}

  @Override
  @Test
  public void edges_checkReturnedSetMutability() {
    assume().that(graphIsMutable()).isTrue();

    Set<String> edges = network.edges();
    UnsupportedOperationException e =
        assertThrows(UnsupportedOperationException.class, () -> edges.add(E12));
    addEdge(N1, N2, E12);
    assertThat(network.edges()).containsExactlyElementsIn(edges);
  }

  @Override
  @Test

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_ABSTRACT_TENSOR_HANDLE_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_TENSOR_HANDLE_H_

#include <memory>

#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"

      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);

 *   <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,
 * and forbids implementations or extensions with parallel edges. If you need parallel edges, use
 * {@link Network}. (You can use a positive {@code Integer} edge value as a loose representation of

      }
    };
  }

  @Override
  @CheckForNull
  public N removeInEdge(E edge, boolean isSelfLoop) {
    if (!isSelfLoop) {
      return removeOutEdge(edge);
    }
    return null;
  }

  @Override
  public N removeOutEdge(E edge) {
    N node = super.removeOutEdge(edge);
    Multiset<N> adjacentNodes = getReference(adjacentNodesReference);
    if (adjacentNodes != null) {

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_ABSTRACT_OP_ATTRS_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_OP_ATTRS_H_

#include "absl/container/inlined_vector.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/types.pb.h"

  // Ideally, the ordering in test should never be updated.
  @Test
  public void stableIncidentEdgeOrder_edges_returnsInStableOrder() {
    assume().that(graph.incidentEdgeOrder().type()).isEqualTo(ElementOrder.Type.STABLE);

    populateStarShapedGraph();

    assertThat(graph.edges())
        .containsExactly(
            EndpointPair.ordered(2, 1),
            EndpointPair.ordered(1, 4),

        + nodes()
        + ", edges: "
        + edgeValueMap(this);
  }

  private static <N, V> Map<EndpointPair<N>, V> edgeValueMap(final ValueGraph<N, V> graph) {
    return Maps.asMap(
        graph.edges(),
        edge ->
            // requireNonNull is safe because the endpoint pair comes from the graph.
            requireNonNull(graph.edgeValueOrDefault(edge.nodeU(), edge.nodeV(), null)));
  }

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_ABSTRACT_OPERATION_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_OPERATION_H_

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/tensor_interface.h"
#include "tensorflow/core/framework/tensor_shape.h"

      return network.outEdges(node);
    }

    @Override
    public EndpointPair<N> incidentNodes(E edge) {
      return network.incidentNodes(edge);
    }

    @Override
    public Set<E> adjacentEdges(E edge) {
      return network.adjacentEdges(edge);
    }

    // _don't_ override edge*Connecting*; we want the behavior from AbstractNetwork
  }