final N node;
  final BaseGraph<N> graph;

  IncidentEdgeSet(BaseGraph<N> graph, N node) {
    this.graph = graph;
    this.node = node;
  }

  @Override
  public boolean remove(@CheckForNull Object o) {
    throw new UnsupportedOperationException();
  }

  @Override
  public int size() {
    if (graph.isDirected()) {
      return graph.inDegree(node)
          + graph.outDegree(node)

    assertThat(graph.nodes()).containsExactly(N1, N5, N4, N2, N3).inOrder();
    assertThat(graph.adjacentNodes(N1)).containsExactly(N4, N5);
    assertThat(graph.adjacentNodes(N2)).containsExactly(N3);
    assertThat(graph.adjacentNodes(N3)).containsExactly(N2);
    assertThat(graph.adjacentNodes(N4)).containsExactly(N1);
    assertThat(graph.adjacentNodes(N5)).containsExactly(N1);
  }

  @Test

// A TF_ExecutionContext stores knowledge about how to execute an operation.
// E.g. it could know whether we're in eager mode or graph mode, keeps track
// of gradient tapes, etc.
typedef struct TF_ExecutionContext TF_ExecutionContext;

// A TF_AbstractTensor is an input to an operation. E.g. it could be a union
// type of eager and graph tensors. It is also the result of executing an
// operation.
typedef struct TF_AbstractTensor TF_AbstractTensor;

    assertThat(graph.incidentEdgeOrder()).isEqualTo(ElementOrder.stable());
  }

  @Test
  public void immutableGraphBuilder_addNode() {
    ImmutableGraph<String> graph = GraphBuilder.directed().<String>immutable().addNode("A").build();

    assertThat(graph.nodes()).containsExactly("A");
    assertThat(graph.edges()).isEmpty();
  }

  @Test
  public void immutableGraphBuilder_putEdgeFromNodes() {

    assertThat(graph.incidentEdgeOrder()).isEqualTo(ElementOrder.stable());
  }

  @Test
  public void immutableGraphBuilder_addNode() {
    ImmutableGraph<String> graph = GraphBuilder.directed().<String>immutable().addNode("A").build();

    assertThat(graph.nodes()).containsExactly("A");
    assertThat(graph.edges()).isEmpty();
  }

  @Test
  public void immutableGraphBuilder_putEdgeFromNodes() {

 *
 * <h3>Usage</h3>
 *
 * Given an algorithm, for example:
 *
 * <pre>{@code
 * public <N> someGraphAlgorithm(N startNode, PredecessorsFunction<N> predecessorsFunction);
 * }</pre>
 *
 * you will invoke it depending on the graph representation you're using.
 *
 * <p>If you have an instance of one of the primary {@code common.graph} types ({@link Graph},
 * {@link ValueGraph}, and {@link Network}):

 *
 * <h3>Usage</h3>
 *
 * Given an algorithm, for example:
 *
 * <pre>{@code
 * public <N> someGraphAlgorithm(N startNode, SuccessorsFunction<N> successorsFunction);
 * }</pre>
 *
 * you will invoke it depending on the graph representation you're using.
 *
 * <p>If you have an instance of one of the primary {@code common.graph} types ({@link Graph},
 * {@link ValueGraph}, and {@link Network}):

    assertThat(graph.nodeOrder().comparator()).isEqualTo(Ordering.natural());
    assertThat(graph.nodes()).containsExactly(node2, node4, node6, node8).inOrder();
  }

  private static void addNodes(MutableGraph<Integer> graph) {
    graph.addNode(3);
    graph.addNode(1);
    graph.addNode(4);
  }

  private static void addEdges(MutableNetwork<Integer, String> network) {
    network.addEdge(3, 1, "i");

      MutableGraph<Integer> graph = graphBuilder.allowsSelfLoops(true).build();

      assertThat(graph.nodes()).isEmpty();
      assertThat(graph.edges()).isEmpty();
      AbstractGraphTest.validateGraph(graph);

      while (graph.nodes().size() < NUM_NODES) {
        graph.addNode(gen.nextInt(NODE_POOL_SIZE));
      }
      ArrayList<Integer> nodeList = new ArrayList<>(graph.nodes());

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/refcount.h"
namespace tensorflow {
namespace tracing {
namespace graph {
using tensorflow::AbstractFunction;
// Thin wrapper around a FunctionDef.
class GraphFunction : public AbstractFunction {
 public:
  explicit GraphFunction(FunctionDef fdef);
  ~GraphFunction() override;