function rbm = rbmtrain(rbm, x, opts)
assert(isfloat(x), 'x must be a float');
assert(all(x(:)>=0) && all(x(:)<=1), 'all data in x must be in [0:1]');
m = size(x, 1);
numbatches = m / opts.batchsize;
assert(rem(numbatches, 1) == 0, 'numbatches not integer');
for i = 1 : opts.numepochs
kk = randperm(m);
err = 0;
for l = 1 : numbatches
batch = x(kk((l - 1) * opts.batchsize + 1 : l * opts.batchsize), :);
v1 = batch;
h1 = sigmrnd(repmat(rbm.c', opts.batchsize, 1) + v1 * rbm.W');
v2 = sigmrnd(repmat(rbm.b', opts.batchsize, 1) + h1 * rbm.W);
h2 = sigm(repmat(rbm.c', opts.batchsize, 1) + v2 * rbm.W');
c1 = h1' * v1;
c2 = h2' * v2;
rbm.vW = rbm.momentum * rbm.vW + rbm.alpha * (c1 - c2) / opts.batchsize;
rbm.vb = rbm.momentum * rbm.vb + rbm.alpha * sum(v1 - v2)' / opts.batchsize;
rbm.vc = rbm.momentum * rbm.vc + rbm.alpha * sum(h1 - h2)' / opts.batchsize;
rbm.W = rbm.W + rbm.vW;
rbm.b = rbm.b + rbm.vb;
rbm.c = rbm.c + rbm.vc;
err = err + sum(sum((v1 - v2) .^ 2)) / opts.batchsize;
end
disp(['epoch ' num2str(i) '/' num2str(opts.numepochs) '. Average reconstruction error is: ' num2str(err / numbatches)]);
end
end
