* properties remain intact, and further updates to {@code graph} will be reflected in the view.
   */
  public static <N> Graph<N> transpose(Graph<N> graph) {
    if (!graph.isDirected()) {
      return graph; // the transpose of an undirected graph is an identical graph
    }

    if (graph instanceof TransposedGraph) {
      return ((TransposedGraph<N>) graph).graph;

 * terms</a>):
 *
 * <ul>
 *   <li>directed graphs
 *   <li>undirected graphs
 *   <li>graphs that do/don't allow self-loops
 *   <li>graphs whose nodes/edges are insertion-ordered, sorted, or unordered
 *   <li>graphs whose edges have associated values
 * </ul>
 *
 * <p>{@code ValueGraph}, as a subtype of {@code Graph}, explicitly does not support parallel edges,

  @Nullable Integer expectedNodeCount = null;

  /**
   * Creates a new instance with the specified edge directionality.
   *
   * @param directed if true, creates an instance for graphs whose edges are each directed; if
   *     false, creates an instance for graphs whose edges are each undirected.
   */
  AbstractGraphBuilder(boolean directed) {
    this.directed = directed;
  }

   * Graph#adjacentNodes(Object)}, {@link Graph#predecessors(Object)}, {@link
   * Graph#successors(Object)} and {@link Graph#incidentEdges(Object)}.
   *
   * <p>The default value is {@link ElementOrder#unordered() unordered} for mutable graphs. For
   * immutable graphs, this value is ignored; they always have a {@link ElementOrder#stable()
   * stable} order.
   *

programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a

 *
 * <h3>Capabilities</h3>
 *
 * <p>{@code Graph} supports the following use cases (<a
 * href="https://github.com/google/guava/wiki/GraphsExplained#definitions">definitions of
 * terms</a>):
 *
 * <ul>
 *   <li>directed graphs
 *   <li>undirected graphs
 *   <li>graphs that do/don't allow self-loops

 *
 * {@snippet :
 * // Building a mutable value graph
 * MutableValueGraph<String, Double> graph =
 *     ValueGraphBuilder.undirected().allowsSelfLoops(true).build();
 * graph.putEdgeValue("San Francisco", "San Francisco", 0.0);
 * graph.putEdgeValue("San Jose", "San Jose", 0.0);
 * graph.putEdgeValue("San Francisco", "San Jose", 48.4);
 *
 * // Building an immutable value graph
 * ImmutableValueGraph<String, Double> immutableGraph =

  @SuppressWarnings("Immutable") // The backing graph must be immutable.
  private final BaseGraph<N> backingGraph;

  ImmutableGraph(BaseGraph<N> backingGraph) {
    this.backingGraph = backingGraph;
  }

  /** Returns an immutable copy of {@code graph}. */
  public static <N> ImmutableGraph<N> copyOf(Graph<N> graph) {
    return (graph instanceof ImmutableGraph)
        ? (ImmutableGraph<N>) graph
        : new ImmutableGraph<N>(

 */

package com.google.common.graph;

import static com.google.common.base.Preconditions.checkArgument;
import static com.google.common.base.Preconditions.checkNotNull;
import static com.google.common.base.Preconditions.checkState;
import static com.google.common.graph.GraphConstants.SELF_LOOPS_NOT_ALLOWED;
import static com.google.common.graph.Graphs.checkNonNegative;

  private ImmutableValueGraph(ValueGraph<N, V> graph) {
    super(ValueGraphBuilder.from(graph), getNodeConnections(graph), graph.edges().size());
  }

  /** Returns an immutable copy of {@code graph}. */
  public static <N, V> ImmutableValueGraph<N, V> copyOf(ValueGraph<N, V> graph) {
    return (graph instanceof ImmutableValueGraph)
        ? (ImmutableValueGraph<N, V>) graph
        : new ImmutableValueGraph<N, V>(graph);
  }