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