class_docstr: CIFAR10 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/cifar10
      Path to temp folder for storing data.
  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: ["CIFAR10","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\/cifar10","Path","to","temp","folder","for","storing","data",".","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", "cifar10"),
      train=True,
      transform=None,
  ):
      self._train = train
      self._archive_file = (
          "cifar-10-binary.tar.gz",
          "fab780a1e191a7eda0f345501ccd62d20f7ed891",
      )
      self._train_data = [
          (
              "data_batch_1.bin",
              "aadd24acce27caa71bf4b10992e9e7b2d74c2540",
          ),
          (
              "data_batch_2.bin",
              "c0ba65cce70568cd57b4e03e9ac8d2a5367c1795",
          ),
          (
              "data_batch_3.bin",
              "1dd00a74ab1d17a6e7d73e185b69dbf31242f295",
          ),
          (
              "data_batch_4.bin",
              "aab85764eb3584312d3c7f65fd2fd016e36a258e",
          ),
          (
              "data_batch_5.bin",
              "26e2849e66a845b7f1e4614ae70f4889ae604628",
          ),
      ]
      self._test_data = [
          ("test_batch.bin", "67eb016db431130d61cd03c7ad570b013799c88c")
      ]
      self._namespace = "cifar10"
      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 CIFAR10 object from inherited base classes: dataset with example: obj = CIFAR10(root, train, transform)