human
I wrote the below code

    def gibbs_step(v):
        mean_h = T.nnet.sigmoid((T.dot(v, W) + bh))
        h = rng.binomial(size=mean_h.shape, n=1, p=mean_h, dtype=theano.config.floatX)
        mean_v = T.nnet.sigmoid((T.dot(h, W.T) + bv))
        v = rng.binomial(size=mean_v.shape, n=1, p=mean_v, dtype=theano.config.floatX)
        return (mean_v, v)
    (chain, updates) = theano.scan((lambda v: gibbs_step(v)[1]), outputs_info=[v], n_steps=k)
    v_sample = chain[(-1)]
    mean_v = gibbs_step(v_sample)[0]
    monitor = (T.xlogx.xlogy0(v, mean_v) + T.xlogx.xlogy0((1 - v), (1 - mean_v)))
    monitor = (monitor.sum() / v.shape[0])
    def free_energy(v):
        return ((- (v * bv).sum()) - T.log((1 + T.exp((T.dot(v, W) + bh)))).sum())
    cost = ((free_energy(v) - free_energy(v_sample)) / v.shape[0])
    return (v_sample, cost, monitor, updates)

What's a good function header?
 ... Here's a good function header?
assistant
#Here's a good function header.

def build_rbm(v, W, bv, bh, k):