Clipped ReLU would preform !!
Marchete: no
Marchete: I mean
Marchete: I was testing different things
Marchete: I thought regularization or batchnorm could help me to get weights in range
Marchete: like in -2.0 to 2.0 always
Marchete: also because it improves learning and avoid overfitting
Marchete: I need to recheck something else
Marchete: now I'm seeing P1 as always lose
Marchete: when on previous tests it seems to have some advantage
Marchete: thanks for your help wontonimo
Wontonimo: hey ...
Wontonimo: to be clear, my usual method to these things is to talk about the network like I did
Wontonimo: then come up with some theories, and then test them
Wontonimo: and then a lot of times I wrong
Wontonimo: when then allows me to learn lol
Wontonimo: if you have the CPU, try ReLU then leakyReLU,
Wontonimo: clipped ReLU
Wontonimo: and honestly , i don't think i helped yet ;)
Wontonimo: thanks for chatting
doomento: I'm clueless
Astrobytes: I'm Astrobytes.
doomento: I don't know what to do on "The Descent". . . or really anything.
Astrobytes: May I recommend starting here:
https://www.codingame.com/playgrounds/55547/how-to-get-started-on-codingame
Astrobytes: Should clarify a few things
doomento: Ok I will start reading it now.:nerd: thanks
BOTAlex: I unexpectedly created an ai that ranked up from wood 2 to gold 3
(Coders strike back)
FunkyFrenchman_e730: Anyone got like some youtube videos
Wontonimo: cool BOTAlex
Wontonimo: what was the algo?
Wontonimo: oh, it looks like you are using the -3v algo
BOTAlex: i have no idea which or what it is named. I just made the thing stop drifting that much.
anon325671: hello
