class_docstr: Load the ImageNet classification dataset.
  
  Refer to :doc:`../build/examples_datasets/imagenet` for the description of
  this dataset and how to prepare it.
  
  Parameters
  ----------
  root : str, default '~/.mxnet/datasets/imagenet'
      Path to the folder stored the dataset.
  train : bool, default True
      Whether to load the training or validation set.
  transform : function, default None
      A function that takes data and label and transforms them. Refer to
      :doc:`./transforms` for examples. (TODO, should we restrict its datatype
      to transformer?)
code: def __init__(
      self,
      root=path.join("~", ".mxnet", "datasets", "imagenet"),
      train=True,
      transform=None,
  ):
      split = "train" if train else "val"
      root = path.join(root, split)
      super(ImageNet, self).__init__(
          root=root, flag=1, transform=transform
      )
  
imports: from os import path
  from mxnet.gluon.data.vision import ImageFolderDataset
label_desc: Use image node_id 1 to create a new ImageNet object from inherited base classes: ImageFolderDataset with example: obj = ImageNet(root, train, transform)