},
				},
			},
			needsUpdate: true,
		}, {
			name:         "no update needed but capacity and allocatable of existing node should be initialized",
			initialNode:  &v1.Node{},
			existingNode: &v1.Node{},
			expectedNode: &v1.Node{
				Status: v1.NodeStatus{
					Capacity:    v1.ResourceList{},
					Allocatable: v1.ResourceList{},
				},

			return
		}
		// Zero nonce, we only use each key once, and 32 bytes is plenty.
		nonce := make([]byte, stream.NonceSize())
		encw := stream.EncryptWriter(w, nonce, nil)
		defer encw.Close()

		// Initialize a zip writer which will provide a zipped content
		// of profiling data of all nodes
		inspectZipW = zip.NewWriter(encw)
		defer inspectZipW.Close()

		if b := getClusterMetaInfo(ctx); len(b) > 0 {

			// The tests assume that Get/GetList/Watch calls shouldn't fail.
			// However, 429 error can now be returned if watchcache is under initialization.
			// To avoid rewriting all tests, we wait for watchcache to initialize.
			if err := cacher.Wait(context.Background()); err != nil {
				t.Fatal(err)
			}
		}
		d := destroyFunc
		s = cacher
		destroyFunc = func() {
			cacher.Stop()
			d()
		}
	}

 public synchronized class DefaultArtifactTrans implements ArtifactTransformati, org.codehaus.plexus.personality.plexus.lifecycle.phase.Initializable { private java.util.List artifactTransformati; public void DefaultArtifactTrans(); public void initialize() throws org.codehaus.plexus.personality.plexus.lifecycle.phase.InitializationExcept; public void transformForResolve(org.apache.maven.artifact.Artifact, java.util.List, org.apache.maven.artifact.repository.ArtifactRepository) throws org.apache...

 public synchronized class DefaultArtifactTrans implements ArtifactTransformati, org.codehaus.plexus.personality.plexus.lifecycle.phase.Initializable { private java.util.List artifactTransformati; public void DefaultArtifactTrans(); public void initialize() throws org.codehaus.plexus.personality.plexus.lifecycle.phase.InitializationExcept; public void transformForResolve(org.apache.maven.artifact.Artifact, java.util.List, org.apache.maven.artifact.repository.ArtifactRepository) throws org.apache...

java.util.Collection values(); public java.util.Set entrySet(); public java.util.Set keySet(); protected void sizeChanged(); private static int keyHash(Object); private void addEntry(Object, Object); private void removeEntry(FastMap$EntryImpl); private void initialize(int); private void readObject(java.io.ObjectInputStream) throws java.io.IOException, ClassNotFoundExcepti; private void writeObject(java.io.ObjectOutputStream) throws java.io.IOException; } org/codehaus/plexus/util/FileUtils$FilterWrapper.class...

java.util.Collection values(); public java.util.Set entrySet(); public java.util.Set keySet(); protected void sizeChanged(); private static int keyHash(Object); private void addEntry(Object, Object); private void removeEntry(FastMap$EntryImpl); private void initialize(int); private void readObject(java.io.ObjectInputStream) throws java.io.IOException, ClassNotFoundExcepti; private void writeObject(java.io.ObjectOutputStream) throws java.io.IOException; } org/codehaus/plexus/util/FileUtils$FilterWrapper.class...

	}
	return int64(score), nil
}

func (pl *numericMapPlugin) ScoreExtensions() framework.ScoreExtensions {
	return nil
}

// NewNoPodsFilterPlugin initializes a noPodsFilterPlugin and returns it.
func NewNoPodsFilterPlugin(_ context.Context, _ runtime.Object, _ framework.Handle) (framework.Plugin, error) {
	return &noPodsFilterPlugin{}, nil
}

arith::ConstantOp ExpandedShape(PatternRewriter& rewriter, Value input,
                                DenseIntElementsAttr broadcast_dimensions,
                                Value output) {
  // Initialize expanded shape with output rank and dimensions of 1.
  SmallVector<Attribute, 4> expanded_shape(
      mlir::cast<ShapedType>(output.getType()).getRank(),
      /*Value=*/rewriter.getI64IntegerAttr(1));

  (void)padding_is_valid;

  auto get_int = [](Attribute attr) {
    return mlir::cast<IntegerAttr>(attr).getInt();
  };

  // Output always have `num_dims` rank. All dimensions are initialized to
  // dynamic size and can be partially inferred.
  SmallVector<int64_t, 4> return_shape(num_dims, ShapedType::kDynamic);
  // Output batch and channel dimension can be obtained using utilities from