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123 lines
4.4 KiB
123 lines
4.4 KiB
using System;
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using System.Collections.Generic;
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using System.Diagnostics;
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using System.Linq;
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using System.Threading;
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using ZeroLevel.HNSW;
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namespace HNSWDemo
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{
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class Program
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{
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public enum Gender
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{
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Unknown, Male, Feemale
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}
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public class Person
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{
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public Gender Gender { get; set; }
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public int Age { get; set; }
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public long Number { get; set; }
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private static (float[], Person) Generate(int vector_size)
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{
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var rnd = new Random((int)Environment.TickCount);
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var vector = new float[vector_size];
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DefaultRandomGenerator.Instance.NextFloats(vector);
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VectorUtils.NormalizeSIMD(vector);
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var p = new Person();
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p.Age = rnd.Next(15, 80);
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var gr = rnd.Next(0, 3);
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p.Gender = (gr == 0) ? Gender.Male : (gr == 1) ? Gender.Feemale : Gender.Unknown;
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p.Number = CreateNumber(rnd);
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return (vector, p);
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}
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public static List<(float[], Person)> GenerateRandom(int vectorSize, int vectorsCount)
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{
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var vectors = new List<(float[], Person)>();
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for (int i = 0; i < vectorsCount; i++)
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{
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vectors.Add(Generate(vectorSize));
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}
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return vectors;
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}
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static HashSet<long> _exists = new HashSet<long>();
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private static long CreateNumber(Random rnd)
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{
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long start_number;
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do
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{
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start_number = 79600000000L;
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start_number = start_number + rnd.Next(4, 8) * 10000000;
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start_number += rnd.Next(0, 1000000);
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}
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while (_exists.Add(start_number) == false);
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return start_number;
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}
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}
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private static List<float[]> RandomVectors(int vectorSize, int vectorsCount)
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{
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var vectors = new List<float[]>();
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for (int i = 0; i < vectorsCount; i++)
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{
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var vector = new float[vectorSize];
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DefaultRandomGenerator.Instance.NextFloats(vector);
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VectorUtils.NormalizeSIMD(vector);
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vectors.Add(vector);
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}
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return vectors;
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}
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private static Dictionary<int, Person> _database = new Dictionary<int, Person>();
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static void Main(string[] args)
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{
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var dimensionality = 128;
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var testCount = 1000;
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var count = 100000;
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var batchSize = 5000;
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var samples = Person.GenerateRandom(dimensionality, count);
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var sw = new Stopwatch();
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var world = new SmallWorld<float[]>(NSWOptions<float[]>.Create(6, 4, 120, 120, CosineDistance.ForUnits));
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for (int i = 0; i < (count / batchSize); i++)
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{
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var batch = samples.Skip(i * batchSize).Take(batchSize).ToArray();
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sw.Restart();
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var ids = world.AddItems(batch.Select(i => i.Item1).ToArray());
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sw.Stop();
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Console.WriteLine($"Batch [{i}]. Insert {ids.Length} items on {sw.ElapsedMilliseconds} ms");
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for (int bi = 0; bi < batch.Length; bi++)
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{
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_database.Add(ids[bi], batch[bi].Item2);
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}
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}
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var vectors = RandomVectors(dimensionality, testCount);
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//HNSWFilter filter = new HNSWFilter(ids => ids.Where(id => { var p = _database[id]; return p.Age > 45 && p.Gender == Gender.Feemale; }));
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/*var fackupCount = 0;
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foreach (var v in vectors)
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{
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var result = world.Search(v, 10, filter);
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foreach (var r in result)
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{
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if (_database[r.Item1].Age <= 45 || _database[r.Item1].Gender != Gender.Feemale)
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{
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Interlocked.Increment(ref fackupCount);
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}
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}
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}*/
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//Console.WriteLine($"Completed. Fackup count: {fackupCount}");
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Console.ReadKey();
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}
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}
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}
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