def primal_loss(w_vect, reg, i_primal, record_results=False):
RS = RandomState((seed, i_primal, "primal"))
idxs = RS.randint(N_data, size=batch_size)
minibatch = dictslice(data, idxs)
loss = loss_fun(w_vect, **minibatch)
reg = regularization(w_vect, reg)
if record_results and i_primal % N_thin == 0:
print "Iter {0}: train: {1}".format(i_primal, getval(loss))
return loss + reg
