Of course whether these "neuro-playouts" are any better than the heavy playouts currently being used by strong programs is an empirical question. But I would love to see it answered...
On Tue, Dec 8, 2015 at 1:31 PM, David Ongaro <david.ong...@hamburg.de> wrote: > Did everyone forget the fact that stronger playouts don't necessarily lead > to an better evaluation function? (Yes, that what playouts essential are, a > dynamic evaluation function.) This is even under the assumption that we can > reach the same number of playouts per move. > > > On 08 Dec 2015, at 10:21, Álvaro Begué <alvaro.be...@gmail.com> wrote: > > I don't think the CPU-GPU communication is what's going to kill this idea. > The latency in actually computing the feed-forward pass of the CNN is going > to be in the order of 0.1 seconds (I am guessing here), which means > finishing the first playout will take many seconds. > > So perhaps it would be interesting to do something like this for > correspondence games, but not for regular games. > > > Álvaro. > > > > On Tue, Dec 8, 2015 at 12:03 PM, Petr Baudis <pa...@ucw.cz> wrote: > >> Hi! >> >> Well, for this to be practical the entire playout would have to be >> executed on the GPU, with no round-trips to the CPU. That's what my >> email was aimed at. >> >> On Tue, Dec 08, 2015 at 04:37:05PM +0000, Josef Moudrik wrote: >> > Regarding full CNN playouts, I think that problem is that a playout is a >> > long serial process, given 200-300 moves a game. You need to construct >> > planes and transfer them to GPU for each move and read result back (at >> > least with current CNN implementations afaik), so my guess would be that >> > such playout would take time in order of seconds. So there seems to be a >> > tradeoff, CNN playouts are (probably much) better (at "playing better >> > games") than e.g. distribution playouts, but whether this is worth the >> > implied (probably much) lower height of the MC tree is a question. >> > >> > Maybe if you had really a lot of GPUs and very high thinking time, this >> > could be the way. >> > >> > Josef >> > >> > On Tue, Dec 8, 2015 at 5:17 PM Petr Baudis <pa...@ucw.cz> wrote: >> > >> > > Hi! >> > > >> > > In case someone is looking for a starting point to actually >> implement >> > > Go rules etc. on GPU, you may find useful: >> > > >> > > >> > > >> https://www.mail-archive.com/computer-go@computer-go.org/msg12485.html >> > > >> > > I wonder if you can easily integrate caffe GPU kernels in another >> GPU >> > > kernel like this? But without training, reimplementing the NN could >> be >> > > pretty straightforward. >> > > >> > > On Tue, Dec 08, 2015 at 04:53:14PM +0100, Michael Markefka wrote: >> > > > Hello Detlef, >> > > > >> > > > I've got a question regarding CNN-based Go engines I couldn't find >> > > > anything about on this list. As I've been following your posts >> here, I >> > > > thought you might be the right person to ask. >> > > > >> > > > Have you ever tried using the CNN for complete playouts? I know that >> > > > CNNs have been tried for move prediction, immediate scoring and move >> > > > generation to be used in an MC evaluator, but couldn't find anything >> > > > about CNN-based playouts. >> > > > >> > > > It might only be feasible to play out the CNN's first choice move >> for >> > > > evaluation purposes, but considering how well the performance of >> batch >> > > > sizes scales, especially on GPU-based CNN applications, it might be >> > > > possible to setup something like 10 candidate moves, 10 reply >> > > > candidate moves and then have the CNN play out the first choice move >> > > > for those 100 board positions until the end and then sum up scores >> > > > again for move evaluation (and/or possibly apply some other tried >> and >> > > > tested methods like minimax). Given that the number of 10 moves is >> > > > supposed to be illustrative rather than representative, other >> > > > configurations of depth and width in position generation and >> > > > evaluation would be possible. >> > > > >> > > > It feels like CNN can provide a very focused, high-quality width in >> > > > move generation, but it might also be possible to apply that quality >> > > > to depth of evaluation. >> > > > >> > > > Any thoughts to share? >> > > > >> > > > >> > > > All the best >> > > > >> > > > Michael >> > > > >> > > > On Tue, Dec 8, 2015 at 4:13 PM, Detlef Schmicker <d...