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Please let me know if I am making any error in parameter selection that may have resulted in this issue. The details of the parameter along with data set are as follows -
dim(train_x) = 29x29x131072
dim(train_y) = 4x1x131072
similarly test data sets.
Now, number of layers = 5 as per default in the test_example_CNN. With kernel size = 3 in both layer 2 & 4. Scale factor is set to be 3 in layer 3 and 7(just for trial purposes) in layer 5.
you shou add a function to do this, the purpose of the matrix expansion.
/////////////////////////////////////////////////////////////////////////////////////////////////
function expand_bp = expand_cnn(x,y)
expand_bp = zeros(size(x,1)*y(1),size(x,2)*y(2),size(x,3)*y(3)); %
test_column = zeros(size(x,1)*y(1),size(x,2)*y(2),size(x,3));;% column operation
test_row = zeros(size(x,1)*y(1),size(x,2),size(x,3)); % row operation
row_row = y(1);
column_column = y(2);
heigh_heigh = y(3);
for n =1: size(x,3)
% row operation
for row = 1:size(x,1)
while row_row>0
test_row(y(1)*row-(row_row-1),:,n) = x(row,:,n);
row_row = row_row-1;
end
row_row = y(1);
end
% column operation
for column = 1:size(x,2)
while column_column>0
test_column(:,(y(2)*column-(column_column-1)),n) = test_row(:,column,n);
column_column = column_column-1;
end
column_column = y(2);
end
% third dimension
while heigh_heigh>0
expand_bp(:,:,y(3)*n-(heigh_heigh-1)) = test_column(:,:,n);
heigh_heigh = heigh_heigh-1;
end
heigh_heigh = y(3);
end
There is an error in cnnbp.m file, which said that
////////////////////////////////////////////////
“Undefined function ‘expand’ for input arguments of type ‘double’.”
in the following line:
net.layers{l}.d{j} = net.layers{l}.a{j} .* (1 – net.layers{l}.a{j}) .* (expand(net.layers{l + 1}.d{j}, [net.layers{l + 1}.scale net.layers{l + 1}.scale 1]) / net.layers{l + 1}.scale ^ 2);
//////////////////////////////////////////////
Please let me know if I am making any error in parameter selection that may have resulted in this issue. The details of the parameter along with data set are as follows -
similarly test data sets.
Now, number of layers = 5 as per default in the test_example_CNN. With kernel size = 3 in both layer 2 & 4. Scale factor is set to be 3 in layer 3 and 7(just for trial purposes) in layer 5.
opts.alpha = 1
opts.batchsize = 64
opts.numepochs = 1
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