class_docstr: Loosely return list of the input data samples.
  There is no constraint of shape for any of the input samples, however, you will
  only be able to apply single batch operations since the output have different shapes.
  
  Examples
  --------
  >>> a = [1, 2, 3, 4]
  >>> b = [4, 5, 6]
  >>> c = [8, 2]
  >>> batchify.Append()([a, b, c])
  [
  [[1. 2. 3. 4.]]
  <NDArray 1x4 @cpu_shared(0)>,
  [[4. 5. 6.]]
  <NDArray 1x3 @cpu_shared(0)>,
  [[8. 2.]]
  <NDArray 1x2 @cpu_shared(0)>
  ]
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code: def __init__(self, expand=True, batch_axis=0):
      self._expand = expand
      self._batch_axis = batch_axis
  
imports: import logging
  import numpy
  import mxnet
label_desc: Use image node_id 1 to create a new Append object from inherited base classes: object with example: obj = Append(expand, batch_axis)