@physik.de> >> wrote: >> > > > > -----BEGIN PGP SIGNED MESSAGE----- >> > > > > Hash: SHA1 >> > > > > >> > > > > Hi, >> > > > > >> > > > > as somebody ask I will offer my actual CNN for testing. >> > > > > >> > > > > It has 54% prediction on KGS 6d+ data (which I thought would be >> state >> > > > > of the art when I started training, but it is not anymore:). >> > > > > >> > > > > it has: >> > > > > 1 >> > > > > 2 >> > > > > 3 >> > > > >> 4 libs playing color >> > > > > 1 >> > > > > 2 >> > > > > 3 >> > > > >> 4 libs opponent color >> > > > > Empty points >> > > > > last move >> > > > > second last move >> > > > > third last move >> > > > > forth last move >> > > > > >> > > > > input layers, and it is fully convolutional, so with just editing >> the >> > > > > golast19.prototxt file you can use it for 13x13 as well, as I did >> on >> > > > > last sunday. It was used in November tournament as well. >> > > > > >> > > > > You can find it >> > > > > http://physik.de/CNNlast.tar.gz >> > > > > >> > > > > >> > > > > >> > > > > If you try here some points I like to get discussion: >> > > > > >> > > > > - - it seems to me, that the playouts get much more important >> with such >> > > > > a strong move prediction. Often the move prediction seems better >> the >> > > > > playouts (I use 8000 at the moment against pachi 32000 with about >> 70% >> > > > > winrate on 19x19, but with an extremely focused progressive >> widening >> > > > > (a=400, a=20 was usual). >> > > > > >> > > > > - - live and death becomes worse. My interpretation is, that the >> strong >> > > > > CNN does not play moves, which obviously do not help to get a >> group >> > > > > life, but would help the playouts to recognize the group is dead. >> > > > > (http://physik.de/example.sgf top black group was with weaker >> move >> > > > > prediction read very dead, with good CNN it was 30% alive or so :( >> > > > > >> > > > > >> > > > > OK, hope you try it, as you know our engine oakfoam is open >> source :) >> > > > > We just merged all the CNN stuff into the main branch! >> > > > > https://bitbucket.org/francoisvn/oakfoam/wiki/Home >> > > > > http://oakfoam.com >> > > > > >> > > > > >> > > > > Do the very best with the CNN >> > > > > >> > > > > Detlef >> > > > > >> > > > > >> > > > > >> > > > > >> > > > > code: >> > > > > if (col==Go::BLACK) { >> > > > > for (int j=0;j<size;j++) >> > > > > for (int k=0;k<size;k++) >> > > > > { >> > > > > for (int l=0;l<caffe_test_net_input_dim;l++) >> > > > > data[l*size*size+size*j+k]=0; >> > > > > //fprintf(stderr,"%d %d %d\n",i,j,k); >> > > > > int pos=Go::Position::xy2pos(j,k,size); >> > > > > int libs=0; >> > > > > if (board->inGroup(pos)) >> > > > > libs=board->getGroup(pos)->numRealLibs()-1; >> > > > > if (libs>3) libs=3; >> > > > > if (board->getColor(pos)==Go::BLACK) >> > > > > { >> > > > > data[(0+libs)*size*size + size*j + >> k]=1.0; >> > > > > //data[size*size+size*j+k]=0.0; >> > > > > } >> > > > > else if (board->getColor(pos)==Go::WHITE) >> > > > > { >> > > > > //data[j*size+k]=0.0; >> > > > > data[(4+libs)*size*size + size*j + >> k]=1.0; >> > > > > } >> > > > > else if >> > > > > (board->getColor(Go::Position::xy2pos(j,k,size))==Go::EMPTY) >> > > > > { >> > > > > data[8*size*size + size*j + k]=1.0; >> > > > > } >> > > > > } >> > > > > } >> > > > > if (col==Go::WHITE) { >> > > > > for (int j=0;j<size;j++) >> > > > > for (int k=0;k<size;k++) >> > > > > {//fprintf(stderr,"%d %d %d\n",i,j,k); >> > > > > for (int l=0;l<caffe_test_net_input_dim;l++) >> > > > > data[l*size*size+size*j+k]=0; >> > > > > //fprintf(stderr,"%d %d %d\n",i,j,k); >> > > > > int pos=Go::Position::xy2pos(j,k,size); >> > > > > int libs=0; >> > > > > if (board->inGroup(pos)) >> > > > > libs=board->getGroup(pos)->numRealLibs()-1; >> > > > > if (libs>3) libs=3; >> > > > > if (board->getColor(pos)==Go::BLACK) >> > > > > { >> > > > > data[(4+libs)*size*size + size*j + >> k]=1.0; >> > > > > //data[size*size+size*j+k]=0.0; >> > > > > } >> > > > > else if (board->getColor(pos)==Go::WHITE) >> > > > > { >> > > > > //data[j*size+k]=0.0; >> > > > > data[(0+libs)*size*size + size*j + >> k]=1.0; >> > > > > } >> > > > > else if (board->getColor(pos)==Go::EMPTY) >> > > > > { >> > > > > data[8*size*size + size*j + k]=1.0; >> > > > > } >> > > > > } >> > > > > } >> > > > > if (caffe_test_net_input_dim > 9) { >> > > > > if (board->getLastMove().isNormal()) { >> > > > > int >> j=Go::Position::pos2x(board->getLastMove().getPosition(),size); >> > > > > int >> k=Go::Position::pos2y(board->getLastMove().getPosition(),size); >> > > > > data[9*size*size+size*j+k]=1.0; >> > > > > } >> > > > > if (board->getSecondLastMove().isNormal()) { >> > > > > int >> > > > > >> j=Go::Position::pos2x(board->getSecondLastMove().getPosition(),size); >> > > > > int >> > > > > >> k=Go::Position::pos2y(board->getSecondLastMove().getPosition(),size); >> > > > > data[10*size*size+size*j+k]=1.0; >> > > > > } >> > > > > if (board->getThirdLastMove().isNormal()) { >> > > > > int >> > > > > >> j=Go::Position::pos2x(board->getThirdLastMove().getPosition(),size); >> > > > > int >> > > > > >> k=Go::Position::pos2y(board->getThirdLastMove().getPosition(),size); >> > > > > data[11*size*size+size*j+k]=1.0; >> > > > > } >> > > > > if (board->getForthLastMove().isNormal()) { >> > > > > int >> > > > > >> j=Go::Position::pos2x(board->getForthLastMove().getPosition(),size); >> > > > > int >> > > > > >> k=Go::Position::pos2y(board->getForthLastMove().getPosition(),size); >> > > > > data[12*size*size+size*j+k]=1.0; >> > > > > } >> > > > > } >> > > > > >> > > > > -----BEGIN PGP SIGNATURE----- >> > > > > Version: GnuPG v2.0.22 (GNU/Linux) >> > > > > >> > > > > iQIcBAEBAgAGBQJWZvOlAAoJEInWdHg+Znf4t8cP/2a9fE7rVb3Hz9wvdMkvVkFS >> > > > > 4Y3AomVx8i56jexVyXuzKihfizVRM7x6lBiwjYBhj4Rm9UFWjj2ZvDzBGCm3Sy4I >> > > > > SpG8D01VnzVR6iC1YTu3ecv9Wo4pTjc7NL5pAxiZDB0V7OTRklfZAYsX4mWyHygn >> > > > > cr1pIb79/9QfBf/johmuutXJIwYfVG9ShR1+udbxs3aU3QDAbJJ4eTs8oj+NqFpg >> > > > > JolEEEg3wY693e77SqbUbjxR3kSsysoz9h1nKnR/ZjHByqlwNvSz9ho9eU0rKhaK >> > > > > GSQ22/c1VPIZhr24FYBbYNYweOzDtonLpuUFCPSnYVels3h/I/LlqV3MeDo6wuZ2 >> > > > > QCPp5+11o4JzvEt7A4zfJCtEOEH0W2/+IjRcIkAVOo65OV/pPsz2EjHehMU6PC6m >> > > > > vXA/kPx0jqUm1qSb0qCgMq5ZvSqfpcCY7JOlkEwkDBS1fty9sU0hqst3zXR0KGtn >> > > > > rFuoREmQYi/mkjZfS2Q4AHiZUDbDZUKzRegUA+gR/eKAmJsmWeTDEI9ZAXgxL0cB >> > > > > p1HGBNDEUKGk+ruq0gIe5vYygyBcJV0BbbBnweDjeZnlG8vLUAVoMF6V/q3gkZb1 >> > > > > P61rfE4d9dohfGBsZ+UWltRyWMj09ieR2G2zCDpIXyxEuoV6CTAlLzDuhmqFa2ma >> > > > > Fp3lK/uLhOucXwBtStdx >> > > > > =E47K >> > > > > -----END PGP SIGNATURE----- >> > > > > _______________________________________________ >> > > > > Computer-go mailing list >> > > > > Computer-go@computer-go.org >> > > > > http://computer-go.org/mailman/listinfo/computer-go >> > > > _______________________________________________ >> > > > Computer-go mailing list >> > > > Computer-go@computer-go.org >> > > > http://computer-go.org/mailman/listinfo/computer-go >> > > >> > > -- >> > > Petr Baudis >> > > If you have good ideas, good data and fast computers, >> > > you can do almost anything. -- Geoffrey Hinton >> > > _______________________________________________ >> > > Computer-go mailing list >> > > Computer-go@computer-go.org >> > > http://computer-go.org/mailman/listinfo/computer-go >> >> > _______________________________________________ >> > Computer-go mailing list >> > Computer-go@computer-go.org >> > http://computer-go.org/mailman/listinfo/computer-go >> >> >> -- >> Petr Baudis >> If you have good ideas, good data and fast computers, >> you can do almost anything. -- Geoffrey Hinton >> _______________________________________________ >> Computer-go mailing list >> Computer-go@computer-go.org >> http://computer-go.org/mailman/listinfo/computer-go >> > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go > > > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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