}

    private ClassMetaData getCurrentClass() {
        return classStack.peek();
    }

    private void visitExtendedTypes(NodeWithExtends<?> node) {
        ClassMetaData currentClass = getCurrentClass();
        for (ClassOrInterfaceType extendedType : node.getExtendedTypes()) {
            if (currentClass.isInterface()) {
                currentClass.addInterfaceName(extractName(extendedType));
            } else {

    private void processTreeNodes(MetadataGraphVertex parentVertex, MetadataTreeNode node, int depth, int pomOrder)
            throws MetadataResolutionException {
        if (node == null) {
            return;
        }

        MetadataGraphVertex vertex = new MetadataGraphVertex(node.md, versionedVertices, scopedVertices);
        vertices.add(vertex);

/**
 * Tests for {@code TreeTraverser}.
 *
 * @deprecated Use {@link com.google.common.graph.Traverser} instead.
 * @author Louis Wasserman
 */
@GwtCompatible
@NullMarked
@Deprecated // Use com.google.common.graph.Traverser instead.
public class TreeTraverserTest extends TestCase {
  private static class Node {
    final char value;

    Node(char value) {
      this.value = value;
    }
  }

   * <p>The valid values are:
   *
   * <ul>
   *   <li>{@code null} initial state, nothing has happened.
   *   <li>{@link Cancellation} terminal state, {@code cancel} was called.
   *   <li>{@link Failure} terminal state, {@code setException} was called.
   *   <li>{@link DelegatingToFuture} intermediate state, {@code setFuture} was called.
   *   <li>{@link #NULL} terminal state, {@code set(null)} was called.

MinIO in distributed mode lets you pool multiple drives (even on different machines) into a single object storage server. As drives are distributed across several nodes, distributed MinIO can withstand multiple node failures and yet ensure full data protection.

## Why distributed MinIO?

### Node Binaries

filename | sha512 hash
-------- | -----------
[kubernetes-node-linux-amd64.tar.gz](https://dl.k8s.io/v1.25.16/kubernetes-node-linux-amd64.tar.gz) | f120b00facb8a03b1e6b2a675878a673ba6faf278c5d8df5ec907b7674ed56cf6489a2d374d2d0603e4f31eccc5d9a452e965fa17ac410f48831264bc8195612

    }

    /**
     * Adds {@code node} if it is not already present.
     *
     * <p><b>Nodes must be unique</b>, just as {@code Map} keys must be. They must also be non-null.
     *
     * @return this {@code Builder} object
     */
    @CanIgnoreReturnValue
    public ImmutableValueGraph.Builder<N, V> addNode(N node) {
      mutableValueGraph.addNode(node);
      return this;
    }

    /**

	memTotalMD     = NewGaugeMD(memTotal, "Total memory on the node")
	memUsedMD      = NewGaugeMD(memUsed, "Used memory on the node")
	memUsedPercMD  = NewGaugeMD(memUsedPerc, "Used memory percentage on the node")
	memFreeMD      = NewGaugeMD(memFree, "Free memory on the node")
	memBuffersMD   = NewGaugeMD(memBuffers, "Buffers memory on the node")
	memCacheMD     = NewGaugeMD(memCache, "Cache memory on the node")

  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each
  // value records whether the graph has been mutated since the corresponding

      @Override
      public Set<N> adjacentNodes(N node) {
        return AbstractValueGraph.this.adjacentNodes(node);
      }

      @Override
      public Set<N> predecessors(N node) {
        return AbstractValueGraph.this.predecessors(node);
      }

      @Override
      public Set<N> successors(N node) {
        return AbstractValueGraph.this.successors(node);
      }

      @Override