features: map[featuregate.Feature]bool{
				features.VolumeCapacityPriority: true,
			},
			args: config.VolumeBindingArgs{
				BindTimeoutSeconds: 10,
				Shape: []config.UtilizationShapePoint{
					{Utilization: -1, Score: 1},
					{Utilization: 10, Score: -1},
					{Utilization: 20, Score: 11},
					{Utilization: 101, Score: 1},
				},
			},

		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)
		}
	}
}

				Columns: []clause.Column{{Name: "age"}},
				Values:  [][]interface{}{{18}},
			},
		},
		{
			name: "Test convert float value",
			input: map[string]interface{}{
				"score": 99.5,
			},
			expect: clause.Values{
				Columns: []clause.Column{{Name: "score"}},
				Values:  [][]interface{}{{99.5}},
			},
		},
		{
			name: "Test convert bool value",
			input: map[string]interface{}{
				"active": true,
			},

			{Name: names.PodTopologySpread},
			{Name: names.InterPodAffinity},
			{Name: names.NodeResourcesBalancedAllocation},
		},
	},
	Score: config.PluginSet{
		Enabled: []config.Plugin{
			// Weight is tripled because:
			// - This is a score coming from user preference.
			// - Usage of node tainting to group nodes in the cluster is increasing becoming a use-case
			// for many user workloads

					}
				}
				score, status := p.(framework.ScorePlugin).Score(ctx, state, test.requestedPod, n.Name)
				if !status.IsSuccess() {
					t.Errorf("Score is expected to return success, but didn't. Got status: %v", status)
				}
				gotPriorities = append(gotPriorities, framework.NodeScore{Name: n.Name, Score: score})
			}

import org.apache.logging.log4j.Logger;
import org.codelibs.core.lang.StringUtil;
import org.codelibs.core.misc.Pair;
import org.codelibs.fess.mylasta.direction.FessConfig;
import org.codelibs.fess.util.ComponentUtil;

public class QueryFieldConfig {

    private static final Logger logger = LogManager.getLogger(QueryFieldConfig.class);

    public static final String SCORE_FIELD = "score";

  // CHECK-NEXT: %[[RESULT_0:.*]] = corert.get_op_handler %[[ARG_0:.*]] "cpu"
  %0 = corert.get_op_handler %arg0 "cpu"
  // CHECK-NEXT: %[[RESULT_1:.*]] = corert.get_op_handler %[[ARG_0]] "gpu"
  %1 = corert.get_op_handler %arg0 "gpu"
  // CHECK-NEXT: %[[RESULT_2:.*]] = corert.create_dense_tensor.i32 {shape = [0], value = []}
  %2 = corert.create_dense_tensor.i32 {shape = [0], value = []}

	defaultPlugins.PreScore = mergePluginSet(logger, defaultPlugins.PreScore, customPlugins.PreScore)
	defaultPlugins.Score = mergePluginSet(logger, defaultPlugins.Score, customPlugins.Score)
	defaultPlugins.Reserve = mergePluginSet(logger, defaultPlugins.Reserve, customPlugins.Reserve)
	defaultPlugins.Permit = mergePluginSet(logger, defaultPlugins.Permit, customPlugins.Permit)

// CHECK-SAME: ([[arg0:%.*]]: !corert.tensorhandle, [[arg1:%.*]]: !corert.tensorhandle)
func.func @test_const_tensor_canonicalization_mixed_operands(%arg0: !corert.tensorhandle, %arg1: !corert.tensorhandle) -> (!tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor) {
  %a = corert.const_dense_tensor dense<[true, false]> : tensor<2xi1>
  %b = corert.const_dense_tensor dense<[false, true]> : tensor<2xi1>

}

// RegisterScorePlugin returns a function to register a Score Plugin to a given registry.
func RegisterScorePlugin(pluginName string, pluginNewFunc runtime.PluginFactory, weight int32) RegisterPluginFunc {
	return RegisterPluginAsExtensionsWithWeight(pluginName, weight, pluginNewFunc, "Score")
}

// RegisterPreScorePlugin returns a function to register a Score Plugin to a given registry.