code: def _make_per_replica(values, devices, regroup=False):
      devices = _get_devices(devices)
      assert len(values) == len(devices)
  
      # We simulate the result of regroup called on PerReplica which strips the
      # PerReplica wrapper if it has only one value.
      if len(values) == 1 and regroup:
          with ops.device(devices[0]):
              placed_v = array_ops.identity(values[0])
          return placed_v
  
      index = []
      for d, v in zip(devices, values):
          with ops.device(d):
              placed_v = array_ops.identity(v)
          index.append(placed_v)
      return distribute_utils.regroup(index)
  
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 2 for calling a global function with example usage: _make_per_replica(values, devices, regroup) and returns: distribute_utils, placed_v