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using System;
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using System.Collections.Generic;
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using System.Linq;
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using ZeroLevel.Services.Serialization;
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namespace ZeroLevel.HNSW
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{
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/// <summary>
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/// NSW graph
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/// </summary>
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internal sealed class ReadOnlyLayer<TItem>
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: IBinarySerializable
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{
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private readonly ReadOnlyVectorSet<TItem> _vectors;
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private readonly ReadOnlyCompactBiDirectionalLinksSet _links;
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/// <summary>
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/// HNSW layer
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/// </summary>
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/// <param name="vectors">General vector set</param>
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internal ReadOnlyLayer(ReadOnlyVectorSet<TItem> vectors)
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{
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_vectors = vectors;
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_links = new ReadOnlyCompactBiDirectionalLinksSet();
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}
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#region Implementation of https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf
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/// <summary>
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/// Algorithm 2
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/// </summary>
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/// <param name="q">query element</param>
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/// <param name="ep">enter points ep</param>
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/// <returns>Output: ef closest neighbors to q</returns>
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internal void KNearestAtLayer(int entryPointId, Func<int, float> targetCosts, IDictionary<int, float> W, int ef)
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{
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/*
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* v ← ep // set of visited elements
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* C ← ep // set of candidates
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* W ← ep // dynamic list of found nearest neighbors
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* while │C│ > 0
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* c ← extract nearest element from C to q
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* f ← get furthest element from W to q
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* if distance(c, q) > distance(f, q)
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* break // all elements in W are evaluated
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* for each e ∈ neighbourhood(c) at layer lc // update C and W
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* if e ∉ v
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* v ← v ⋃ e
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* f ← get furthest element from W to q
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* if distance(e, q) < distance(f, q) or │W│ < ef
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* C ← C ⋃ e
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* W ← W ⋃ e
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* if │W│ > ef
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* remove furthest element from W to q
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* return W
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*/
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var v = new VisitedBitSet(_vectors.Count, 1);
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// v ← ep // set of visited elements
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v.Add(entryPointId);
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// C ← ep // set of candidates
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var C = new Dictionary<int, float>();
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C.Add(entryPointId, targetCosts(entryPointId));
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// W ← ep // dynamic list of found nearest neighbors
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W.Add(entryPointId, C[entryPointId]);
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var popCandidate = new Func<(int, float)>(() => { var pair = C.OrderBy(e => e.Value).First(); C.Remove(pair.Key); return (pair.Key, pair.Value); });
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var fartherFromResult = new Func<(int, float)>(() => { var pair = W.OrderByDescending(e => e.Value).First(); return (pair.Key, pair.Value); });
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var fartherPopFromResult = new Action(() => { var pair = W.OrderByDescending(e => e.Value).First(); W.Remove(pair.Key); });
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// run bfs
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while (C.Count > 0)
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{
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// get next candidate to check and expand
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var toExpand = popCandidate();
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var farthestResult = fartherFromResult();
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if (toExpand.Item2 > farthestResult.Item2)
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{
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// the closest candidate is farther than farthest result
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break;
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}
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// expand candidate
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var neighboursIds = GetNeighbors(toExpand.Item1).ToArray();
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for (int i = 0; i < neighboursIds.Length; ++i)
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{
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int neighbourId = neighboursIds[i];
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if (!v.Contains(neighbourId))
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{
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// enqueue perspective neighbours to expansion list
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farthestResult = fartherFromResult();
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var neighbourDistance = targetCosts(neighbourId);
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if (W.Count < ef || neighbourDistance < farthestResult.Item2)
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{
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C.Add(neighbourId, neighbourDistance);
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W.Add(neighbourId, neighbourDistance);
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if (W.Count > ef)
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{
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fartherPopFromResult();
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}
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}
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v.Add(neighbourId);
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}
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}
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}
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C.Clear();
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v.Clear();
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}
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/// <summary>
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/// Algorithm 2
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/// </summary>
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/// <param name="q">query element</param>
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/// <param name="ep">enter points ep</param>
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/// <returns>Output: ef closest neighbors to q</returns>
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internal void KNearestAtLayer(int entryPointId, Func<int, float> targetCosts, IDictionary<int, float> W, int ef, SearchContext context)
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{
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/*
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* v ← ep // set of visited elements
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* C ← ep // set of candidates
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* W ← ep // dynamic list of found nearest neighbors
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* while │C│ > 0
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* c ← extract nearest element from C to q
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* f ← get furthest element from W to q
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* if distance(c, q) > distance(f, q)
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* break // all elements in W are evaluated
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* for each e ∈ neighbourhood(c) at layer lc // update C and W
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* if e ∉ v
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* v ← v ⋃ e
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* f ← get furthest element from W to q
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* if distance(e, q) < distance(f, q) or │W│ < ef
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* C ← C ⋃ e
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* W ← W ⋃ e
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* if │W│ > ef
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* remove furthest element from W to q
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* return W
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*/
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var v = new VisitedBitSet(_vectors.Count, 1);
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// v ← ep // set of visited elements
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v.Add(entryPointId);
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// C ← ep // set of candidates
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var C = new Dictionary<int, float>();
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C.Add(entryPointId, targetCosts(entryPointId));
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// W ← ep // dynamic list of found nearest neighbors
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if (context.IsActiveNode(entryPointId))
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{
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W.Add(entryPointId, C[entryPointId]);
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}
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var popCandidate = new Func<(int, float)>(() => { var pair = C.OrderBy(e => e.Value).First(); C.Remove(pair.Key); return (pair.Key, pair.Value); });
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var farthestDistance = new Func<float>(() => { var pair = W.OrderByDescending(e => e.Value).First(); return pair.Value; });
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var fartherPopFromResult = new Action(() => { var pair = W.OrderByDescending(e => e.Value).First(); W.Remove(pair.Key); });
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// run bfs
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while (C.Count > 0)
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{
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// get next candidate to check and expand
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var toExpand = popCandidate();
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if (W.Count > 0)
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{
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if (toExpand.Item2 > farthestDistance())
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{
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// the closest candidate is farther than farthest result
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break;
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}
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}
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// expand candidate
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var neighboursIds = GetNeighbors(toExpand.Item1).ToArray();
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for (int i = 0; i < neighboursIds.Length; ++i)
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{
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int neighbourId = neighboursIds[i];
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if (!v.Contains(neighbourId))
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{
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// enqueue perspective neighbours to expansion list
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var neighbourDistance = targetCosts(neighbourId);
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if (context.IsActiveNode(neighbourId))
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{
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if (W.Count < ef || (W.Count > 0 && neighbourDistance < farthestDistance()))
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{
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W.Add(neighbourId, neighbourDistance);
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if (W.Count > ef)
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{
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fartherPopFromResult();
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}
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}
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}
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if (W.Count < ef)
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{
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C.Add(neighbourId, neighbourDistance);
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}
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v.Add(neighbourId);
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}
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}
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}
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C.Clear();
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v.Clear();
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}
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#endregion
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private IEnumerable<int> GetNeighbors(int id) => _links.FindLinksForId(id);
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public void Serialize(IBinaryWriter writer)
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{
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_links.Serialize(writer);
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}
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public void Deserialize(IBinaryReader reader)
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{
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_links.Deserialize(reader);
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}
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}
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}
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