// -> ReadVariableOp1 and AssignVariableOp0 -> AssignVariableOp1 edges will be
// respected by XlaLaunchOp though because all reads happen before all writes
// with that limited clustering..
//
//
// NB!  The result computed by this analysis assumes that we don't auto-cluster
// back-edges (i.e. the edges from NextIteration to Merge).
//

// 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

        // If none of the incoming edges are transitive, remove previous state and do not traverse.
        // If not traversed before, simply add all selected outgoing edges (either hard or pending edges)
        // If traversed before:
        //      If net exclusions for this node have not changed, ignore
        //      If net exclusions for this node have changed, remove previous state and traverse outgoing edges again.

// 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

	// build it early since we rely heavily on the def-use chain later
	t.buildDefUses()

	// pick up either an edge or SSA value from worklist, process it
	for {
		if len(t.edges) > 0 {
			edge := t.edges[0]
			t.edges = t.edges[1:]
			if _, exist := t.visited[edge]; !exist {
				dest := edge.b
				destVisited := t.visitedBlock[dest.ID]

				// mark edge as visited
				t.visited[edge] = true

// 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
}

    )


def get_individual_sponsors(settings: Settings):
    nodes: List[SponsorshipAsMaintainerNode] = []
    edges = get_graphql_sponsor_edges(settings=settings)

    while edges:
        for edge in edges:
            nodes.append(edge.node)
        last_edge = edges[-1]
        edges = get_graphql_sponsor_edges(settings=settings, after=last_edge.cursor)

// enforce arbitrary ordering dependencies (via control or data edges) between
// resource operations.  Since all resource reads happen before all resource
// writes, edges constraining resource reads to happen before resource writes
// are fine, but all other kinds of edges are problematic.  This analysis
// computes the set of pairs of resource operations that cannot be put in the

            this.included = included;
            this.edges = edges;
            this.includeFileDirectives = dependentIncludeDirectives;
        }

        FileVisitResult(File file) {
            this.file = file;
            result = IncludeFileResolutionResult.NoMacroIncludes;
            includeDirectives = null;
            included = Collections.emptyList();
            edges = Collections.emptyList();