class_docstr: Simply forward the list of input data.
  
  This is particularly useful when the Dataset contains textual data
  and in conjonction with the `Tuple` batchify function.
  
  Examples
  --------
  >>> import gluonnlp.data.batchify as bf
  >>> a = ([1, 2, 3, 4], "I am using MXNet")
  >>> b = ([5, 7, 2, 5], "Gluon rocks!")
  >>> c = ([1, 2, 3, 4], "Batchification!")
  >>> _, l = bf.Tuple(bf.Stack(), bf.List())([a, b, c])
  >>> l
  ['I am using MXNet', 'Gluon rocks!', 'Batchification!']
docstr: Parameters
  ----------
  data
      The list of samples
  
  Returns
  -------
  ret
      The input list
docstr_tok: ["Parameters","--","--","--","--","--","data","The","list","of","samples","Returns","--","--","--","-","ret","The","input","list"]
code: def __call__(self, data: t_List) -> t_List:
      """
      Parameters
      ----------
      data
          The list of samples
  
      Returns
      -------
      ret
          The input list
      """
      return list(data)
  
imports: import warnings
  import math
  from typing import Dict, Callable, NamedTuple, List, Tuple, AnyStr, Union
  import numpy
  import mxnet
  from mxnet.util import is_np_array
label_desc: Use image node_id 1 for calling the List obj's underlying member method code with example usage: obj.__call__(data) and returns: list