ArrayList<Object> edgeList = new ArrayList<>(network.edges());

      assertThat(network.nodes()).hasSize(NUM_NODES);
      assertThat(network.edges()).hasSize(NUM_EDGES);
      AbstractNetworkTest.validateNetwork(network);

      Collections.shuffle(edgeList, gen);
      int numEdgesToRemove = gen.nextInt(NUM_EDGES);
      for (int i = 0; i < numEdgesToRemove; ++i) {
        Object edge = edgeList.get(i);

                "wrong # of v2 incident edges in the resulting graph after resolver");
        assertEquals(
                "1.2",
                res.getIncidentEdges(v2).get(0).getVersion(),
                "wrong edge v1-v2 in the resulting graph after resolver");

        assertEquals(
                1, res.getIncidentEdges(v3).size(), "wrong # of edges v1-v3 in the resulting graph after resolver");

    discussion_edges = get_graphql_question_discussion_edges(settings=settings)

    while discussion_edges:
        for discussion_edge in discussion_edges:
            discussion_nodes.append(discussion_edge.node)
        last_edge = discussion_edges[-1]
        discussion_edges = get_graphql_question_discussion_edges(
            settings=settings, after=last_edge.cursor
        )
    return discussion_nodes

    for (N node : graph.nodes()) {
      copy.addNode(node);
    }
    for (EndpointPair<N> edge : graph.edges()) {
      copy.putEdge(edge.nodeU(), edge.nodeV());
    }
    return copy;
  }

  /** Creates a mutable copy of {@code graph} with the same nodes, edges, and edge values. */
  public static <N, V> MutableValueGraph<N, V> copyOf(ValueGraph<N, V> graph) {
    MutableValueGraph<N, V> copy =

        return AbstractNetwork.this.nodes();
      }

      @Override
      public Set<EndpointPair<N>> edges() {
        if (allowsParallelEdges()) {
          return super.edges(); // Defer to AbstractGraph implementation.
        }

        // Optimized implementation assumes no parallel edges (1:1 edge to EndpointPair mapping).
        return new AbstractSet<EndpointPair<N>>() {
          @Override

      ArrayList<Object> edgeList = new ArrayList<>(network.edges());

      assertThat(network.nodes()).hasSize(NUM_NODES);
      assertThat(network.edges()).hasSize(NUM_EDGES);
      AbstractNetworkTest.validateNetwork(network);

      Collections.shuffle(edgeList, gen);
      int numEdgesToRemove = gen.nextInt(NUM_EDGES);
      for (int i = 0; i < numEdgesToRemove; ++i) {
        Object edge = edgeList.get(i);

        while (resultWithDoubleSelfLoop.hasNext()) {
          EndpointPair<N> edge = resultWithDoubleSelfLoop.next();
          if (edge.nodeU().equals(edge.nodeV())) {
            if (!alreadySeenSelfLoop.getAndSet(true)) {
              return edge;
            }
          } else {
            return edge;
          }
        }
        return endOfData();
      }
    };
  }

  mutex_lock l(graph->mu);
  std::vector<const tensorflow::Edge*> control_edges;
  for (const tensorflow::Edge* edge : op->node.in_edges()) {
    if (!edge->IsControlEdge()) continue;
    control_edges.push_back(edge);
  }
  for (const tensorflow::Edge* edge : control_edges) {
    graph->graph.RemoveControlEdge(edge);
  }
}

void TF_SetRequireShapeInferenceFns(TF_Graph* graph, bool require) {

    Graph<Integer> asGraph = graph.asGraph();
    AbstractGraphTest.validateGraph(asGraph);
    assertThat(graph.nodes()).isEqualTo(asGraph.nodes());
    assertThat(graph.edges()).isEqualTo(asGraph.edges());
    assertThat(graph.nodeOrder()).isEqualTo(asGraph.nodeOrder());
    assertThat(graph.incidentEdgeOrder()).isEqualTo(asGraph.incidentEdgeOrder());
    assertThat(graph.isDirected()).isEqualTo(asGraph.isDirected());

would never access <code>*p</code> or <code>*q</code>, but the rewritten program would.
And if the call contained synchronizing operations, then the original program
could establish happens before edges preceding the accesses
to <code>*p</code> and <code>*q</code>, but the rewritten program would not.
</p>

<p>
Not allowing a single read to observe multiple values means