if check_base_rbm_partition_function:
baserbm = RestrictedBoltzmannMachine(0, cfg.n_vis, cfg.n_hid, 0)
baserbm.weights = gp.zeros(baserbm.weights.shape)
baserbm.bias_hid = gp.zeros(baserbm.bias_hid.shape)
baserbm.bias_vis = ais.base_bias_vis
print "Base RBM log partition function using partition_func: %f" % baserbm.partition_function(20, 50).ln()
# perform estimation of partition function
print "Estimating partition function using %dx %d AIS runs with %d intermediate "\
"RBMs and %d Gibbs steps..." % (ais_iterations, ais_runs, len(ais_betas), ais_gibbs_steps)
with open("ais_iterations.csv", 'w') as outfile:
outfile.write("iterations\tlog Z\n")
lpfs = []
for i in range(ais_iterations):
lpf, lpf_m_3s, lpf_p_3s = ais.log_partition_function(ais_betas, ais_runs,
ais_gibbs_steps)
lpfs.append(lpf)
print "%3d: ln Z = %3.6f; ln(Z-3s) = %3.6f; ln(Z+3s) = %3.6f" \
% (i, lpf, lpf_m_3s, lpf_p_3s)
outfile.write("%d\t%f\n" % (i, lpf))
lpf_mean = np.mean(lpfs)
lpf_std = np.std(lpfs)
print
print "mean: ln Z = %f +/- %f" % (lpf_mean, lpf_std)
np.savez_compressed("lpf-%02d.npz" % epoch, lpf=lpf_mean, lpf_std=lpf_std)
