Module keras.datasets.cifar
Utilities common to CIFAR10 and CIFAR100 datasets.
Expand source code
# Copyright 2015 The TensorFlow Authors. 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.
# ==============================================================================
"""Utilities common to CIFAR10 and CIFAR100 datasets."""
import _pickle as cPickle
def load_batch(fpath, label_key='labels'):
"""Internal utility for parsing CIFAR data.
Args:
fpath: path the file to parse.
label_key: key for label data in the retrieve
dictionary.
Returns:
A tuple `(data, labels)`.
"""
with open(fpath, 'rb') as f:
d = cPickle.load(f, encoding='bytes')
# decode utf8
d_decoded = {}
for k, v in d.items():
d_decoded[k.decode('utf8')] = v
d = d_decoded
data = d['data']
labels = d[label_key]
data = data.reshape(data.shape[0], 3, 32, 32)
return data, labels
Functions
def load_batch(fpath, label_key='labels')
-
Internal utility for parsing CIFAR data.
Args
fpath
- path the file to parse.
label_key
- key for label data in the retrieve dictionary.
Returns
A tuple
(data, labels)
.Expand source code
def load_batch(fpath, label_key='labels'): """Internal utility for parsing CIFAR data. Args: fpath: path the file to parse. label_key: key for label data in the retrieve dictionary. Returns: A tuple `(data, labels)`. """ with open(fpath, 'rb') as f: d = cPickle.load(f, encoding='bytes') # decode utf8 d_decoded = {} for k, v in d.items(): d_decoded[k.decode('utf8')] = v d = d_decoded data = d['data'] labels = d[label_key] data = data.reshape(data.shape[0], 3, 32, 32) return data, labels