class_docstr: A dataset of Zalando's article images consisting of fashion products,
  a drop-in replacement of the original MNIST dataset from
  https://github.com/zalandoresearch/fashion-mnist
  
  Each sample is an image (in 3D NDArray) with shape (28, 28, 1).
  
  Parameters
  ----------
  root : str, default $MXNET_HOME/datasets/fashion-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: ["A","dataset","of","Zalando","'s","article","images","consisting","of","fashion","products",",","a","drop-in","replacement","of","the","original","MNIST","dataset","from","https",":","\/\/github.com\/zalandoresearch\/fashion-mnist","Each","sample","is","an","image","(","in","3D","NDArray",")","with","shape","(","28",",","28",",","1",")",".","Parameters","--","--","--","--","--","root",":","str",",","default","$","MXNET_HOME\/datasets\/fashion-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", "fashion-mnist"),
      train=True,
      transform=None,
  ):
      self._train = train
      self._train_data = (
          "train-images-idx3-ubyte.gz",
          "0cf37b0d40ed5169c6b3aba31069a9770ac9043d",
      )
      self._train_label = (
          "train-labels-idx1-ubyte.gz",
          "236021d52f1e40852b06a4c3008d8de8aef1e40b",
      )
      self._test_data = (
          "t10k-images-idx3-ubyte.gz",
          "626ed6a7c06dd17c0eec72fa3be1740f146a2863",
      )
      self._test_label = (
          "t10k-labels-idx1-ubyte.gz",
          "17f9ab60e7257a1620f4ad76bbbaf857c3920701",
      )
      self._namespace = "fashion-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 FashionMNIST object from inherited base classes: MNIST with example: obj = FashionMNIST(root, train, transform)