def __init__(self):
batch = cifar10.batch1()
train = batch['data'], batch['labels']
batch = cifar10.batch2()
valid = batch['data'], batch['labels']
batch = cifar10.batch3()
test = batch['data'], batch['labels']
Dataset.__init__(self, train, valid, test)
def __init__(self):
batch = cifar10.batch1()
train = batch['data'], batch['labels']
batch = cifar10.batch2()
valid = batch['data'], batch['labels']
batch = cifar10.batch3()
test = batch['data'], batch['labels']
Dataset.__init__(self, train, valid, test)
def __init__(self):
batch1 = cifar10.batch1()
batch2 = cifar10.batch2()
batch3 = cifar10.batch3()
x = numpy.vstack([batch1['data'], batch2['data'], batch3['data']])
y = numpy.concatenate([batch1['labels'], batch2['labels'], batch3['labels']])
self.train = x, y
self.valid = xy(cifar10.batch4())
self.test = xy(cifar10.batch5())
def __init__(self):
self.train = xy(cifar10.batch1())
self.valid = xy(cifar10.batch4())
self.test = xy(cifar10.batch5())
