class_docstr: Stack the input data samples to construct the batch.
  
  The N input samples must have the same shape/length and will be stacked to construct a batch.
  
  Parameters
  ----------
  dtype : str or numpy.dtype, default None
      The value type of the output. If it is set to None, the input data type is used.
  
  Examples
  --------
  >>> import gluonnlp.data.batchify as bf
  >>> # Stack multiple lists
  >>> a = [1, 2, 3, 4]
  >>> b = [4, 5, 6, 8]
  >>> c = [8, 9, 1, 2]
  >>> bf.Stack()([a, b, c])
  <BLANKLINE>
  [[1 2 3 4]
   [4 5 6 8]
   [8 9 1 2]]
  <NDArray 3x4 @cpu_shared(0)>
  >>> # Stack multiple numpy.ndarrays
  >>> a = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
  >>> b = np.array([[5, 6, 7, 8], [1, 2, 3, 4]])
  >>> bf.Stack()([a, b])
  <BLANKLINE>
  [[[1 2 3 4]
    [5 6 7 8]]
  <BLANKLINE>
   [[5 6 7 8]
    [1 2 3 4]]]
  <NDArray 2x2x4 @cpu_shared(0)>
  >>> # Stack multiple NDArrays
  >>> a = mx.nd.array([[1, 2, 3, 4], [5, 6, 7, 8]])
  >>> b = mx.nd.array([[5, 6, 7, 8], [1, 2, 3, 4]])
  >>> bf.Stack()([a, b])
  <BLANKLINE>
  [[[1. 2. 3. 4.]
    [5. 6. 7. 8.]]
  <BLANKLINE>
   [[5. 6. 7. 8.]
    [1. 2. 3. 4.]]]
  <NDArray 2x2x4 @cpu_shared(0)>
docstr: Batchify the input data
  
  Parameters
  ----------
  data : list
      The input data samples
  
  Returns
  -------
  batch_data : NDArray
docstr_tok: ["Batchify","the","input","data","Parameters","--","--","--","--","--","data",":","list","The","input","data","samples","Returns","--","--","--","-","batch_data",":","NDArray"]
code: def __call__(self, data):
      """Batchify the input data
  
      Parameters
      ----------
      data : list
          The input data samples
  
      Returns
      -------
      batch_data : NDArray
      """
      return _stack_arrs(data, False, self._dtype)
  
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 2 for calling the Stack obj's underlying member method code with example usage: obj.__call__(data) and returns: _stack_arrs