class_docstr: An operand for a tflite hint function that is aggregated from many.
  
  For example, an LSTM is a grid of operators that are all related. Inputs
  going into them may need to be fused, so they should all be tracked as
  related arguments.
class_docstr_tok: ["An","operand","for","a","tflite","hint","function","that","is","aggregated","from","many",".","For","example",",","an","LSTM","is","a","grid","of","operators","that","are","all","related",".","Inputs","going","into","them","may","need","to","be","fused",",","so","they","should","all","be","tracked","as","related","arguments","."]
docstr: This adds to `out_graphdef` all the unaggregated outputs.
  
  I.e. we are outputting from a fused stub, but we need to make it compatible
  with the unfused original graph so we insert an unpack. Ideally in a later
  stage the unpack -> pack sequences will be removed.
  
  Args:
    fused_op_name: The name of the stub we are in the process of fusing.
    output_index: The output output_index this object represents.
    out_graphdef: The graphdef we are in the process of buildings
  
  Returns:
    The type of the aggregated output (so we can finish building the stub
    op).
code: def aggregate_and_return_name_for_output(
      self, fused_op_name, output_index, out_graphdef
  ):
      """This adds to `out_graphdef` all the unaggregated outputs.
  
      I.e. we are outputting from a fused stub, but we need to make it compatible
      with the unfused original graph so we insert an unpack. Ideally in a later
      stage the unpack -> pack sequences will be removed.
  
      Args:
        fused_op_name: The name of the stub we are in the process of fusing.
        output_index: The output output_index this object represents.
        out_graphdef: The graphdef we are in the process of buildings
  
      Returns:
        The type of the aggregated output (so we can finish building the stub
        op).
      """
      flattened = self.flatten_nodes()
      if (self.aggregation == OpHint.AGGREGATE_FIRST) or (
          self.aggregation == OpHint.AGGREGATE_LAST
      ):
          assert len(flattened) == 1
      if (
          len(flattened) == 1
          and self.aggregation != OpHint.AGGREGATE_STACK
      ):
          temp_op = _LiteSingleOperand(flattened[0])
          return temp_op.aggregate_and_return_name_for_output(
              fused_op_name, output_index, out_graphdef
          )
      else:
          stack_node = _node_def_pb2.NodeDef()
          stack_node.op = "Unpack"
          stack_node.name = "OpHintUnstack-%s" % flattened[0].name
          stack_node.attr["num"].i = len(flattened)
          output_type = flattened[0].attr["T"].type
          stack_node.attr["T"].type = output_type
          stack_node.input.append(
              _tensorflow_output_name(fused_op_name, output_index)
          )
          out_graphdef.node.extend([stack_node])
  
          for idx, discrete in enumerate(flattened):
              output_node = _copy.deepcopy(discrete)
              del output_node.input[:]
              output_node.input.append(
                  _tensorflow_output_name(stack_node.name, idx)
              )
              out_graphdef.node.extend([output_node])
  
          return output_type
  
imports: import collections
  import copy
  import json
  import uuid
  from tensorflow.core.framework import attr_value_pb2
  from tensorflow.core.framework import graph_pb2
  from tensorflow.core.framework import node_def_pb2
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.framework.graph_util_impl import _bfs_for_reachable_nodes
  from tensorflow.python.framework.graph_util_impl import _extract_graph_summary
  from tensorflow.python.ops import array_ops
  from tensorflow.python.util import compat
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.all_util import remove_undocumented
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 6 for calling the _LiteAggregateOperand obj's underlying member method code with example usage: obj.aggregate_and_return_name_for_output(fused_op_name, output_index, out_graphdef) and returns: temp_op, output_type