fixed biases not getting updated for CNNs. Thanks [email protected]. Performance upgrades by lots of ifs in nnapplygrads.

Author: rasmusbergpalm

CNN/cnnapplygrads.m

@@ -5,8 +5,8 @@
                 for ii = 1 : numel(net.layers{l - 1}.a)
                     net.layers{l}.k{ii}{j} = net.layers{l}.k{ii}{j} - opts.alpha * net.layers{l}.dk{ii}{j};
                 end
+                net.layers{l}.b{j} = net.layers{l}.b{j} - opts.alpha * net.layers{l}.db{j};
             end
-            net.layers{l}.b{j} = net.layers{l}.b{j} - opts.alpha * net.layers{l}.db{j};
         end
     end
 

DBN/dbnunfoldtonn.m

@@ -2,8 +2,12 @@
 %DBNUNFOLDTONN Unfolds a DBN to a NN
 %   dbnunfoldtonn(dbn, outputsize ) returns the unfolded dbn with a final
 %   layer of size outputsize added.
-
-    nn = nnsetup([dbn.sizes outputsize]);
+    if(exist('outputsize','var'))
+        size = [dbn.sizes outputsize];
+    else
+        size = [dbn.sizes];
+    end
+    nn = nnsetup(size);
     for i = 1 : numel(dbn.rbm)
         nn.W{i} = dbn.rbm{i}.W;
         nn.b{i} = dbn.rbm{i}.c;

NN/nnapplygrads.m

@@ -4,9 +4,23 @@
 % weights and biases
 
     for i = 1 : (nn.n - 1)
-        nn.vW{i} = nn.momentum*nn.vW{i} + nn.learningRate * (nn.dW{i} + nn.weightPenaltyL2 * nn.W{i});
-        nn.vb{i} = nn.momentum*nn.vb{i} + nn.learningRate * nn.db{i};
-        nn.W{i} = nn.W{i} - nn.vW{i};
-        nn.b{i} = nn.b{i} - nn.vb{i}; 
+        if(nn.weightPenaltyL2>0)
+            dW = nn.dW{i} + nn.weightPenaltyL2 * nn.W{i};
+        else
+            dW = nn.dW{i};
+        end
+        
+        dW = nn.learningRate * dW;
+        db = nn.learningRate * nn.db{i};
+        
+        if(nn.momentum>0)
+            nn.vW{i} = nn.momentum*nn.vW{i} + dW;
+            nn.vb{i} = nn.momentum*nn.vb{i} + db;
+            dW = nn.vW{i};
+            db = nn.vb{i};
+        end
+            
+        nn.W{i} = nn.W{i} - dW;
+        nn.b{i} = nn.b{i} - db; 
     end
 end

util/im2patches.m

@@ -5,8 +5,9 @@
     patches = [];
     for i=1:m:size(im,1)
         for u=1:n:size(im,2)
-             patch = im(u:u+m-1,i:i+n-1);
+             patch = im(i:i+n-1,u:u+m-1);
              patches = [patches patch(:)];
         end
     end
+    patches = patches';
 end

util/visualize.m

@@ -1,10 +1,10 @@
-function r=visualize(X, cn, s1, s2)
+function r=visualize(X, mm, s1, s2)
 %FROM RBMLIB http://code.google.com/p/matrbm/
 %Visualize weights X. If the function is called as a void method,
 %it does the plotting. But if the function is assigned to a variable 
 %outside of this code, the formed image is returned instead.
-if ~exist('cn','var')
-    cn = 0;
+if ~exist('mm','var')
+    mm = [min(X(:)) max(X(:))];
 end
 if ~exist('s1','var')
     s1 = 0;
@@ -21,16 +21,11 @@
     end
     %its a square, so data is probably an image
     num=ceil(sqrt(N));
-    a=zeros(num*s2+num+1,num*s1+num+1)-1;
+    a=mm(2)*ones(num*s2+num-1,num*s1+num-1);
     x=0;
     y=0;
     for i=1:N
         im = reshape(X(:,i),s1,s2)';
-        if(cn==1)
-            im = im-min(im(:));
-            im = im./max(im(:));
-            im = im*2-1;
-        end
         a(x*s2+1+x : x*s2+s2+x, y*s1+1+y : y*s1+s1+y)=im;
         x=x+1;
         if(x>=num)
@@ -48,5 +43,5 @@
 if nargout==1
     r=a;
 else
-    imshow(a, [-1 1]);
+    imshow(a, [mm(1) mm(2)]);
 end