def import_and_test():
import nnpy
print dir(nnpy)
for a in dir(nnpy):
print getattr(nnpy, a)
try:
print getattr(nnpy, a)()
except TypeError:
pass
set1 = [([1, 1], [1]),
([1, 0], [0]),
([0, 1], [0]),
([0, 0], [1])]
n = test_net([2, 10, 1], set1)
for a in dir(n):
print "n.%s: " % a
print getattr(n, a)
try:
print getattr(n, a).__doc__
except AttributeError:
pass
print "trying 4 layer net"
test_net([2,4,4,1], set1)
set2 = []
for x in range(16):
ins = (x >> 3, x >> 2 & 1, x >> 1 & 1, x & 1)
outs = (sum(ins)>>1 &1, sum(ins)&1)
set2.append((ins, outs))
#test_net([4,9,9,2], set2)
net = test_net([4, 11, 2], set2)
print "refcount is %s " % sys.getrefcount(net)
net.save_weights('/tmp/test.net')
net2 = nnpy.Network([4, 11, 2])#, 0.3, 0.3, 1.0)
print "loading weights"
net2.load_weights('/tmp/test.net')
#print_results(set2, net2)
print "trying 2 layer net"
net = nnpy.Network((3, 2))
print "trying 1 layer net -- should fail"
try:
net = nnpy.Network((2,))
except ValueError, e:
print e
def make_net(n_teams):
net = nnpy.Network([
16 + 16 * n_teams + config.EXTRA_INPUTS + config.FEEDBACK_NODES,
config.LAYER2_NODES, config.OUTPUT_NODES + config.FEEDBACK_NODES
],
bias=1)
return net
def memtest():
from resource import getrusage, RUSAGE_SELF
#x =[]
for z in range(50):
t = time.time()
for y in range(100000):
net = nnpy.Network([5, 13, 3], weight_range=(-1,1))
net.opinion((0,0,0,0,0))
#x.append(net)
print getrusage(RUSAGE_SELF)[2:8], time.time() - t
def get_net(team):
inputs = (team.inputs_per_type * (team.game.n_teams + 1) +
config.EXTRA_INPUTS + config.FEEDBACK_NODES)
outputs = len(team.directions) + team.fires + config.FEEDBACK_NODES
if config.LAYER2_NODES:
shape = [inputs, config.LAYER2_NODES, outputs]
else:
shape = [inputs, outputs]
return nnpy.Network(shape, bias=1)
def test_net(dimensions, set, momentum=0.3, learn_rate=0.2, scale=1, r=(-0.5,0.5), count=10000,threshold=0.00001):
import nnpy
net = nnpy.Network(dimensions, momentum=momentum,
learn_rate=learn_rate, scale=scale, weight_range=r)
print "in test_net, refcount is %s " % sys.getrefcount(net)
#net.randomise(r)
net.learn_rate = 0.23
net.momentum = 0.321
print "set learn_rate and momentum "
t = time.time()
print "got time"
net.train_set(set, count, threshold, 0)
print "took %s seconds" % (time.time() - t)
#print_results(set, net)
w = net.get_weights()
print "copied net via python:"
net2 = nnpy.Network(dimensions)
net2.set_weights(w)
#print_results(set, net2)
return net
def seed_nets(entropy):
"""seed the nnpy generator. once per game works for all nets"""
random_holding_net = nnpy.Network([2, 3, 1])
random_holding_net.seed_random(entropy[1])
return random_holding_net