delegate().putAll(map);
  }

  @Override
  public Set<K> keySet() {
    return delegate().keySet();
  }

  @Override
  public Collection<V> values() {
    return delegate().values();
  }

  @Override
  public Set<Entry<K, V>> entrySet() {
    return delegate().entrySet();
  }

  @Override
  public boolean equals(@Nullable Object object) {

    do {
      int entryIndex = next - 1;
      int entry = entries[entryIndex];
      if (getHashPrefix(entry, mask) == hashPrefix
          && Objects.equals(key, keys[entryIndex])
          && (values == null || Objects.equals(value, values[entryIndex]))) {
        int newNext = getNext(entry, mask);
        if (lastEntryIndex == -1) {
          // we need to update the root link from table[]
          tableSet(table, tableIndex, newNext);

        setCreatedTime_PercentileRanks(values, null);
    }

    public void setCreatedTime_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setCreatedTime_PercentileRanks("createdTime", values, opLambda);
    }

    public void setCreatedTime_PercentileRanks(String name, double[] values,

	values := v.Values()
	defer v.Recycle()
	var prefix string
	if len(values[peerRESTListenPrefix]) > 1 {
		return grid.NewRemoteErrString("invalid request (peerRESTListenPrefix)")
	}
	globalAPIConfig.getRequestsPoolCapacity()
	if len(values[peerRESTListenPrefix]) == 1 {
		if err := event.ValidateFilterRuleValue(values[peerRESTListenPrefix][0]); err != nil {

		case maxCnt < count:
			maxCnt = count
			maxErr = err

		// Prefer `nil` over other error values with the same
		// number of occurrences.
		case maxCnt == count && err == nil:
			maxErr = err
		}
	}
	return maxCnt, maxErr
}

// reduceQuorumErrs behaves like reduceErrs by only for returning
// values of maximally occurring errors validated against a generic

        setCreatedTime_PercentileRanks(values, null);
    }

    public void setCreatedTime_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setCreatedTime_PercentileRanks("createdTime", values, opLambda);
    }

    public void setCreatedTime_PercentileRanks(String name, double[] values,

        setCreatedTime_PercentileRanks(values, null);
    }

    public void setCreatedTime_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setCreatedTime_PercentileRanks("createdTime", values, opLambda);
    }

    public void setCreatedTime_PercentileRanks(String name, double[] values,

                                                  int num_dims);

// Get a Matrix TensorHandle with given float values and dimensions
TFE_TensorHandle* TestTensorHandleWithDimsFloat(TFE_Context* ctx, float data[],
                                                int64_t dims[], int num_dims);

// Get a Matrix TensorHandle with given int values and dimensions
TFE_TensorHandle* TestTensorHandleWithDimsInt(TFE_Context* ctx, int data[],

        setCreatedTime_PercentileRanks(values, null);
    }

    public void setCreatedTime_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setCreatedTime_PercentileRanks("createdTime", values, opLambda);
    }

    public void setCreatedTime_PercentileRanks(String name, double[] values,

 * Utilities for benchmarks.
 *
 * <p>In many cases, we wish to vary the order of magnitude of the input as much as we want to vary
 * the input itself, so most methods which generate values use an exponential distribution varying
 * the order of magnitude of the generated values uniformly at random.
 *
 * @author Louis Wasserman
 */
@NullUnmarked
final class MathBenchmarking {
  static final int ARRAY_SIZE = 0x10000;