def submit_vector():
# best_vec = []
# GET THE VALUE HERE
best_vecs = [{
'vector': [
-1.5900117634696895e-18, -1.1089152508024613e-12,
-2.5448264472393646e-13, 5.156495819895334e-11,
-1.4685999507818116e-10, -1.7336464013051853e-15,
7.588385881788844e-16, 2.7525165125385616e-05,
-1.8852756204130466e-06, -1.5953841373151045e-08,
8.741325830954951e-10
],
'results': [116101460426.6661, 87860031424.50586],
'generation':
32
}]
i = 0
f = open("last_vector_8th.txt", "a")
for best_vec in best_vecs:
# break
x = submit(TEAM_KEY, best_vec["vector"])
print(x)
rank = input()
# SAVING THE VECTOR IN LAST VECTOR
f.write(str(best_vec))
f.write("\n")
f.write(rank)
f.write("\n")
# IF THIS VECTOR GETS THE BEST RANK YET, DO:
# bash save_this_vector.sh
f.close()
def main():
np.set_printoptions(formatter={'float_kind':'{:f}'.format})
population = generate_population()
while 1:
fitness = fitness_function(population)
np.save('example',population)
np.save('error',fitness)
print(population,fitness)
offspring = np.zeros((16,11))
offspring[0:2]= sel.rank_selection(population,fitness)
offspring[0:2]= sel.rank_selection2(population,fitness)
for i in range(4,10):
offspring[i] = mut.random_setting_mutation(offspring[rand.randint(0,4)])
for i in range(10,16):
first = rand.randint(0,4)
second = rand.randint(0,4)
while first is not second:
second = rand.randint(0,4)
offspring[i] = cs.mutation_crossover(np.array([offspring[first],offspring[second]]))
population = np.copy(offspring)
print(cl.submit(key,np.ndarray.tolist(offspring[0])))
print(cl.submit(key,np.ndarray.tolist(offspring[1])))
print(cl.submit(key,np.ndarray.tolist(offspring[2])))
print(cl.submit(key,np.ndarray.tolist(offspring[3])))
def clean(self, values):
super(ReCaptchaField, self).clean(values[1])
recaptcha_challenge_value = smart_unicode(values[0])
recaptcha_response_value = smart_unicode(values[1])
if settings.DEBUG and recaptcha_response_value == 'PASSED':
return values[0]
check_captcha = client.submit(recaptcha_challenge_value, \
recaptcha_response_value, private_key=self.private_key, \
remoteip=self.get_remote_ip(), use_ssl=self.use_ssl)
if not check_captcha.is_valid:
raise forms.util.ValidationError(
self.error_messages['captcha_invalid']
)
return values[0]
def clean(self,values):
'''
values[0]= requestID
values[1]= codefromuser
'''
super(NexmoField, self).clean(values[1])
nexmo_challenge_value = smart_unicode(values[1])
request_id=smart_unicode(values[0])
try:
responce = client.submit(
request_id,
nexmo_challenge_value)
except socket.error: # Catch timeouts, etc
raise ValidationError(
'network error'
)
if responce.status!=0:
raise ValidationError(
responce.error_text
)
return values[1]
generation = Gene.generate_population(POPULATION_SIZE)
assert all([type(person) is Gene for person in generation])
for i in range(ITERATIONS):
print('****************************')
couples = Gene.pairing(generation)
children = Gene.mating(couples)
generation = Gene.selection(generation + children)
assert all([type(person) is Gene for person in generation])
# Checking if the change in hyperparameters is useful
print("Best Soln : ")
print(BEST_WEIGHTS, BEST_ERROR)
# Submitting it regardless
client.submit(SECRET_KEY, list(BEST_WEIGHTS))
