TFE_OpReset(reused_op.get(), "Identity",
              "/job:localhost/replica:0/task:0/device:CPU:0", status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_EQ(tensorflow::string(TFE_OpGetDevice(reused_op.get(), status.get())),
            tensorflow::string("/job:localhost/replica:0/task:0/device:CPU:0"));
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
}

  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  const char task0_name[] = "/job:localhost/replica:0/task:0/device:CPU:0";
  const char task1_name[] = "/job:localhost/replica:0/task:1/device:CPU:0";
  const char task2_name[] = "/job:localhost/replica:0/task:2/device:CPU:0";

  // Create one variable per task.
  TFE_TensorHandle* h0 = TestVariable(ctx, 1.0, task1_name);

replication is configured, any incoming uploads and metadata changes to versions created on the target, will sync back to the source and be marked as `REPLICA` on the source. AWS, as well as MinIO do not by default sync metadata changes on a object version marked `REPLICA` back to source. This requires a setting in the replication configuration called [replica modification sync](https://aws.amazon.com/about-aws/whats-new/2020/12/amazon-s3-replication-adds-support-two-way-replication/).

For active-active...

  EXPECT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  const char* first_device = "/job:worker/replica:0/task:1/device:CPU:0";
  const char* second_device = "/job:worker/replica:0/task:2/device:CPU:0";
  const char* device_name = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  std::array<const char*, 2> underlying_devices{first_device, second_device};

	}

	opts, err := getOpts(ctx, rq, bucket, object)
	if err != nil {
		return mode, retainDate, legalHold, toAPIErrorCode(ctx, err)
	}

	replica := rq.Header.Get(xhttp.AmzBucketReplicationStatus) == replication.Replica.String()

	if opts.VersionID != "" && !replica {
		if objInfo, err := getObjectInfoFn(ctx, bucket, object, opts); err == nil {
			r := objectlock.GetObjectRetentionMeta(objInfo.UserDefined)

  optional StatefulSetPersistentVolumeClaimRetentionPolicy persistentVolumeClaimRetentionPolicy = 10;

  // ordinals controls the numbering of replica indices in a StatefulSet. The
  // default ordinals behavior assigns a "0" index to the first replica and
  // increments the index by one for each additional replica requested. Using
  // the ordinals field requires the StatefulSetStartOrdinal feature gate to be
  // enabled, which is beta.
  // +optional

// on each underlying device.
//
// For example if `device_name` is
//   "/job:localhost/replica:0/task:0/device:CUSTOM:0"
// and `underlying_devices` is
//   {"/job:localhost/replica:0/task:0/device:GPU:0",
//    "/job:localhost/replica:0/task:0/device:GPU:1"}
// Then executing an operation on CUSTOM:0 will execute it on GPU:0 and GPU:1.
//

## Replica Modification sync

		},
		expStatus: replication.Failed,
	},
	{ // 5. replication status for replica version
		name:      "replication status for replica version",
		rs:        ReplicationState{ReplicationStatusInternal: string(replication.Replica)},
		expStatus: replication.Replica,
	},
}

func TestCompositeReplicationStatus(t *testing.T) {
	for i, test := range replicationStateTest {

  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  const char remote_device_name[] =
      "/job:localhost/replica:0/task:1/device:CPU:0";
  const char local_device_name[] =
      "/job:localhost/replica:0/task:0/device:CPU:0";
  CheckRemoteMatMulExecutesOK(ctx, remote_device_name, local_device_name);

  TFE_Executor* executor = TFE_ContextGetExecutorForThread(ctx);