def save_weights():
#loop through all perceptrons and save weights to file
weights = []
for percep in perceptrons:
weights.append(percep.label + ":" + str(percep.weight) + '\n')
fm.write_file('data/weights.txt', weights, 'w+')
return
def check_progress():
tmp = fm.read_file("data/progress.txt")
if tmp != None:
return tmp
else:
print("Progress File Not Found: Creating One...")
fm.write_file("data/progress.txt", '', "w+")
print("Progress File Created!")
return []
def get_user():
tmp = fm.read_file("data/user.txt")
if tmp != None:
return tmp
else:
print("User File Not Found: Creating One...")
user_email = input('User Email: ') + "\n"
print("Retrieving User Token...")
token = json.dumps(get_token(user_email))
print("Token Collected!")
fm.write_file("data/user.txt", [user_email, token], 'w')
return [user_email, token]
def save_progress(last_output):
fm.write_file("data/progress.txt", last_output + '\n', 'a')
return
def save_hash(line):
fm.write_file('data/hashes.txt', line, 'a')
return
def save_training_data(target, blob):
#save server challenge and answer in a training file
line = target + ":" + blob + "\n"
fm.write_file('data/scipio_training_data.txt', line, 'a')
def execute():
counter = 0
streak = 0
top_streak = 0
time_start = time.time()
while True:
(targets, blob) = request()
#set all outputs
for percep in perceptrons:
percep.input = compute_frequency(blob, percep.chunk)
percep.get_output()
count = {}
for percep in perceptrons:
if percep.output == 1 and targets.__contains__(percep.label):
if percep.label in count.keys():
count[percep.label] = count[percep.label] + 1
else:
count[percep.label] = 1
try:
guess = max(count, key=count.get)
#if confidence low ie low fire rate .. raise and pull
net_conf = int(count.get(guess))
if net_conf <= confidence:
print('low answer confidence...low fire[' +
str(int(count.get(guess))) + "]")
raise ('')
print("Guess:\t" + guess + '\tConfidence: ' + str(net_conf))
response = solve(guess)
correct_resp = response.json()['correct']
target = response.json()['target']
accuracy = response.json()['accuracy']
try:
hash_resp = response.json()['hash']
print("HASH COLLECTED!")
time_stop = time.time()
time_total = time_stop - time_start
save_hash("Streak: " +
str(fm.read_file('data/top_streak.txt')) +
"Correct: " + str(correct_resp) + "\tAccuracy: " +
str(accuracy) + "\tTotal Time: " + str(time_total) +
"\nHash: " + hash_resp + "\n")
# ask_hash(email)
except:
hash_resp = "None"
print('Answer: ' + target + '\tNumber: ' + str(correct_resp) +
"\tAccuracy: " + str(accuracy))
if (target == guess):
streak = streak + 1
# if streak > top_streak:
# top_streak=streak
print("streak: " + str(streak) + '\n')
else:
if int(fm.read_file('data/top_streak.txt')) < streak:
fm.write_file('data/top_streak.txt', top_streak, 'w+')
print('streak reset...\n')
streak = 0
for percep in perceptrons:
percep.adjust_weight(target)
percep.mod = random.choice([0, 1])
counter = counter + 1
save_training_data(target, blob)
#save weights every 10 cycles
if counter % 10 == 0:
print("Weights saved!")
save_weights()
except:
pass
return