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:
  - |

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) {

}

}  // 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);

	}

	return framework.MaxNodeScore * (sumScores - minThreshold) / (maxThreshold - minThreshold)
}

// sumImageScores returns the sum of image scores of all the containers that are already on the node.
// Each image receives a raw score of its size, scaled by scaledImageScore. The raw scores are later used to calculate
// the final score.
func sumImageScores(nodeInfo *framework.NodeInfo, pod *v1.Pod, totalNumNodes int) int64 {
	var sum int64

func (c *sigctxt) cs() uint64      { return c.regs().sc_cs }
func (c *sigctxt) fs() uint64      { return c.regs().sc_fs }
func (c *sigctxt) gs() uint64      { return c.regs().sc_gs }
func (c *sigctxt) sigcode() uint64 { return uint64(c.info.si_code) }
func (c *sigctxt) sigaddr() uint64 {
	return *(*uint64)(add(unsafe.Pointer(c.info), 16))
}

}

// NormalizeScore invoked after scoring all nodes.
func (pl *TaintToleration) NormalizeScore(ctx context.Context, _ *framework.CycleState, pod *v1.Pod, scores framework.NodeScoreList) *framework.Status {
	return helper.DefaultNormalizeScore(framework.MaxNodeScore, true, scores)
}

// ScoreExtensions of the Score plugin.
func (pl *TaintToleration) ScoreExtensions() framework.ScoreExtensions {
	return pl
}