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# Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Download MNIST, Omniglot datasets for Rebar."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import urllib
import gzip
import os
import config
import struct
import numpy as np
import cPickle as pickle
import datasets
MNIST_URL = 'see README'
MNIST_BINARIZED_URL = 'see README'
OMNIGLOT_URL = 'see README'
MNIST_FLOAT_TRAIN = 'train-images-idx3-ubyte'
def load_mnist_float(local_filename):
with open(local_filename, 'rb') as f:
f.seek(4)
nimages, rows, cols = struct.unpack('>iii', f.read(12))
dim = rows*cols
images = np.fromfile(f, dtype=np.dtype(np.ubyte))
images = (images/255.0).astype('float32').reshape((nimages, dim))
return images
if __name__ == '__main__':
if not os.path.exists(config.DATA_DIR):
os.makedirs(config.DATA_DIR)
# Get MNIST and convert to npy file
local_filename = os.path.join(config.DATA_DIR, MNIST_FLOAT_TRAIN)
if not os.path.exists(local_filename):
urllib.urlretrieve("%s/%s.gz" % (MNIST_URL, MNIST_FLOAT_TRAIN), local_filename+'.gz')
with gzip.open(local_filename+'.gz', 'rb') as f:
file_content = f.read()
with open(local_filename, 'wb') as f:
f.write(file_content)
os.remove(local_filename+'.gz')
mnist_float_train = load_mnist_float(local_filename)[:-10000]
# save in a nice format
np.save(os.path.join(config.DATA_DIR, config.MNIST_FLOAT), mnist_float_train)
# Get binarized MNIST
splits = ['train', 'valid', 'test']
mnist_binarized = []
for split in splits:
filename = 'binarized_mnist_%s.amat' % split
url = '%s/binarized_mnist_%s.amat' % (MNIST_BINARIZED_URL, split)
local_filename = os.path.join(config.DATA_DIR, filename)
if not os.path.exists(local_filename):
urllib.urlretrieve(url, local_filename)
with open(local_filename, 'rb') as f:
mnist_binarized.append((np.array([map(int, line.split()) for line in f.readlines()]).astype('float32'), None))
# save in a nice format
with open(os.path.join(config.DATA_DIR, config.MNIST_BINARIZED), 'w') as out:
pickle.dump(mnist_binarized, out)
# Get Omniglot
local_filename = os.path.join(config.DATA_DIR, config.OMNIGLOT)
if not os.path.exists(local_filename):
urllib.urlretrieve(OMNIGLOT_URL,
local_filename)
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