def main():
# tb(Traceback.colour) function should be removed
import tb
tb.colour()
# user code
ultraTrainSet()
def main():
# tb(Traceback.colour) function should be removed
import tb
tb.colour()
# user code
ResnetRunner().train_test()
def main():
# tb(Traceback.colour) function should be removed
import tb
tb.colour()
# user code
a = np.ones((2, 3))
b = np.array(np.arange(0, 6).reshape((2, 3))) - 1
print(accuracy(a, b))
print('max={}, mean={:.3f}, shape={}'.format(
np.array(sample).max(),
np.array(sample).mean(), sample.size))
sample = sample.convert('L')
print('max={}, mean={:.3f}, shape={}'.format(
np.array(sample).max(),
np.array(sample).mean(), sample.size))
# sample = T.ToTensor()(sample)
sample = torch.Tensor(np.array(sample))
print('max={}, mean={:.3f}, shape={}'.format(
np.array(sample).max(),
np.array(sample).mean(), sample.shape))
# target = torch.Tensor(target)
def main():
# user code
data_analysis()
# data_debug()
if __name__ == '__main__':
# pdb: python debuger
import pdb
# tb(Traceback.colour) function should be removed
import tb
tb.colour()
main()
def main():
# tb(Traceback.colour) function should be removed
import tb
tb.colour()
def main():
import tb
tb.colour()
sinaAnalyser().run()