# ## Sample Ouput
#
# The format is [gene] , training error, validation error.
#
# A single generation output is :
#
# [ 0.00000000e+00 1.24051937e-01 -6.21157191e+00 4.93390104e-02<br>
# 3.81066382e-02 8.13198767e-05 -6.01791626e-05 -1.25163350e-07<br>
# 3.48379719e-08 4.16166196e-11 -6.73266866e-12] 79068.35618656754 3625009.2445584373<br>
#
# [ 0.00000000e+00 2.48074052e-01 -6.21227586e+00 4.93420788e-02<br>
# 3.81088826e-02 8.13320094e-05 -6.01862275e-05 -1.25174854e-07<br>
# 3.48411764e-08 4.16121405e-11 -6.73257744e-12] 78564.99206532972 3599264.6284862114<br>
#
# ] # tempv = [ # -0.010352359899980625, # -1.4938708798725434e-12, # -2.1344537013801585e-13, # 4.754606122495976e-11, # -1.7513765845712067e-10, # -2.9750369207778414e-20, # 2.216842207753494e-20, # 8.683381211976487e-15, # -6.662021179304016e-09, # -2.6599123253785434e-14, # 3.026701227755296e-17 # ] # tempv = [ # -0.00924596659365373, # -1.494818150350766e-12, # -2.211532640173319e-13, # 5.039657579364812e-11, # -1.6753978508012588e-10, # -9.080082588227132e-25, # 7.257195414468184e-26, # 4.605087763217074e-20, # -1.3071635934940838e-11, # -1.4401903358063287e-17, # 2.7501251088023155e-21 # ] server.submit(TEAM_ID, tempv) # In[ ]:
def runEvolution(self, steps: int) -> None:
"""Run step iterations of genetic algorithm"""
population = self.initializePopulation()
for iteration in range(steps):
fitness, testFitness = self.calculateFitness(population)
sortedIndices = (abs(fitness + testFitness)).argsort()
population = population[sortedIndices]
fitness = fitness[sortedIndices]
testFitness = testFitness[sortedIndices]
print("Fitness: ", np.array([fitness[0]]))
print("Test Fitness: ", np.array([testFitness[0]]))
print("Vector: ", population[0])
# print("\n", population[0])
submit(population.tolist()[0])
with open("generations.txt", "a") as outfile:
pprint(
f"-----------GENERATION: {iteration}--------------",
stream=outfile,
)
pprint(population, stream=outfile)
pprint(
f"---Train Fitness: {iteration}---",
stream=outfile,
)
pprint(fitness, stream=outfile)
pprint(
f"---Test Fitness: {iteration}---",
stream=outfile,
)
pprint(testFitness, stream=outfile)
input()
# Gurantee that top two will be selected without any mutation or
# crossover: 9 = 8 + 1
nextGeneration = population[:1]
nonMutatedNextGen = population[:1]
for crossoverIteration in range(self.populationSize):
# Select two parents from population
index_a, index_b = self.selectTwo(population)
# Cross them
offspring_a, offspring_b = self.crossOver(
population[index_a],
population[index_b],
fitness[index_a],
fitness[index_b],
)
nonMutatedNextGen = np.concatenate(
(nonMutatedNextGen, [offspring_a, offspring_b]), axis=0
)
# Mutate
offspring_a = self.mutateOffspring(offspring_a)
offspring_b = self.mutateOffspring(offspring_b)
# Add to next generation
nextGeneration = np.concatenate(
(nextGeneration, [offspring_a, offspring_b]), axis=0
)
population = nextGeneration[:self.populationSize]
with open("generations.txt", "a") as outfile:
pprint(
f"---After crossover population: {iteration}---",
stream=outfile,
)
pprint(nonMutatedNextGen, stream=outfile)
pprint(
f"---After mutation population: {iteration}---",
stream=outfile,
)
pprint(nextGeneration, stream=outfile)
pprint(
f"---After Selection population: {iteration}---",
stream=outfile,
)
pprint(population, stream=outfile)
-1.155594498963827e-06,
-1.4123701076309361e-09,
4.27567136105673e-10
]
# "errorTuple": [
# 39607118493.38789,
# 82107826837.5237
# ] 8 star
v = [
-1.2011582262254875e-22,
-4.841884920942542e-13,
-3.3920520574732524e-13,
5.7520186415565817e-11,
-1.2165314793847423e-09,
-2.732620328430599e-16,
