Few changes to make CNNs work on Octave.

CNN/cnnbp.m

@@ -41,7 +41,12 @@
         if strcmp(net.layers{l}.type, 'c')
             for j = 1 : numel(net.layers{l}.a)
                 for i = 1 : numel(net.layers{l - 1}.a)
-                    net.layers{l}.dk{i}{j} = custom_convn(flipall(net.layers{l - 1}.a{i}), net.layers{l}.d{j}, 'valid') / size(net.layers{l}.d{j}, 3);
+                    %ugly if, until convn() is fixed in Octave.
+					if(isOctave())
+                        net.layers{l}.dk{i}{j} = convn_valid(flipall(net.layers{l - 1}.a{i}), net.layers{l}.d{j}) / size(net.layers{l}.d{j}, 3);
+				    else
+					    net.layers{l}.dk{i}{j} = convn(flipall(net.layers{l - 1}.a{i}), net.layers{l}.d{j}, 'valid') / size(net.layers{l}.d{j}, 3);
+                    end				
                 end
                 net.layers{l}.db{j} = sum(net.layers{l}.d{j}(:)) / size(net.layers{l}.d{j}, 3);
             end

CNN/cnntrain.m

@@ -1,29 +1,27 @@
-
 function net = cnntrain(net, x, y, opts)
     m = size(x, 3);
     numbatches = m / opts.batchsize;
     if rem(numbatches, 1) ~= 0
         error('numbatches not integer');
     end
-
     net.rL = [];
     for i = 1 : opts.numepochs
         disp(['epoch ' num2str(i) '/' num2str(opts.numepochs)]);
         tic;
         kk = randperm(m);
-        %how many processes?
-        numWorkers = 4
-		pids = 0:numWorkers-1;
-		starts = pids * numbatches / numWorkers
-
-		%process starts
-		turn = 0;
+        for l = 1 : numbatches
+            batch_x = x(:, :, kk((l - 1) * opts.batchsize + 1 : l * opts.batchsize));
+            batch_y = y(:,    kk((l - 1) * opts.batchsize + 1 : l * opts.batchsize));
 
-        pararrayfun(numWorkers,
-                    @(starts, pids)process_batch(x, y, kk, net, turn, starts, (numbatches/numWorkers),  pids, numWorkers, opts),
-                    starts,
-					pids,
-					"ErrorHandler" , @eh);
+            net = cnnff(net, batch_x);
+            net = cnnbp(net, batch_y);
+            net = cnnapplygrads(net, opts);
+            if isempty(net.rL)
+                net.rL(1) = net.L;
+            end
+            net.rL(end + 1) = 0.99 * net.rL(end) + 0.01 * net.L;
+        end
         toc;
     end
+
 end

CNN/convn_valid.m

@@ -2,22 +2,10 @@
 %equivalent to convn(A,B, 'valid')
 
 function result = convn_valid(A, B)
-
     m = size(A, 1) - size(B, 1) + 1;
-    numWorkers = 2;
-
-    function retcode = eh(error)
-        a = error
-        retcode = zeros(25, 1);	
+    result = zeros(m, m);
+    B = flipdim(B,3);
+    for j=1:size(A, 3)  
+	 result += conv2(A(:,:,j),B(:,:,j), 'valid');
     end
-
-	%each worker will write its output to specific part of the output
-	chunkSize = size(A,3)/numWorkers;
-	result = pararrayfun(numWorkers,  @(i)convadd(A, B, m, i, chunkSize), 0:numWorkers-1, "ErrorHandler" , @eh);
-
-    for j=m:numWorkers*m:m  
-	    result(:,1:m) += result(:,j+1:j+m);
-	end
-
-	result = result(1:m,1:m);
 end