* <p>Rate limiters are often used to restrict the rate at which some physical or logical resource
 * is accessed. This is in contrast to {@link java.util.concurrent.Semaphore} which restricts the
 * number of concurrent accesses instead of the rate (note though that concurrency and rate are
 * closely related, e.g. see <a href="http://en.wikipedia.org/wiki/Little%27s_law">Little's
 * Law</a>).
 *

 * <p>Rate limiters are often used to restrict the rate at which some physical or logical resource
 * is accessed. This is in contrast to {@link java.util.concurrent.Semaphore} which restricts the
 * number of concurrent accesses instead of the rate (note though that concurrency and rate are
 * closely related, e.g. see <a href="http://en.wikipedia.org/wiki/Little%27s_law">Little's
 * Law</a>).
 *

   * we change the rate.
   */
  public void testWeNeverGetABurstMoreThanOneSec() {
    RateLimiter limiter = RateLimiter.create(1.0, stopwatch);
    int[] rates = {1000, 1, 10, 1000000, 10, 1};
    for (int rate : rates) {
      int oneSecWorthOfWork = rate;
      stopwatch.sleepMillis(rate * 1000);
      limiter.setRate(rate);

   * we change the rate.
   */
  public void testWeNeverGetABurstMoreThanOneSec() {
    RateLimiter limiter = RateLimiter.create(1.0, stopwatch);
    int[] rates = {1000, 1, 10, 1000000, 10, 1};
    for (int rate : rates) {
      int oneSecWorthOfWork = rate;
      stopwatch.sleepMillis(rate * 1000);
      limiter.setRate(rate);

	BandWidthLimitInBytesPerSecond int64 `json:"limitInBits"`
	// current bandwidth reported
	CurrentBandwidthInBytesPerSecond float64 `json:"currentBandwidth"`
	// transfer rate for large uploads
	XferRateLrg *XferStats `json:"-" msg:"lt"`
	// transfer rate for small uploads
	XferRateSml *XferStats `json:"-" msg:"st"`

	// Deprecated fields
	// Pending size in bytes
	PendingSize int64 `json:"pendingReplicationSize"`

	rc, err := kube.DefaultRestConfig(kubeconfig, configContext, func(config *rest.Config) {
		// We are running a one-off command locally, so we don't need to worry too much about rate limiting
		// Bumping this up greatly decreases install time
		config.QPS = 50
		config.Burst = 100
		config.Impersonate = impersonateConfig
	})
	if err != nil {
		return nil, err
	}

potentially exploit a vulnerability in the TensorFlow code that handles videos,
which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

 * late. Also, all life cycle methods are executed with a lock held, so subclasses can safely modify
 * shared state without additional synchronization necessary for visibility to later executions of
 * the life cycle methods.
 *
 * <h3>Usage Example</h3>
 *
 * <p>Here is a sketch of a service which crawls a website and uses the scheduling capabilities to
 * rate limit itself.
 *
 * <pre>{@code

	// we allocate buffers rounded up to the closest size class.
	c := len(b) + n // ensure enough space for n elements
	if c < 2*cap(b) {
		// The growth rate has historically always been 2x. In the future,
		// we could rely purely on append to determine the growth rate.
		c = 2 * cap(b)
	}
	b2 := append([]byte(nil), make([]byte, c)...)
	i := copy(b2, b)
	return b2[:i]
}

	},
	ErrMalformedDate: {
		Code:           "MalformedDate",
		Description:    "Invalid date format header, expected to be in ISO8601, RFC1123 or RFC1123Z time format.",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrMalformedPresignedDate: {
		Code:           "AuthorizationQueryParametersError",
		Description:    "X-Amz-Date must be in the ISO8601 Long Format \"yyyyMMdd'T'HHmmss'Z'\"",
		HTTPStatusCode: http.StatusBadRequest,