code: def _make_mirrored_indexed_slices(
      devices, values, indices, dense_shape
  ):
      values = [
          _make_indexed_slices(values, indices, dense_shape, d)
          for d in devices
      ]
      return distribute_utils.regroup(
          values, wrap_class=value_lib.Mirrored
      )
  
imports: import itertools
  import os
  import threading
  import time
  from absl.testing import parameterized
  import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.distribute import cluster_resolver
  from tensorflow.python.distribute import collective_all_reduce_strategy
  from tensorflow.python.distribute import collective_util
  from tensorflow.python.distribute import combinations
  from tensorflow.python.distribute import cross_device_ops
  from tensorflow.python.distribute import cross_device_utils
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import distribute_utils
  from tensorflow.python.distribute import multi_worker_test_base
  from tensorflow.python.distribute import multi_worker_util
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute import strategy_combinations
  from tensorflow.python.distribute import values
  from tensorflow.python.eager import context
  from tensorflow.python.eager import test
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import kernels
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import collective_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
label_desc: Use image node_id 5 for calling a global function with example usage: _make_mirrored_indexed_slices(devices, values, indices, dense_shape) and returns: distribute_utils