function net = cnntrain(net, x, y, opts, test_x, test_y)

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);

for iter = 1 : numbatches

batch_x = x(:, :, kk((iter - 1) * opts.batchsize + 1 : iter * opts.batchsize));

batch_y = y(:, kk((iter - 1) * opts.batchsize + 1 : iter * opts.batchsize));

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;

%if(mod(i,2) == 0)

[er, bad] = cnntest(net, test_x, test_y);

disp('==============================');

fprintf('Epoch=%d error=%f\n', i, er);

disp('==============================');

%end

end