key = new Object();
    cache.refresh(key);
    checkNothingLogged();
    stats = cache.stats();
    assertThat(stats.missCount()).isEqualTo(2);
    assertThat(stats.loadSuccessCount()).isEqualTo(3);
    assertThat(stats.loadExceptionCount()).isEqualTo(0);
    assertThat(stats.hitCount()).isEqualTo(0);

    assertThat(cache.get(key)).isSameInstanceAs(key);
    stats = cache.stats();

		}, idx, *client.host)
	}
	return ng.Wait()
}

// BackgroundHealStatus - returns background heal status of all peers
func (sys *NotificationSys) BackgroundHealStatus(ctx context.Context) ([]madmin.BgHealState, []NotificationPeerErr) {
	ng := WithNPeers(len(sys.peerClients))
	states := make([]madmin.BgHealState, len(sys.peerClients))
	for idx, client := range sys.peerClients {
		client := client

type Metrics struct {
	LastReachableSecs, LastUnreachableSecs float64

	// Last whole minute stats
	TotalRequests, FailedRequests int64
	AvgSuccRTTMs                  float64
	MaxSuccRTTMs                  float64
}

// Metrics reports metrics related to plugin service reachability and stats for the last whole minute
func (o *AuthNPlugin) Metrics() Metrics {
	if o == nil {

xmlns="http://s3.amazonaws.com/doc/2006-03-01/"><Role></Role><Rule><Status>Enabled</Status><DeleteMarkerReplication><Status>Disabled</Status></DeleteMarkerReplication><DeleteReplication><Status>Disabled</Status></DeleteReplication><Prefix>key-prefix</Prefix><Destination><Bucket>arn:minio:replication:::destinationbucket</Bucket></Destination></Rule><Rule><Status>Enabled</Status><Priority>3</Priority><DeleteMarkerReplication><Status>Disabled</Status></DeleteMarkerReplication><DeleteReplication><Status>Disab...

}

void TF_TensorFromProto(const TF_Buffer* from, TF_Tensor* to,
                        TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  tensorflow::TensorProto from_tensor_proto;
  status->status = BufferToMessage(from, &from_tensor_proto);
  if (!status->status.ok()) {
    return;
  }
  status->status =
      tensorflow::down_cast<tensorflow::TensorInterface*>(to->tensor)
          ->FromProto(from_tensor_proto);

  status->status = c.construction_status();
  if (!status->status.ok()) return;

  if (op_reg_data->shape_inference_fn == nullptr) {
    status->status =
        InvalidArgument("No shape inference function exists for op '",
                        node_def.op(), "', did you forget to define it?");
    return;
  }

  status->status = c.Run(op_reg_data->shape_inference_fn);

xmlns="http://s3.amazonaws.com/doc/2006-03-01/"><Role>arn:aws:iam::AcctID:role/role-name</Role><Rule><Status>Enabled</Status><DeleteMarkerReplication><Status>Disabled</Status></DeleteMarkerReplication><DeleteReplication><Status>Disabled</Status></DeleteReplication><Prefix>key-prefix</Prefix><Destination><Bucket>arn:aws:s3:::destinationbucket</Bucket></Destination><SourceSelectionCriteria><ReplicaModifications><Status>Enabled</Status></ReplicaModifications></SourceSelectionCriteria></Rule></ReplicationConfiguration>`,...

  if (TF_GetCode(status) != TF_OK) return;
  if (!grad) return;

  status->status = g->graph.AddFunctionDef(grad->record->fdef(),
                                           grad->record->stack_traces());
  if (TF_GetCode(status) != TF_OK) return;

  tensorflow::GradientDef gdef;
  gdef.set_function_name(func->record->fdef().signature().name());
  gdef.set_gradient_func(grad->record->fdef().signature().name());

    key = new Object();
    cache.refresh(key);
    checkNothingLogged();
    stats = cache.stats();
    assertThat(stats.missCount()).isEqualTo(2);
    assertThat(stats.loadSuccessCount()).isEqualTo(3);
    assertThat(stats.loadExceptionCount()).isEqualTo(0);
    assertThat(stats.hitCount()).isEqualTo(0);

    assertThat(cache.get(key)).isSameInstanceAs(key);
    stats = cache.stats();

    TF_Status* out_status) const {
  absl::Status status;
  if (reader_ != nullptr) {
    status = reader_->GetTensor(name, out_tensor);
  } else {
    tensorflow::DataType dtype;
    tensorflow::TensorShape shape;
    status = v2_reader_->LookupDtypeAndShape(name, &dtype, &shape);
    if (status.ok()) {
      out_tensor->reset(new Tensor(dtype, shape));
      status = v2_reader_->Lookup(name, out_tensor->get());