def test(expid):
# to test:
# OMP_NUM_THREADS=1 THEANO_FLAGS=device=cpu taskset -c 0 python $(expip)/code.py $(expid)
import os
os.chdir(expid)
print "loading data"
data = GenericClassificationDataset("cifar10", "../cifar_10_shuffled.pkl")
print "building model"
model, learn, test = build_model(False)
print "importing weights"
shared.importFromFile("weights.pkl")
print "testing"
import time
t0 = time.time()
test_error, test_cost = data.doTest(test, 50)
t1 = time.time()
print "Error, cost, time(s)"
print test_error, test_cost, t1 - t0
specialized_test_time = t1 - t0
normal_test_time = t1 - t0
f = file("test_results.txt", 'w')
f.write("specialized:%f\ntheano:%f\nerror:%f\n" %
(specialized_test_time, normal_test_time, test_error))
f.close()
def test(expid):
# to test:
# OMP_NUM_THREADS=1 THEANO_FLAGS=device=cpu taskset -c 0 python $(expip)/code.py $(expid)
import os
os.chdir(expid)
print "loading data"
data = GenericClassificationDataset("cifar10", "../cifar_10_shuffled.pkl")
print "building model"
model,learn,test = build_model(False)
print "importing weights"
shared.importFromFile("weights.pkl")
print "testing"
import time
t0 = time.time()
test_error, test_cost = data.doTest(test, 50)
t1 = time.time()
print "Error, cost, time(s)"
print test_error, test_cost, t1-t0
specialized_test_time = t1-t0
normal_test_time = t1-t0
f= file("test_results.txt",'w')
f.write("specialized:%f\ntheano:%f\nerror:%f\n"%(specialized_test_time, normal_test_time, test_error))
f.close()
