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()