Welll, David is making a product. Making a product is 'trooper' solution unless you are making very specific product to a very narrow target group, willing to pay thousands for single license
Petri 2016-02-04 23:50 GMT+02:00 uurtamo . <uurt...@gmail.com>: > David, > > You're a trooper for doing this in windows. :) > > The OS overhead is generally lighter if you use unix; even the most modern > windows versions have a few layers of slowdown. Unix (for better or worse) > will give you closer, easier access to the hardware, and closer, easier > access to halting your machine if you are deep in the guts. ;) > > s. > > > On Tue, Feb 2, 2016 at 10:25 AM, David Fotland <fotl...@smart-games.com> > wrote: > >> Detlef, Hiroshi, Hideki, and others, >> >> I have caffelib integrated with Many Faces so I can evaluate a DNN. >> Thank you very much Detlef for sample code to set up the input layer. >> Building caffe on windows is painful. If anyone else is doing it and gets >> stuck I might be able to help. >> >> What hardware are you using to train networks? I don’t have a >> cuda-capable GPU yet, so I'm going to buy a new box. I'd like some >> advice. Caffe is not well supported on Windows, so I plan to use a Linux >> box for training, but continue to use Windows for testing and development. >> For competitions I could use either windows or linux. >> >> Thanks in advance, >> >> David >> >> > -----Original Message----- >> > From: Computer-go [mailto:computer-go-boun...@computer-go.org] On >> Behalf >> > Of Hiroshi Yamashita >> > Sent: Monday, February 01, 2016 11:26 PM >> > To: computer-go@computer-go.org >> > Subject: *****SPAM***** Re: [Computer-go] DCNN can solve semeai? >> > >> > Hi Detlef, >> > >> > My study heavily depends on your information. Especially Oakfoam code, >> > lenet.prototxt and generate_sample_data_leveldb.py was helpful. Thanks! >> > >> > > Quite interesting that you do not reach the prediction rate 57% from >> > > the facebook paper by far too! I have the same experience with the >> > >> > I'm trying 12 layers 256 filters, but it is around 49.8%. >> > I think 57% is maybe from KGS games. >> > >> > > Did you strip the games before 1800AD, as mentioned in the FB paper? I >> > > did not do it and was thinking my training is not ok, but as you have >> > > the same result probably this is the only difference?! >> > >> > I also did not use before 1800AD. And don't use hadicap games. >> > Training positions are 15693570 from 76000 games. >> > Test positions are 445693 from 2156 games. >> > All games are shuffled in advance. Each position is randomly rotated. >> > And memorizing 24000 positions, then shuffle and store to LebelDB. >> > At first I did not shuffle games. Then accuracy is down each 61000 >> > iteration (one epoch, 256 mini-batch). >> > http://www.yss-aya.com/20160108.png >> > It means DCNN understands easily the difference 1800AD games and 2015AD >> > games. I was surprised DCNN's ability. And maybe 1800AD games are also >> > not good for training? >> > >> > Regards, >> > Hiroshi Yamashita >> > >> > ----- Original Message ----- >> > From: "Detlef Schmicker" <d...@physik.de> >> > To: <computer-go@computer-go.org> >> > Sent: Tuesday, February 02, 2016 3:15 PM >> > Subject: Re: [Computer-go] DCNN can solve semeai? >> > >> > > Thanks a lot for sharing this. >> > > >> > > Quite interesting that you do not reach the prediction rate 57% from >> > > the facebook paper by far too! I have the same experience with the >> > > GoGoD database. My numbers are nearly the same as yours 49% :) my net >> > > is quite simelar, but I use 7,5,5,3,3,.... with 12 layers in total. >> > > >> > > Did you strip the games before 1800AD, as mentioned in the FB paper? I >> > > did not do it and was thinking my training is not ok, but as you have >> > > the same result probably this is the only difference?! >> > > >> > > Best regards, >> > > >> > > Detlef >> > >> > _______________________________________________ >> > 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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