7.837772952003539e-17,
6.543320242559382e-06,
-1.1555982661911288e-06,
-1.1821086653098595e-09,
4.199995041318772e-10
]
# "errorTuple": [
# 41208277820.35068,
# 97512445787.4025
# ] 19
res = client.submit(secrets.KEY, v)
print(res)
# -1.83977009e-10, -1.47605324e-15, 7.40791508e-16, 2.41394471e-05,
# -1.90069755e-06, -1.58002421e-08, 9.01600023e-10]
#[ 0.00000000e+00, -1.43185174e-12, -2.71229788e-13, 4.15487720e-11,
# -1.74740805e-10, -1.49297563e-15, 7.57681374e-16, 2.38883785e-05,
# -1.87813527e-06, -1.60177440e-08, 8.96744048e-10]
#[ 0.00000000e+00, -1.50721525e-12, -2.38330355e-13, 4.60972509e-11,
# -1.89423828e-10, -1.73086769e-15, 9.13556565e-16, 2.42086504e-05,
# -1.99153311e-06, -1.49579921e-08, 9.24081436e-10]
#[ 0.00000000e+00, -1.56391135e-12, -2.44028674e-13, 3.93282451e-11,
# -1.83236407e-10, -1.63784812e-15, 8.96217971e-16, 2.54014231e-05,
# -1.99701550e-06, -1.52996086e-08, 9.21303663e-10]
#best: best-submission-7
# [ 0.00000000e+00, -1.55976128e-12, -2.34784495e-13, 4.29084694e-11,
# -1.89954128e-10, -1.61562430e-15, 8.62092675e-16, 2.42243848e-05,
# -1.99597630e-06, -1.47379698e-08, 9.22303588e-10]
#[ 0.00000000e+00,-1.20706058e-12, -2.32612320e-13 , 4.50071868e-11,
# -1.88160202e-10, -1.85757143e-15, 8.83139750e-16, 2.49351778e-05,
# -1.90201334e-06, -1.75150969e-08, 9.37418225e-10]
#best:
#[ 0.00000000e+00, -1.56391135e-12, -2.44028674e-13, 3.93282451e-11,
# -1.83236407e-10, -1.63784812e-15, 8.96217971e-16, 2.54014231e-05,
# -1.99701550e-06, -1.52996086e-08, 9.21303663e-10]
print(
client.submit('GU0MCOlKFoi0lk7HmBpwjhFGlcTTZvO77FA3FVMq0m4lYCMIho',
weights))
import client
import constants
v = [
-1.3675704081705325e-09,
-4.08138881979391e-13,
-2.5005644219889285e-10,
4.662859881370373e-12,
6.150047217005676e-12,
-9.161738820014592e-16,
7.340163120738338e-10,
5.018644203347845e-06,
-1.2133184934354136e-06,
-6.572866429792964e-10,
4.4955546296023274e-10,
]
res = client.submit(constants.SECRET_KEY, v)
print(res)
wt2 = [
9.913269136508803e-19, -1.3651432220474988e-12, -2.298198393159188e-13,
5.0168495585679045e-11, -1.9142692264536784e-10, -5.708139268721448e-16,
9.222307658340838e-16, 3.2077307818350485e-05, -2.1023487765642816e-06,
-1.3862270237706852e-08, 8.640892314427145e-10
]
wt2 = [
9.915672591936594e-19, -1.3654972148183978e-12, -2.3013915250437e-13,
5.0202893139928207e-11, -1.9197681316495378e-10, -5.695747268129501e-16,
9.247415970198904e-16, 3.204237015306432e-05, -2.0963811355424884e-06,
-1.3922304080398685e-08, 8.619693246341732e-10
]
# wt2 = [9.919603226020886e-19, -1.3643039330187416e-12, -2.300025187475665e-13, 5.01420607948874e-11, -1.9171213875705204e-10, -5.704916302387945e-16, 9.249323842424032e-16, 3.2018325502112234e-05, -2.092484885878187e-06, -1.3842788049128266e-08, 8.640308071699504e-10]
# wt2 = [1.0152006490722198e-18, -1.2675221413533424e-12, -2.219456862667535e-13, 5.2746185700513954e-11, -2.048741688083159e-10, -5.906269772197416e-16, 9.464899300647767e-16, 3.105910784304104e-05, -2.055769267289396e-06, -1.6494805651419324e-08, 9.224439203791275e-10]
status = server.submit(TEAM_ID, list(wt2))
print(status)
# for i in range(10):
# weights[7] -= 0.02e-05
train_err, valid_err = server.get_errors(TEAM_ID, list(wt2))
tot_err = train_err + valid_err
# print(wt2)
print('fitness:')
print("{:e}".format(-tot_err), "{:e}".format(train_err),
"{:e}".format(valid_err))
# INITIAL_WEIGHTS = [1.0016758736507022e-18, -1.3696155264603411e-12, -2.300768584393704e-13, 4.617028826499339e-11, -1.7627848513209744e-10, -1.7730847899381538e-15, 8.38639892842589e-16, 2.2778568625222342e-05, -1.9784050209132108e-06, -1.5846641527483793e-08, 9.522475355911996e-10]