*       <ul>
   *         <li>UNSET, meaning "null pointer"
   *         <li>one plus an index into the entries and elements array
   *       </ul>
   *   <li>another java.util.Set delegate implementation. In most modern JDKs, normal java.util hash
   *       collections intelligently fall back to a binary search tree if hash table collisions are
   *       detected. Rather than going to all the trouble of reimplementing this ourselves, we

  /**
   * This neat test shows that no matter what weights we use in our requests, if we push X amount of
   * permits in a cool state, where X = rate * timeToCoolDown, and we have specified a
   * timeToWarmUp() period, it will cost as the prescribed amount of time. E.g., calling
   * [acquire(5), acquire(1)] takes exactly the same time as [acquire(2), acquire(3), acquire(1)].
   */
  public void testTimeToWarmUpIsHonouredEvenWithWeights() {

     * when hasNext() was called.
     */
    private @Nullable E nextItem;

    /**
     * Index of element returned by most recent call to next. Reset to -1 if this element is deleted
     * by a call to remove.
     */
    private int lastRet;

    Itr() {
      lastRet = -1;
      if (count == 0) nextIndex = -1;
      else {

  /**
   * This neat test shows that no matter what weights we use in our requests, if we push X amount of
   * permits in a cool state, where X = rate * timeToCoolDown, and we have specified a
   * timeToWarmUp() period, it will cost as the prescribed amount of time. E.g., calling
   * [acquire(5), acquire(1)] takes exactly the same time as [acquire(2), acquire(3), acquire(1)].
   */
  public void testTimeToWarmUpIsHonouredEvenWithWeights() {

  if (!status->status.ok()) {
    return 0;
  }
  return op_reg_data->op_def.is_stateful();
}

void TF_InitMain(const char* usage, int* argc, char*** argv) {
  tensorflow::port::InitMain(usage, argc, argv);
}

int TF_PickUnusedPortOrDie() {
  return tensorflow::internal::PickUnusedPortOrDie();
}

TFE_TensorHandle* TFE_NewTensorHandleFromScalar(TF_DataType data_type,

 *
 * <p>The extra bookkeeping done by cycle detecting locks comes at some cost to performance.
 * Benchmarks (as of December 2011) show that:
 *
 * <ul>
 *   <li>for an unnested {@code lock()} and {@code unlock()}, a cycle detecting lock takes 38ns as
 *       opposed to the 24ns taken by a plain lock.
 *   <li>for nested locking, the cost increases with the depth of the nesting:
 *       <ul>

* Flush conntrack state for removed/changed UDP Services ([#22573](https://github.com/kubernetes/kubernetes/pull/22573), [@freehan](https://github.com/freehan))
* Allow setting the Host header in a httpGet probe ([#24292](https://github.com/kubernetes/kubernetes/pull/24292), [@errm](https://github.com/errm))

// Iterate through the operations of a graph.  To use:
// size_t pos = 0;
// TF_Operation* oper;
// while ((oper = TF_GraphNextOperation(graph, &pos)) != nullptr) {
//   DoSomethingWithOperation(oper);
// }
TF_CAPI_EXPORT extern TF_Operation* TF_GraphNextOperation(TF_Graph* graph,
                                                          size_t* pos);

// Write out a serialized representation of `graph` (as a GraphDef protocol

## Changelog since v1.28.1

## Changes by Kind

### API Change

- Fixed a bug where CEL expressions in CRD validation rules would incorrectly compute a high estimated cost for functions that return strings, lists or maps.

					perc = math.Round(ls.Load15*100*100/float64(hm.CPU.CPUCount)) / 100
					updateResourceMetrics(cpuSubsystem, cpuLoad15Perc, perc, labels, false)
				}
			}
		}
		break // only one host expected
	}

	collectDriveMetrics(m)
}

func initLatestValues() {
	m := collectLocalMetrics(madmin.MetricsDisk, collectMetricsOpts{})
	latestDriveStatsMu.Lock()