This is a quick check of my understanding of the network architecture. Let's count the number of parameters in the model: * convolutional block: (17*9+1)*256 + 2*256 [ 17 = number of input channels 9 = size of the 3x3 convolution window 1 = bias (I am not sure this is needed if you are going to do batch normalization immediately after) 256 = number of output channels 2 = mean and standard deviation of the output of the batch normalization 256 = number of channels in the batch normalization ] * residual block: (256*9+1)*256 + 2*256 + (256*9+1)*256 + 2*256 * policy head: (256*1+1)*2 + 2*2 + (2*361+1)*362 * value head: (256*1+1)*1 + 2*1 + (1*361+1)*256 + (256+1)*1
Summing it all up, I get 22,837,864 parameters for the 20-block network and 46,461,544 parameters for the 40-block network. Does this seem correct? Álvaro. On Thu, Oct 19, 2017 at 6:17 AM, Petr Baudis <pa...@ucw.cz> wrote: > On Wed, Oct 18, 2017 at 04:29:47PM -0700, David Doshay wrote: > > I saw my first AlphaGo Zero joke today: > > > > After a few more months of self-play the games might look like this: > > > > AlphaGo Zero Black - move 1 > > AlphaGo Zero White - resigns > > ...which is exactly what my quick attempt to reproduce AlphaGo Zero > yesterday converged to overnight. ;-) But I'm afraid it's because of > a bug, not wisdom... > > Petr Baudis > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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