class_docstr: CIFAR100 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html
  
  Each sample is an image (in 3D NDArray) with shape (32, 32, 3).
  
  Parameters
  ----------
  root : str, default $MXNET_HOME/datasets/cifar100
      Path to temp folder for storing data.
  fine_label : bool, default False
      Whether to load the fine-grained (100 classes) or coarse-grained (20 super-classes) labels.
  train : bool, default True
      Whether to load the training or testing set.
  transform : function, default None
      DEPRECATED FUNCTION ARGUMENTS.
      A user defined callback that transforms each sample. For example::
  
          transform=lambda data, label: (data.astype(np.float32)/255, label)
class_docstr_tok: ["CIFAR100","image","classification","dataset","from","https",":","\/\/www.cs.toronto.edu\/~kriz\/cifar.html","Each","sample","is","an","image","(","in","3D","NDArray",")","with","shape","(","32",",","32",",","3",")",".","Parameters","--","--","--","--","--","root",":","str",",","default","$","MXNET_HOME\/datasets\/cifar100","Path","to","temp","folder","for","storing","data",".","fine_label",":","bool",",","default","False","Whether","to","load","the","fine-grained","(","100","classes",")","or","coarse-grained","(","20","super-classes",")","labels",".","train",":","bool",",","default","True","Whether","to","load","the","training","or","testing","set",".","transform",":","function",",","default","None","DEPRECATED","FUNCTION","ARGUMENTS",".","A","user","defined","callback","that","transforms","each","sample",".","For","example",":",":","transform=lambda","data",",","label",":","(","data.astype","(","np.float32",")","\/255",",","label",")"]
code: def __init__(
      self,
      root=os.path.join(base.data_dir(), "datasets", "cifar100"),
      fine_label=False,
      train=True,
      transform=None,
  ):
      self._train = train
      self._archive_file = (
          "cifar-100-binary.tar.gz",
          "a0bb982c76b83111308126cc779a992fa506b90b",
      )
      self._train_data = [
          ("train.bin", "e207cd2e05b73b1393c74c7f5e7bea451d63e08e")
      ]
      self._test_data = [
          ("test.bin", "8fb6623e830365ff53cf14adec797474f5478006")
      ]
      self._fine_label = fine_label
      self._namespace = "cifar100"
      super(CIFAR10, self).__init__(root, transform)
  
imports: import os
  import gzip
  import tarfile
  import struct
  import warnings
  import numpy
  from ..None import dataset
  from ...utils import download, check_sha1, _get_repo_file_url
  from ....None import ndarray, image, recordio, base
  from ....None import numpy
  from ....util import is_np_array, default_array
  from ....base import numeric_types
label_desc: Use image node_id 1 to create a new CIFAR100 object from inherited base classes: CIFAR10 with example: obj = CIFAR100(root, fine_label, train, transform)