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from darknet import *
def predict_tactic(net, s):
prob = 0
d = c_array(c_float, [0.0]*256)
tac = ''
if not len(s):
s = '\n'
for c in s[:-1]:
d[ord(c)] = 1
pred = predict(net, d)
d[ord(c)] = 0
c = s[-1]
while 1:
d[ord(c)] = 1
pred = predict(net, d)
d[ord(c)] = 0
pred = [pred[i] for i in range(256)]
ind = sample(pred)
c = chr(ind)
prob += math.log(pred[ind])
if len(tac) and tac[-1] == '.':
break
tac = tac + c
return (tac, prob)
def predict_tactics(net, s, n):
tacs = []
for i in range(n):
reset_rnn(net)
tacs.append(predict_tactic(net, s))
tacs = sorted(tacs, key=lambda x: -x[1])
return tacs
net = load_net("cfg/coq.test.cfg", "/home/pjreddie/backup/coq.backup", 0)
t = predict_tactics(net, "+++++\n", 10)
print t
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