Python cifar_info_gain Beispiele

Beispiel #1

Datei: script_obtain_cifar_test_infogain.py Projekt: wenhuach/anytime_recognition

########
# Settings
########

FEATDIR = "/u/vis/ttmp/jiayq/cifar100/"

########
# Main script
########
if mpi.SIZE > 1:
    raise RuntimeError, "This script runs on single machine only."

Xtest = mpi.load_matrix_multi(os.path.join(FEATDIR, 'Xtest'))
Ytest = mpi.load_matrix_multi(os.path.join(FEATDIR, 'Ytest')).astype(np.int)

infogain = tax.cifar_info_gain()

info_mean = infogain.mean(axis=1)
info_max = infogain.max(axis=1)

randguess = sum([info_mean[y] for y in Ytest]) / float(len(Ytest))
bestguess = sum([info_max[y] for y in Ytest]) / float(len(Ytest))

print 'Random guess baseline:', randguess
print 'Best guess baseline:', bestguess

for filename in sys.argv[1:]:
    data = pickle.load(open(filename))
    w, b = data[:2]
    accu_test = data[-1]
    pred = np.argmax(np.dot(Xtest, w) + b, axis=1)

Beispiel #2

Datei: script_obtain_cifar_test_infogain.py Projekt: 2dpodcast/anytime_recognition

########
# Settings
########

FEATDIR = "/u/vis/ttmp/jiayq/cifar100/"

########
# Main script
########
if mpi.SIZE > 1:
    raise RuntimeError, "This script runs on single machine only."

Xtest = mpi.load_matrix_multi(os.path.join(FEATDIR,'Xtest'))
Ytest = mpi.load_matrix_multi(os.path.join(FEATDIR,'Ytest')).astype(np.int)
    
infogain = tax.cifar_info_gain()

info_mean = infogain.mean(axis=1)
info_max = infogain.max(axis=1)

randguess = sum([info_mean[y] for y in Ytest]) / float(len(Ytest))
bestguess = sum([info_max[y] for y in Ytest]) / float(len(Ytest))

print 'Random guess baseline:', randguess
print 'Best guess baseline:', bestguess

for filename in sys.argv[1:]:
    data = pickle.load(open(filename))
    w, b = data[:2]
    accu_test = data[-1]
    pred = np.argmax(np.dot(Xtest, w) + b, axis=1)