class_docstr: MNIST handwritten digits dataset from http://yann.lecun.com/exdb/mnist
  
  Each sample is an image (in 3D NDArray) with shape (28, 28, 1).
  
  Parameters
  ----------
  root : str, default $MXNET_HOME/datasets/mnist
      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: ["MNIST","handwritten","digits","dataset","from","http",":","\/\/yann.lecun.com\/exdb\/mnist","Each","sample","is","an","image","(","in","3D","NDArray",")","with","shape","(","28",",","28",",","1",")",".","Parameters","--","--","--","--","--","root",":","str",",","default","$","MXNET_HOME\/datasets\/mnist","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", "mnist"),
      train=True,
      transform=None,
  ):
      self._train = train
      self._train_data = (
          "train-images-idx3-ubyte.gz",
          "6c95f4b05d2bf285e1bfb0e7960c31bd3b3f8a7d",
      )
      self._train_label = (
          "train-labels-idx1-ubyte.gz",
          "2a80914081dc54586dbdf242f9805a6b8d2a15fc",
      )
      self._test_data = (
          "t10k-images-idx3-ubyte.gz",
          "c3a25af1f52dad7f726cce8cacb138654b760d48",
      )
      self._test_label = (
          "t10k-labels-idx1-ubyte.gz",
          "763e7fa3757d93b0cdec073cef058b2004252c17",
      )
      self._namespace = "mnist"
      super(MNIST, 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 MNIST object from inherited base classes: dataset with example: obj = MNIST(root, train, transform)