code: def _make_unstacked(cond, body, pfor_config):
      def _cond(*args):
          return math_ops.reduce_any(pfor_config.reduce_concat(args[0]))
  
      def _body(*args):
          not_done = args[0]
          args = args[1:]
          not_done = math_ops.logical_and(not_done, cond(*args))
          outputs = body(*args)
          return (not_done,) + tuple(
              array_ops.where_v2(not_done, x, y)
              for x, y in zip(outputs, args)
          )
  
      return _cond, _body
  
imports: from tensorflow.compiler.tf2xla.python import xla
  from tensorflow.python.compiler.xla import jit
  from tensorflow.python.compiler.xla import xla
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_v2_toggles
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.python.ops.parallel_for import control_flow_ops
  from tensorflow.python.ops.parallel_for.test_util import PForTestCase
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling a global function with example usage: _make_unstacked(cond, body, pfor_config) and returns: _cond,  _body, math_ops, unknown