Dividing data for neural network

If I want to use dividerand and retraining for 10 times shoould the dividerand also be on the loop of 10 times or it should be out of the loop?

% dividing the data randomly
net.divideFcn = 'dividerand';  
        net.divideMode = 'sample';  % Divide up every sample
                    net.divideParam.trainRatio = 70/100;
                    net.divideParam.valRatio = 15/100;
                    net.divideParam.testRatio = 15/100;

for j=1:100 % number of hidden neuron
    net = feedforwardnet(j);
    for i =1:10 % 10 times for creating 10 network
        net = configure(net,inputs,targets);
        [ net tr y e ]  = train(net,inputs,targets);
save net
end 
end

If the function "configure" can define different initial weights and rng, how about the different random dividing of data (which allocates 70/15/15 among train/val/test)? Should we use different division of dataset for each neuron or repetition ? or the division of datasets should be the same for each neuron? Thanks