// declaration "type T int", we construct edges T<-A and T<-B with
// weight 1; and because of instantiation "f[T, map[A]B]" we construct
// edges A<-T with weight 0, and B<-A and B<-B with weight 1.
//
// Finally, we look for any positive-weight cycles. Zero-weight cycles
// are allowed because static instantiation will reach a fixed point.

type monoGraph struct {
	vertices []monoVertex
	edges    []monoEdge

    const Graph* g, const string& outside_compilation_attr_name);

// Preprocesses edges within the same XLA cluster. It will perform the following
// operations in order:
//
// 0.  Remove edges from source node to outside compilation nodes, and edges
//     from outside compilation nodes to sink node.
// 1a. For edges between different outside compilation clusters, remove the edge

// of edges. An edge connects two nodes. Both nodes and edges must be
// comparable. This is an undirected simple graph.
type _Graph[_Node _NodeC[_Edge], _Edge _EdgeC[_Node]] struct {
	nodes []_Node
}

// _NodeC is the constraints on a node in a graph, given the _Edge type.
type _NodeC[_Edge any] interface {
	comparable
	Edges() []_Edge
}

@ElementTypesAreNonnullByDefault
abstract class AbstractBaseGraph<N> implements BaseGraph<N> {

  /**
   * Returns the number of edges in this graph; used to calculate the size of {@link Graph#edges()}.
   * This implementation requires O(|N|) time. Classes extending this one may manually keep track of
   * the number of edges as the graph is updated, and override this method for better performance.
   */
  protected long edgeCount() {

@ElementTypesAreNonnullByDefault
abstract class AbstractBaseGraph<N> implements BaseGraph<N> {

  /**
   * Returns the number of edges in this graph; used to calculate the size of {@link Graph#edges()}.
   * This implementation requires O(|N|) time. Classes extending this one may manually keep track of
   * the number of edges as the graph is updated, and override this method for better performance.
   */
  protected long edgeCount() {

	}
	return postProcessNamedEdgeMap(weight, totalWeight)
}

func sortByWeight(edges []NamedCallEdge, weight map[NamedCallEdge]int64) {
	sort.Slice(edges, func(i, j int) bool {
		ei, ej := edges[i], edges[j]
		if wi, wj := weight[ei], weight[ej]; wi != wj {
			return wi > wj // want larger weight first
		}
		// same weight, order by name/line number

	// TotalWeight is the aggregated edge weights across the profile. This
	// helps us determine the percentage threshold for hot/cold
	// partitioning.
	TotalWeight int64

	// NamedEdgeMap contains all unique call edges in the profile and their
	// edge weight.
	NamedEdgeMap NamedEdgeMap
}

// NamedCallEdge identifies a call edge by linker symbol names and call site
// offset.
type NamedCallEdge struct {
	CallerName     string

    }

    public HashCode getHash() {
        return hash;
    }

    /**
     * Were any edges in the include file graph unable to be resolved?
     */
    public boolean isHasUnresolved() {
        return hasUnresolved;
    }

    /**
     * The set of successfully resolved edges in the include file graph.
     */
    public ImmutableSet<IncludeFileEdge> getEdges() {
        return resolvedIncludes;

        override fun toString() = "ø"
    }

    data class Label(val label: String) : CompactTree() {
        override fun toString() = label
    }

    data class Branch(val edges: List<CompactTree>) : CompactTree() {
        override fun toString() = edges.joinToString(separator = ", ", prefix = "{", postfix = "}")
    }

    data class Edge(val label: Label, val tree: CompactTree) : CompactTree() {

		var b bytes.Buffer
		g.TransitiveReduction()
		// Add cyclic edges for visualization.
		for k := range cyclicRanks {
			g.AddEdge(k, k)
		}
		// Reverse the graph. It's much easier to read this as
		// a "<" partial order than a ">" partial order. This
		// ways, locks are acquired from the top going down
		// and time moves forward over the edges instead of
		// backward.
		g.Transpose()
		generateDot(&b, g)