*/
package org.apache.maven.repository;

import java.util.ArrayList;
import java.util.Collection;

/**
 * This is the main graph data structure used by the RepositorySystem to present tree and graph objects.
 *
 *
 */
@Deprecated
public class MetadataGraph {
    /** all graph nodes */
    Collection<MetadataGraphNode> nodes;

    /** entry point for tree-like structures */
    MetadataGraphNode entry;

   * 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.
   *

    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

 * limitations under the License.
 */

package com.google.common.graph;

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.util.Iterator;
import java.util.Set;
import org.jspecify.annotations.Nullable;

/**
 * An interface for representing and manipulating an origin node's adjacent nodes and edge values in
 * a {@link Graph}.
 *
 * @author James Sexton
 * @param <N> Node parameter type

// 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;

 * <i>For example:</i>
 * <pre>
 * restResources {
 *  restApi {
 *      includeXpack 'graph'
 *   }
 *   restTests {
 *     includeXpack 'graph'
 *   }
 * }
 * </pre>
 * Will copy any of the the x-pack tests that start with graph, and will copy the X-pack graph specification, as well as the full core
 * Rest API specification.
 * <p>

namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}
absl::Status GraphFunction::GetFunctionDef(const FunctionDef **fdef) {
  *fdef = &(func_record_->fdef());
  return absl::OkStatus();
}
}  // namespace graph
}  // namespace tracing

    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

    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

    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}. */