class Breeder(object):
def __init__(self,
init_pop,
growth_time=2 * 60,
mut_prob=0.5,
pop_size=30):
self._init_pop = init_pop
self._mut_prob = mut_prob
self._evaluator = Evaluator(growth_time)
self._nsgaii_sorter = NSGAII(2, None, None)
self._pop_size = pop_size
def breed(self, gen_num, result_file='results.csv'):
curr_pop = self._init_pop[:] # copy
eval_dict = {}
f = open(result_file, 'w')
for g_idx in range(gen_num):
kids = []
if g_idx == 0:
kids += [no_mutation(ip) for ip in curr_pop]
i_idx = -1
while len(kids) < self._pop_size - len(curr_pop):
i_idx += 1
try:
poppa = random.choice(curr_pop)
momma = random.choice(curr_pop)
print poppa, momma
kid = crossover.crossover(poppa,
momma,
'%d_%d' % (g_idx, i_idx),
genpath=code_path)
print kid
if self._mut_prob > random.random():
kid = mutation(kid)
else:
kid = no_mutation(kid)
kids.append(kid)
except RuntimeError:
print 'death due to wrong size'
continue
except Exception as e:
print '%d_%d' % (g_idx, i_idx), 'dead'
print 'death cause:', str(e)
continue
for name in curr_pop + kids:
print name
if len(eval_dict.keys()) != 0:
eval_results = [(name, eval_dict[name][0], eval_dict[name][1])
for name in curr_pop]
else:
eval_results = []
curr_pop += kids
# eval_dict = {} # for fun
for indiv in kids:
print indiv
try:
indiv_score = self._evaluator._indiv_evaluator(indiv)
except Exception as e:
print 'indiv born with defect, killed.'
print 'death cry:', str(e)
indiv_score = (-1, 10000000)
eval_dict[indiv] = indiv_score
indiv_score = (indiv, indiv_score[0], indiv_score[1])
eval_results.append(indiv_score)
selected = self._nsgaii_sorter.run(eval_results, self._pop_size)
plt.plot([i[1] for i in eval_results],
[i[2] for i in eval_results], 'b.')
plt.title('Generation %d' % g_idx)
plt.xlabel('Accuracy (%)')
plt.ylabel('Inference Time (s)')
plt.savefig(img_path + ('/gen%d_pareto.png' % g_idx))
plt.clf()
curr_pop = selected
for chosen in selected:
print 'Honorable chosen neural network in gen %d: %s' % (
g_idx, chosen)
print 'Score: (%.2f, %.2f)' % (eval_dict[chosen])
f.write(chosen + ',')
f.write('%.2f,%.2f' % (eval_dict[chosen]) + '\n')
f.close()
