"math/rand"
	"sync"
	"time"
)

func (er erasureObjects) getOnlineDisks() (newDisks []StorageAPI) {
	disks := er.getDisks()
	var wg sync.WaitGroup
	var mu sync.Mutex
	r := rand.New(rand.NewSource(time.Now().UnixNano()))
	for _, i := range r.Perm(len(disks)) {
		wg.Add(1)
		go func() {
			defer wg.Done()
			if disks[i] == nil {
				return
			}
			di, err := disks[i].DiskInfo(context.Background(), DiskInfoOptions{})

	var dialStart, dialEnd int64
	start := time.Now()
	trace := &httptrace.ClientTrace{
		GotFirstResponseByte: func() {
			atomic.AddUint64(&globalStats.tcpTimeForFirstByteTotalDur, uint64(time.Since(start)))
		},
		ConnectStart: func(network, addr string) {
			atomic.StoreInt64(&dialStart, time.Now().UnixNano())
		},
		ConnectDone: func(network, addr string, err error) {
			if err == nil {

    private final Object messagesLock = new Object();

    /**
     * Default constructor.
     */
    public ChatSession() {
        this.sessionId = UUID.randomUUID().toString();
        this.createdAt = LocalDateTime.now();
        this.lastAccessedAt = this.createdAt;
        this.messages = new CopyOnWriteArrayList<>();
    }

    /**
     * Creates a new chat session for the specified user.
     *
     * @param userId the user ID

	// Must be last:
	scannerMetricLast
)

// log scanner action.
// Use for s > scannerMetricStartTrace
func (p *scannerMetrics) log(s scannerMetric, paths ...string) func(custom map[string]string) {
	startTime := time.Now()
	return func(custom map[string]string) {
		duration := time.Since(startTime)

		atomic.AddUint64(&p.operations[s], 1)
		if s < scannerMetricLastRealtime {
			p.latency[s].add(duration)
		}

 *       returns {@code true}.
 *   <li>A class which implements {@code Comparable<UnrelatedType>} is very broken, and will cause
 *       undefined horrible things to happen in {@code Range}. For now, the Range API does not
 *       prevent its use, because this would also rule out all ungenerified (pre-JDK1.5) data types.
 *       <b>This may change in the future.</b>
 * </ul>
 *
 * <h3>Other notes</h3>
 *
 * <ul>

	}

	return nil
}

func TestCacheCtx(t *testing.T) {
	cache := New[time.Time]()
	t.Parallel()
	cache.InitOnce(2*time.Second, Opts{},
		func(ctx context.Context) (time.Time, error) {
			return time.Now(), slowCaller(ctx)
		},
	)

	ctx, cancel := context.WithCancel(t.Context())
	cancel() // cancel context to test.

	_, err := cache.GetWithCtx(ctx)
	if !errors.Is(err, context.Canceled) {

   * preferred assignment.)
   *
   * @since 8.0
   */
  public static final byte DC1 = 17; // aka XON

  /**
   * Transmission On: Although originally defined as DC1, this ASCII control character is now better
   * known as the XON code used for software flow control in serial communications. The main use is
   * restarting the transmission after the communication has been stopped by the XOFF control code.
   *
   * @since 8.0

	if msg != "" {
		message = fmt.Sprintf(msg, args...)
	} else {
		message = fmt.Sprint(args...)
	}
	logJSON, err := json.Marshal(&log.Entry{
		Level:   FatalKind,
		Message: message,
		Time:    time.Now().UTC(),
		Trace:   &log.Trace{Message: message, Source: []string{getSource(6)}},
	})
	if err != nil {
		panic(err)
	}
	fmt.Fprintln(Output, string(logJSON))
	ExitFunc(1)
}

				Level:   ErrorKind,
				Message: msg,
				Time:    time.Now().UTC(),
				Trace:   &log.Trace{Message: msg},
			})
		}
		if err := w.rotate(); err != nil {
			msg := fmt.Sprintf("unable to rotate log file %v: %v", w.f.Name(), err)
			stdErrEnc.Encode(&log.Entry{
				Level:   ErrorKind,
				Message: msg,
				Time:    time.Now().UTC(),
				Trace:   &log.Trace{Message: msg},
			})
		}
	}
}

  void Run(const std::vector<std::pair<TF_Operation*, TF_Tensor*>>& inputs,
           TF_Operation* output, int32_t expected_result) {
    Run(inputs, {{output, 0}}, {expected_result});
  }

  // Run the host graph, which now contains a function and check that
  // outputs are as expected.
  // 'T' stands for 'tensor' since the outputs are tensors, not scalars.
  void RunT(const std::vector<std::pair<TF_Operation*, TF_Tensor*>>& inputs,