public Builder<N> addNode(N node) {
      mutableGraph.addNode(node);
      return this;
    }

    /**
     * Adds an edge connecting {@code nodeU} to {@code nodeV} if one is not already present.
     *
     * <p>If the graph is directed, the resultant edge will be directed; otherwise, it will be
     * undirected.
     *

        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();
      }
    };
  }

    GraphBuilder<N1> castBuilder = cast();
    return new ImmutableGraph.Builder<>(castBuilder);
  }

  /**
   * Specifies whether the graph will allow self-loops (edges that connect a node to itself).
   * Attempting to add a self-loop to a graph that does not allow them will throw an {@link
   * UnsupportedOperationException}.
   *
   * <p>The default value is {@code false}.
   */

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

    populateTShapedGraph();

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

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

    populateTShapedGraph();

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

  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) {

    ValueGraphBuilder<N1, V1> castBuilder = cast();
    return new ImmutableValueGraph.Builder<>(castBuilder);
  }

  /**
   * Specifies whether the graph will allow self-loops (edges that connect a node to itself).
   * Attempting to add a self-loop to a graph that does not allow them will throw an {@link
   * UnsupportedOperationException}.
   *
   * <p>The default value is {@code false}.
   */

                    .build(Build.newBuilder().plugins(plugins).build())
                    .build();
            model.update(merger.merge(model.getDelegate(), lifecycleModel));
        }
    }

    /**
     *  The domain-specific model merger for lifecycle bindings
     */
    protected static class LifecycleBindingsMerger extends MavenModelMerger {

    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        "//tensorflow/c/eager:abstract_context",
        "//tensorflow/c/eager:abstract_operation",
        "//tensorflow/c/eager:abstract_tensor_handle",
        "//tensorflow/c/eager:c_api_unified_internal",
        "//tensorflow/c/eager:tracing_utils",
        "//tensorflow/core:framework",
        "//tensorflow/core/platform:errors",

#include "tensorflow/c/eager/gradients.h"

#include <memory>

#include "absl/container/flat_hash_set.h"
#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental.h"