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Paddle/python/paddle/v2/dataset/cifar.py

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"""
CIFAR Dataset.
URL: https://www.cs.toronto.edu/~kriz/cifar.html
the default train_creator, test_creator used for CIFAR-10 dataset.
"""
import cPickle
import itertools
import tarfile
import numpy
from common import download
__all__ = [
'cifar_100_train_creator', 'cifar_100_test_creator', 'train_creator',
'test_creator'
]
CIFAR10_URL = 'https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz'
CIFAR10_MD5 = 'c58f30108f718f92721af3b95e74349a'
CIFAR100_URL = 'https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz'
CIFAR100_MD5 = 'eb9058c3a382ffc7106e4002c42a8d85'
def __read_batch__(filename, sub_name):
def reader():
def __read_one_batch_impl__(batch):
data = batch['data']
labels = batch.get('labels', batch.get('fine_labels', None))
assert labels is not None
for sample, label in itertools.izip(data, labels):
yield (sample / 255.0).astype(numpy.float32), int(label)
with tarfile.open(filename, mode='r') as f:
names = (each_item.name for each_item in f
if sub_name in each_item.name)
for name in names:
batch = cPickle.load(f.extractfile(name))
for item in __read_one_batch_impl__(batch):
yield item
return reader
def cifar_100_train_creator():
fn = download(url=CIFAR100_URL, md5=CIFAR100_MD5)
return __read_batch__(fn, 'train')
def cifar_100_test_creator():
fn = download(url=CIFAR100_URL, md5=CIFAR100_MD5)
return __read_batch__(fn, 'test')
def train_creator():
"""
Default train reader creator. Use CIFAR-10 dataset.
"""
fn = download(url=CIFAR10_URL, md5=CIFAR10_MD5)
return __read_batch__(fn, 'data_batch')
def test_creator():
"""
Default test reader creator. Use CIFAR-10 dataset.
"""
fn = download(url=CIFAR10_URL, md5=CIFAR10_MD5)
return __read_batch__(fn, 'test_batch')
def unittest():
for _ in train_creator()():
pass
for _ in test_creator()():
pass
if __name__ == '__main__':
unittest()