def distorted_inputs():
    'Construct distorted input for CIFAR training using the Reader ops.\n\n  Returns:\n    images: Images. 4D tensor of [batch_size, IMAGE_SIZE, IMAGE_SIZE, 3] size.\n    labels: Labels. 1D tensor of [batch_size] size.\n\n  Raises:\n    ValueError: If no data_dir\n  '
    if (not FLAGS.data_dir):
        raise ValueError('Please supply a data_dir')
    data_dir = os.path.join(FLAGS.data_dir, 'cifar-10-batches-bin')
    (images, labels) = cifar10_input.distorted_inputs(data_dir=data_dir, batch_size=FLAGS.batch_size)
    if FLAGS.use_fp16:
        images = tf.cast(images, tf.float16)
        labels = tf.cast(labels, tf.float16)
    return (images, labels)
Construct distorted input for CIFAR training using the Reader ops.

Returns:
  images: Images. 4D tensor of [batch_size, IMAGE_SIZE, IMAGE_SIZE, 3] size.
  labels: Labels. 1D tensor of [batch_size] size.

Raises:
  ValueError: If no data_dir
def distorted_inputs():
    'Construct distorted input for CIFAR training using the Reader ops.\n\n  Returns:\n    images: Images. 4D tensor of [batch_size, IMAGE_SIZE, IMAGE_SIZE, 3] size.\n    labels: Labels. 1D tensor of [batch_size] size.\n\n  Raises:\n    ValueError: If no data_dir\n  '
    if (not FLAGS.data_dir):
        raise ValueError('Please supply a data_dir')
    data_dir = os.path.join(FLAGS.data_dir, 'cifar-10-batches-bin')
    (images, labels) = cifar10_input.distorted_inputs(data_dir=data_dir, batch_size=FLAGS.batch_size)
    if FLAGS.use_fp16:
        images = tf.cast(images, tf.float16)
        labels = tf.cast(labels, tf.float16)
    return (images, labels)