code: def tfvariable(_):
      x = variables.Variable([1000.0], name="x", shape=[1])
      old_x = x.value()
      with ops.control_dependencies([old_x]):
          new_x = x.assign_add([42.0])
      array_ops_stack.stack([old_x, new_x], name="result")
  
imports: import argparse
  import os
  import sys
  from absl import app
  import six
  from six.moves import range
  from tensorflow.core.protobuf import saver_pb2
  from tensorflow.python.client import session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import function
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_assert
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import control_flow_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.ops import variables
  from tensorflow.python.training import saver
label_desc: Use image node_id 13 for calling a global function with example usage: tfvariable(_) without return types