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dcd2bd2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | function res = vl_ffdnet_concise(net, x)
global sigmas;
n = numel(net.layers);
res = struct('x', cell(1,n+1));
res(1).x = x ;
cudnn = {'CuDNN'} ;
%cudnn = {'NoCuDNN'} ;
for i=1:n
l = net.layers{i} ;
switch l.type
case 'conv'
res(i+1).x = vl_nnconv(res(i).x, l.weights{1}, l.weights{2}, ...
'pad', l.pad, ...
'stride', l.stride, ...
'dilate', l.dilate, ...
l.opts{:}, ...
cudnn{:}) ;
case 'concat'
if size(sigmas,1)~=size(res(i).x,1)
sigmaMap = bsxfun(@times,ones(size(res(i).x,1),size(res(i).x,2),1,size(res(i).x,4),'single'),permute(sigmas,[3 4 1 2]));
res(i+1).x = cat(3,res(i).x,sigmaMap);
else
res(i+1).x = cat(3,res(i).x,sigmaMap);
end
case 'SubP'
res(i+1).x = vl_nnSubP(res(i).x, [],'scale',l.scale);
case 'relu'
res(i+1).x = max(res(i).x,0) ;
end
res(i).x = [] ;
end
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