def __init__(self):
self._target_size = 10
logging.info("loading minst data")
path = os.path.join(tempfile.gettempdir(), "mnist.pkl.gz")
if not os.path.exists(path):
logging.info("downloading minst data")
urllib.urlretrieve (MNIST_URL, path)
self._train_set, self._valid_set, self._test_set = cPickle.load(gzip.open(path, 'rb'))
# Moving validation examples to training set, leaving 1000
train_set_x = np.vstack((self._train_set[0], self._valid_set[0][:-1000]))
train_set_y = np.hstack((self._train_set[1], self._valid_set[1][:-1000]))
valid_set_x = self._valid_set[0][-1000:]
valid_set_y = self._valid_set[1][-1000:]
self._train_set = (train_set_x, train_set_y)
self._valid_set = (valid_set_x, valid_set_y)
logging.info("[mnist small validation] training data size: %d" % len(self._train_set[0]))
logging.info("[mnist small validation] valid data size: %d" % len(self._valid_set[0]))
logging.info("[mnist small validation] test data size: %d" % len(self._test_set[0]))
mnist_small_validation.py 文件源码
python
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