}

TF_Operation* Mul(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                  TF_Status* s, const char* name) {
  TF_Operation* op;
  BinaryOpHelper("Mul", l, r, graph, s, name, &op, "", true);
  return op;
}

TF_Operation* Add(TF_Output l, TF_Output r, TF_Graph* graph, TF_Status* s,
                  const char* name) {

    return new Unordered<>(nodeV, nodeU);
  }

  /** Returns an {@link EndpointPair} representing the endpoints of an edge in {@code graph}. */
  static <N> EndpointPair<N> of(Graph<?> graph, N nodeU, N nodeV) {
    return graph.isDirected() ? ordered(nodeU, nodeV) : unordered(nodeU, nodeV);
  }

  /** Returns an {@link EndpointPair} representing the endpoints of an edge in {@code network}. */

   * also connect {@code nodeV} to {@code nodeU}.
   *
   * <p>If this graph is directed, {@code edge} will be directed in this graph; if it is undirected,
   * {@code edge} will be undirected in this graph.
   *
   * <p>If this graph is directed, {@code endpoints} must be ordered.
   *
   * <p><b>{@code edge} must be unique to this graph</b>, just as a {@code Map} key must be. It must
   * also be non-null.
   *

// 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;

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.common.graph;

import static com.google.common.base.Preconditions.checkState;
import static com.google.common.graph.GraphConstants.INNER_CAPACITY;
import static com.google.common.graph.GraphConstants.INNER_LOAD_FACTOR;

import com.google.common.collect.HashMultiset;
import com.google.common.collect.ImmutableMap;

 */

package com.google.common.graph;

import static com.google.common.graph.TestUtil.EdgeType.DIRECTED;
import static com.google.common.graph.TestUtil.EdgeType.UNDIRECTED;
import static com.google.common.graph.TestUtil.assertNodeNotInGraphErrorMessage;
import static com.google.common.truth.Truth.assertThat;
import static org.junit.Assert.assertThrows;

import com.google.common.graph.TestUtil.EdgeType;
import java.util.Arrays;

    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.
  static bool classof(const AbstractFunction* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  core::RefCountPtr<FunctionRecord> func_record_;
};
}  // namespace graph
}  // namespace tracing
}  // namespace tensorflow

 *
 * {@snippet :
 * TreeTraverser<NodeType> traverser = TreeTraverser.using(node -> node.getChildNodes());
 * }
 *
 * @author Louis Wasserman
 * @since 15.0
 * @deprecated Use {@link com.google.common.graph.Traverser} instead. All instance methods have
 *     their equivalent on the result of {@code Traverser.forTree(tree)} where {@code tree}
 *     implements {@code SuccessorsFunction}, which has a similar API as {@link #children} or can be

 * overridden as desired.
 *
 * <p>Usage example:
 *
 * {@snippet :
 * CacheLoader<Key, Graph> loader = new CacheLoader<Key, Graph>() {
 *   public Graph load(Key key) throws AnyException {
 *     return createExpensiveGraph(key);
 *   }
 * };
 * LoadingCache<Key, Graph> cache = CacheBuilder.newBuilder().build(loader);
 * }
 *

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.common.graph;

import static com.google.common.base.Preconditions.checkNotNull;
import static com.google.common.base.Preconditions.checkState;
import static java.util.Objects.requireNonNull;

import java.util.Collections;