code: def _tf_core_pack_sequence_as(
      structure, flat_sequence, expand_composites, sequence_fn=None
  ):
      """Implements sequence packing, with the option to alter the structure."""
      is_nested_fn = (
          _is_nested_or_composite
          if expand_composites
          else _tf_core_is_nested
      )
      sequence_fn = sequence_fn or sequence_like
  
      def truncate(value, length):
          value_str = str(value)
          return value_str[:length] + (value_str[length:] and "...")
  
      if not is_nested_fn(flat_sequence):
          raise TypeError(
              "Attempted to pack value:\n  {}\ninto a structure, but found "
              "incompatible type `{}` instead.".format(
                  truncate(flat_sequence, 100), type(flat_sequence)
              )
          )
  
      if not is_nested_fn(structure):
          if len(flat_sequence) != 1:
              raise ValueError(
                  "The target structure is of type `{}`\n  {}\nHowever the input "
                  "is a sequence ({}) of length {}.\n  {}\nnest cannot "
                  "guarantee that it is safe to map one to the other.".format(
                      type(structure),
                      truncate(structure, 100),
                      type(flat_sequence),
                      len(flat_sequence),
                      truncate(flat_sequence, 100),
                  )
              )
          return flat_sequence[0]
  
      try:
          final_index, packed = _tf_core_packed_nest_with_indices(
              structure, flat_sequence, 0, is_nested_fn, sequence_fn
          )
          if final_index < len(flat_sequence):
              raise IndexError
      except IndexError:
          flat_structure = _tf_core_flatten(
              structure, expand_composites=expand_composites
          )
          if len(flat_structure) != len(flat_sequence):
              # pylint: disable=raise-missing-from
              raise ValueError(
                  "Could not pack sequence. Structure had %d atoms, but "
                  "flat_sequence had %d items.  Structure: %s, flat_sequence: %s."
                  % (
                      len(flat_structure),
                      len(flat_sequence),
                      structure,
                      flat_sequence,
                  )
              )
      return sequence_fn(structure, packed)
  
imports: import collections
  import enum
  import wrapt
  from tensorflow.python import pywrap_tensorflow
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import _pywrap_utils
  from tensorflow.python.util.compat import collections_abc
  from tensorflow.python.util.custom_nest_protocol import CustomNestProtocol
label_desc: Use image node_id 20 for calling a global function with example usage: _tf_core_pack_sequence_as(structure, flat_sequence, expand_composites, sequence_fn) and returns: sequence_fn, unknown, flat_sequence