class_docstr: Dataset of zipped image and label pairs.
  
  This dataset is zip version of :class:`LabeledImageDataset`. It
  takes a zipfile like :class:`ZippedImageDataset`. The label file
  shall contain lines like text file used in
  :class:`LabeledImageDataset`, but a filename in each line of the
  label file shall match with a file in the zip archive.
  
  Args:
      zipfilename (str): Path to a zipfile with images
      labelfilename (str): Path to a label file. ``i``-th line shall
          contain a filename and an integer label that corresponds
          to the ``i``-th sample. A filename in the label file shall
          match with a filename in the zip file given with
          `zipfilename`.
      dtype: Data type of resulting image arrays. ``chainer.config.dtype`` is
          used by default (see :ref:`configuration`).
      label_dtype: Data type of the labels.
code: def __init__(
      self,
      zipfilename,
      labelfilename,
      dtype=None,
      label_dtype=numpy.int32,
  ):
      _check_pillow_availability()
      pairs = []
      with open(labelfilename) as pairs_file:
          for i, line in enumerate(pairs_file):
              pair = line.strip().split()
              if len(pair) != 2:
                  raise ValueError(
                      "invalid format at line {} in file {}".format(
                          i, pairs_file
                      )
                  )
              pairs.append((pair[0], int(pair[1])))
      self._pairs = pairs
      self._label_dtype = label_dtype
      self._zipfile = ZippedImageDataset(zipfilename, dtype=dtype)
  
imports: import bisect
  import io
  import os
  import threading
  import zipfile
  import numpy
  import six
  import chainer
  from chainer.dataset import dataset_mixin
label_desc: Use image node_id 1 to create a new LabeledZippedImageDataset object from inherited base classes: dataset_mixin with example: obj = LabeledZippedImageDataset(zipfilename, labelfilename, dtype, label_dtype)