// Prioritize based on extender-implemented priority functions. The returned scores & weight
	// are used to compute the weighted score for an extender. The weighted scores are added to
	// the scores computed by Kubernetes scheduler. The total scores are used to do the host selection.
	Prioritize(pod *v1.Pod, nodes []*NodeInfo) (hostPriorities *extenderv1.HostPriorityList, weight int64, err error)

		return
	} else if err != nil {
		return
	}
	// Check that OOM scores were applied to the right processes.
	if len(appliedPids) != len(pidOOMs) {
		t.Errorf("Applied OOM scores to incorrect number of processes - %+v vs %v", appliedPids, pidOOMs)
		return
	}
	for _, pid := range appliedPids {
		if !pidOOMs[pid] {
			t.Errorf("Failed to apply OOM scores to process %d", pid)
		}
	}
}

apiVersion: release-notes/v2
kind: feature
area: network
issue:
  - 31779
releaseNotes:
  - |

	{i: 12, as: ASUB, a1: C_LOREG, a6: C_REG},
	{i: 12, as: ASUB, a1: C_LAUTO, a6: C_REG},
	{i: 4, as: AMULHD, a1: C_REG, a6: C_REG},
	{i: 4, as: AMULHD, a1: C_REG, a2: C_REG, a6: C_REG},
	{i: 62, as: AMLGR, a1: C_REG, a6: C_REG},
	{i: 2, as: ADIVW, a1: C_REG, a2: C_REG, a6: C_REG},
	{i: 2, as: ADIVW, a1: C_REG, a6: C_REG},
	{i: 10, as: ASUB, a1: C_REG, a2: C_REG, a6: C_REG},
	{i: 10, as: ASUB, a1: C_REG, a6: C_REG},

static constexpr char kClassifyMethodName[] = "tensorflow/serving/classify";

/// Classification classes output.
static constexpr char kClassifyOutputClasses[] = "classes";

/// Classification scores output.
static constexpr char kClassifyOutputScores[] = "scores";

////////////////////////////////////////////////////////////////////////////////
/// Predict API constants.

/// Predict inputs.
static constexpr char kPredictInputs[] = "inputs";

	_EVFILT_WRITE = -0x2
)

type tforkt struct {
	tf_tcb   unsafe.Pointer
	tf_tid   *int32
	tf_stack uintptr
}

type sigcontext struct {
	sc_cookie uint64
	sc_mask   int32
	sc_reg    [32]uint64
	sc_lr     uint64
	sc_cr     uint64
	sc_xer    uint64
	sc_ctr    uint64
	sc_pc     uint64
	sc_ps     uint64
	sc_vrsave uint64
	pad_cgo_0 [8]byte
	sc_vsx    [64][16]uint8

See the License for the specific language governing permissions and
limitations under the License.
*/

package oom

import (
	"errors"
)

var unsupportedErr = errors.New("setting OOM scores is unsupported in this build")

func NewOOMAdjuster() *OOMAdjuster {
	return &OOMAdjuster{
		ApplyOOMScoreAdj:          unsupportedApplyOOMScoreAdj,
		ApplyOOMScoreAdjContainer: unsupportedApplyOOMScoreAdjContainer,
	}

                resultBuf.append(b.getClass().getSimpleName()).append(" : ").append(count).append('\n');
            } catch (final Exception e) {
                logger.warn("Failed to update scores.", e);
                resultBuf.append(e.getMessage()).append('\n');
            }
        });
        return resultBuf.toString();
    }

    protected void addScoreBooster(final ScoreBooster scoreBooster) {

// which return a score for each node from the call to RunScorePlugins().
// The scores from each plugin are added together to make the score for that node, then
// any extenders are run as well.
// All scores are finally combined (added) to get the total weighted scores of all nodes
func prioritizeNodes(
	ctx context.Context,
	extenders []framework.Extender,
	fwk framework.Framework,

}

}  // namespace

void ConvertNMSPaddedFunc::RewriteFunc() {
  func_->setAttr(kTFImplements,
                 StringAttr::get(func_.getContext(), kTfNMSPadded));
  Value boxes = func_.getArgument(0);
  Value scores = func_.getArgument(1);
  Value max_output_size = func_.getArgument(2);
  Value iou_threshold = func_.getArgument(3);
  Value score_threshold = func_.getArgument(4);
  auto output_type0 = func_.getFunctionType().getResult(0);