Merge pull request rasmusbergpalm#66 from albertoandreottiATgmail/convnfix

convnfix

Author: rasmusbergpalm

.travis.yml

@@ -1,6 +1,8 @@
 before_script:
-  - sudo apt-get install octave
-
+  - sudo apt-add-repository ppa:octave/stable --yes
+  - sudo apt-get update -y
+  - sudo apt-get install octave -y
+  - sudo apt-get install liboctave-dev -y
 script:
   - sh -c "octave tests/runalltests.m"
 

CNN/cnnbp.m

@@ -1,7 +1,7 @@
 function net = cnnbp(net, y)
     n = numel(net.layers);
 
-    %  error
+    %   error
     net.e = net.o - y;
     %  loss function
     net.L = 1/2* sum(net.e(:) .^ 2) / size(net.e, 2);
@@ -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} = 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/cnnnumgradcheck.m

@@ -11,8 +11,6 @@ function cnnnumgradcheck(net, x, y)
         d = (net_p.L - net_m.L) / (2 * epsilon);
         e = abs(d - net.dffb(j));
         if e > er
-            e
-            d / net.dffb(j)
             error('numerical gradient checking failed');
         end
     end
@@ -27,8 +25,6 @@ function cnnnumgradcheck(net, x, y)
             d = (net_p.L - net_m.L) / (2 * epsilon);
             e = abs(d - net.dffW(i, u));
             if e > er
-                e
-                d / net.ffW(i, u)
                 error('numerical gradient checking failed');
             end
         end
@@ -45,8 +41,6 @@ function cnnnumgradcheck(net, x, y)
                 d = (net_p.L - net_m.L) / (2 * epsilon);
                 e = abs(d - net.layers{l}.db{j});
                 if e > er
-                    e
-                    d / net.layers{l}.db{j}
                     error('numerical gradient checking failed');
                 end
                 for i = 1 : numel(net.layers{l - 1}.a)

CNN/cnnsetup.m

@@ -1,5 +1,4 @@
 function net = cnnsetup(net, x, y)
-    assert(exist('OCTAVE_VERSION')==0, 'CNNs does not work with Octave as there is a bug in the implementation of convolution in octave. See: http://savannah.gnu.org/bugs/?39314');
     inputmaps = 1;
     mapsize = size(squeeze(x(:, :, 1)));
 

CNN/convn_valid.m

@@ -0,0 +1,11 @@
+%Convolution for 3 dimensional vectors using conv2
+%equivalent to convn(A,B, 'valid')
+
+function result = convn_valid(A, B)
+    m = size(A, 1) - size(B, 1) + 1;
+    result = zeros(m, m);
+    B = flipdim(B,3);
+    for j=1:size(A, 3)  
+	 result += conv2(A(:,:,j),B(:,:,j), 'valid');
+    end
+end

tests/octave-core

@@ -9,25 +9,27 @@
 %% ex1 Train a 6c-2s-12c-2s Convolutional neural network 
 %will run 1 epoch in about 200 second and get around 11% error. 
 %With 100 epochs you'll get around 1.2% error
+
 rand('state',0)
+
 cnn.layers = {
     struct('type', 'i') %input layer
     struct('type', 'c', 'outputmaps', 6, 'kernelsize', 5) %convolution layer
     struct('type', 's', 'scale', 2) %sub sampling layer
     struct('type', 'c', 'outputmaps', 12, 'kernelsize', 5) %convolution layer
     struct('type', 's', 'scale', 2) %subsampling layer
 };
-cnn = cnnsetup(cnn, train_x, train_y);
+
 
 opts.alpha = 1;
-opts.batchsize = 50;
-opts.numepochs = 1;
+opts.batchsize = 200;
+opts.numepochs = 7;
 
+cnn = cnnsetup(cnn, train_x, train_y);
 cnn = cnntrain(cnn, train_x, train_y, opts);
 
 [er, bad] = cnntest(cnn, test_x, test_y);
 
 %plot mean squared error
 figure; plot(cnn.rL);
-
 assert(er<0.12, 'Too big error');

tests/test_example_CNN.m

@@ -0,0 +1,4 @@
+%detects if we're running Octave
+function result = isOctave()
+    result = exist('OCTAVE_VERSION') ~= 0;
+end