File size: 7,964 Bytes
569457d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 | // Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
#include "inc/Test.h"
#include "inc/Helper/SimpleIniReader.h"
#include "inc/Core/VectorIndex.h"
#include "inc/Core/MultiIndexScan.h"
#include "inc/Core/Common/CommonUtils.h"
#include <chrono>
#include <numeric>
#include <set>
std::vector<int> VID2rid;
// top number to query
int topk = 50;
//vector dimension
SPTAG::DimensionType m = 1024;
std::string pathEmbeddings = "/embeddings/";
std::string outputResult = "/result/";
std::vector<int> testSearchLimit = {256, 512, 1024};
struct FinalData{
double Dist;
int rid, vid;
FinalData(double x, int y, int z): Dist(x), rid(y), vid(z){}
bool operator < (const FinalData x) const {
return Dist < x.Dist;
}
};
static std::string indexName(unsigned int id){
return "testindices" + std::to_string(id);
}
template <typename T>
void BuildIndex(SPTAG::IndexAlgoType algo, std::string distCalcMethod, std::shared_ptr<SPTAG::VectorSet>& vec, std::shared_ptr<SPTAG::MetadataSet>& meta, const std::string out)
{
std::shared_ptr<SPTAG::VectorIndex> vecIndex = SPTAG::VectorIndex::CreateInstance(algo, SPTAG::GetEnumValueType<T>());
BOOST_CHECK(nullptr != vecIndex);
vecIndex->SetParameter("DistCalcMethod", distCalcMethod);
vecIndex->SetParameter("NumberOfThreads", "16");
BOOST_CHECK(SPTAG::ErrorCode::Success == vecIndex->BuildIndex(vec, meta));
BOOST_CHECK(SPTAG::ErrorCode::Success == vecIndex->SaveIndex(out));
}
float sumFunc(std::vector<float> in){
return std::accumulate(in.begin(), in.end(), (float)0.0);
}
template <typename T>
void GenerateVectorDataSet(SPTAG::IndexAlgoType algo, std::string distCalcMethod, unsigned int id, std::vector<T> &query, std::vector<T> &query_id, std::string File_name){
SPTAG::SizeType n = 0, q = 0;
std::string fileName;
fileName = pathEmbeddings + File_name + "_embeds_collection.tsv";
std::ifstream in1(fileName.c_str());
if (!in1)
{
std::cout << "Fail to read " << fileName << "." << std::endl;
return;
}
std::vector<T> vec;
std::string line;
std::vector<std::uint64_t> meta;
for (; getline(in1, line); n++)
{
std::uint64_t number = 0;
std::string a = line.substr(0, line.find("\t"));
for (size_t j = 0; j < a.length(); j++)
number = number * 10 + a[j] - '0';
VID2rid.push_back((int)number);
meta.push_back(number);
int l = (int)vec.size();
line.erase(0, line.find("[") + 1);
for (SPTAG::DimensionType j = 0; j < m - 1; j++) {
vec.push_back((T)std::stof(line.substr(0, line.find(","))));
line.erase(0, line.find(",") + 2);
}
vec.push_back((T)std::stof(line.substr(0, line.find("]"))));
//normalization;
int r = (int)vec.size();
double sum = 0.0;
for (int i = l; i < r; i++)
sum += vec[i] * vec[i];
sum = sqrt(sum);
for (int i = l; i < r; i++)
vec[i] = (T)(vec[i] / sum);
}
fileName = pathEmbeddings + File_name + "_embeds_query.tsv";
std::ifstream in2(fileName.c_str());
if (!in2)
{
std::cout << "Fail to read " << fileName << "." << std::endl;
return;
}
for (; getline(in2, line); q++)
{
query_id.push_back((T)std::stof(line.substr(0, line.find("\t"))));
int l = (int)query.size();
line.erase(0, line.find("[") + 1);
for (SPTAG::DimensionType j = 0; j < m - 1; j++) {
query.push_back((T)std::stof(line.substr(0, line.find(","))));
line.erase(0, line.find(",") + 2);
}
query.push_back((T)std::stof(line.substr(0, line.find("]"))));
