code: def unpack(x, padding_value, no_mask_output=False, name=""):
      """
      This function unpacks the specified sequence operand 'x' along the most
      significant static axis [-1] and pads any gaps with the specified 'padding_value'.
      If the 'no_mask_output' argument is False, the returned Function has 2 outputs;
      viz. the unpacked non-sequence data and a mask denoting the gaps in the unpacked output
      due to differences across lengths of the sequences in the operand.
  
      Args:
          x: the sequence tensor (or its name) which is unpacked
          padding_value (np.float32 or np.float64 or np.float16): The value to pad gaps in the unpacked tensor with.
          no_mask_output (bool, optional): whether the Function has a mask tensor output denoting the
              gaps in the unpacked output due to differences across lengths of the sequences in the operand.
          name (str, optional): the name of the Function instance in the network
  
      Returns:
          :class:`~cntk.ops.functions.Function`
  
      Todo:
          add an example
      """
  
      from cntk.cntk_py import unpack
  
      x = sanitize_input(x)
      return unpack(x, padding_value, no_mask_output, name)
  
imports: import numpy
  from cntk.internal import typemap, sanitize_input
  from cntk.internal.utils import get_data_type
  from ...axis import Axis
  from ...default_options import default_override_or
label_desc: Use image node_id 3 for calling a global function with example usage: unpack(x, padding_value, no_mask_output, name) and returns: unpack