def eval_grid_point(learner, name, t, cp, verbosity):
structure = learner
learner = {'dag':dag.run, 'tree':tree.run}[structure]
rs = random.getstate(), np.random.get_state()
start = time.time()
net, vld_llh, tst_llh = learner(name, t, cp, verbosity=verbosity)
elapsed = time.time() - start
result = {'name':name, 't':t, 'cp':cp, 'time':elapsed, 'num_nodes':len(net.pot), 'num_edges':net.num_edges, \
'vld_llh':vld_llh, 'tst_llh':tst_llh, 'spn':network.to_data(net), 'random_state':rs, 'structure':structure}
return result
def save_net(net, filename, prompt=False):
if filename is not None:
if prompt:
ri = raw_input('Keep this SPN? ')
if ri.lower() not in ['y', 'yes']:
return
print 'saving...'
spn = network.to_data(net)
with open(filename, 'wb') as fp:
pickle.dump(spn, fp)