//normalization;
int r = (int)query.size();
double sum = 0.0;
for (int i = l; i < r; i++)
sum += query[i] * query[i];
sum = sqrt(sum);
for (int i = l; i < r; i++)
query[i] = (T)(query[i] / sum);
}
std::shared_ptr<SPTAG::VectorSet> vecset(new SPTAG::BasicVectorSet(
SPTAG::ByteArray((std::uint8_t*)vec.data(), sizeof(T) * n * m, false),
SPTAG::GetEnumValueType<T>(), m, n));
std::shared_ptr<SPTAG::MetadataSet> metaset (new SPTAG::MemMetadataSet(
n * sizeof(std::uint64_t),
n * sizeof(std::uint64_t),
n));
for (auto x : meta){
std::uint8_t result[sizeof(x)];
std::memcpy(result, &x, sizeof(x));
metaset->Add(SPTAG::ByteArray(result, 8, false));
}
BuildIndex<T>(algo, distCalcMethod, vecset, metaset, indexName(id).c_str());
}
template <typename T>
void TestMultiIndexScanN(SPTAG::IndexAlgoType algo, std::string distCalcMethod, unsigned int n)
{
std::vector<std::vector<T>> queries(n, std::vector<T>());
std::vector<std::vector<T>> query_id(n, std::vector<T>());
GenerateVectorDataSet<T>(algo, distCalcMethod, 0, queries[0], query_id[0], "img");
GenerateVectorDataSet<T>(algo, distCalcMethod, 1, queries[1], query_id[1], "rec");
for (auto KK: testSearchLimit)
{
std::string output_result_path = outputResult + std::to_string(KK) + "_qrels.txt";
std::string output_lantency_path = outputResult + std::to_string(KK) + "_latency.txt";
std::ofstream out1;
out1.open(output_result_path);
if (!out1.is_open())
{
std::cout << "Cannot open file out1" << std::endl;
return ;
}
std::ofstream out2;
out2.open(output_lantency_path);
if (!out2.is_open())
{
std::cout << "Cannot open file out2" << std::endl;
return ;
}
for ( int i = 0; i < query_id[0].size(); i++ ){
std::vector<std::vector<T>> query_current(n, std::vector<T>());
for ( unsigned int j = 0; j < n ; j++ ){
for ( int k = i * m; k < i * m + m; k++ ){
query_current[j].push_back(queries[j][k]);
}
}
int idquery = (int)query_id[0][i];
std::vector<std::shared_ptr<SPTAG::VectorIndex>> vecIndices;
std::vector<void*> p_targets;
for ( unsigned int i = 0; i < n; i++ ) {
std::shared_ptr<SPTAG::VectorIndex> vecIndex;
BOOST_CHECK(SPTAG::ErrorCode::Success == SPTAG::VectorIndex::LoadIndex(indexName(i).c_str(), vecIndex));
BOOST_CHECK(nullptr != vecIndex);
vecIndices.push_back(vecIndex);
p_targets.push_back(query_current[i].data());
}
double Begin_time = clock();
SPTAG::MultiIndexScan scan(vecIndices, p_targets, topk, &sumFunc, false, 10000000, KK);
SPTAG::BasicResult result;
std::set<FinalData> FinalResult;
for (int i = 0; i < topk; i++) {
bool hasResult = scan.Next(result);
if (!hasResult) break;
FinalResult.insert(FinalData(result.Dist, VID2rid[result.VID], result.VID));
auto Finaltmp = FinalResult.end();
Finaltmp--;
if (FinalResult.size() > topk) FinalResult.erase(Finaltmp);
}
double End_time = clock();
out2 << idquery << "\t" << (End_time-Begin_time)/CLOCKS_PER_SEC << std::endl;
int Rank = 0;
for (auto i = FinalResult.begin(); i != FinalResult.end(); i++)
out1 << idquery << " " << i->rid << " " << ++Rank << " " << i->vid << " " << i->Dist << std::endl;
for (int i = (int)FinalResult.size(); i < topk; i++)
out1 << idquery << " " << -1 << " " << ++Rank << " " << -1 << " " << -1 << std::endl;
scan.Close();
}
}
}
BOOST_AUTO_TEST_SUITE(MultiIndexExperiment)
BOOST_AUTO_TEST_CASE(BKTTest)
{
TestMultiIndexScanN<float>(SPTAG::IndexAlgoType::BKT, "InnerProduct", 2);
}
BOOST_AUTO_TEST_SUITE_END()
|