* -------------------------------------------------------------------------
* This file is part of the IndexSDK project.
* Copyright (c) 2025 Huawei Technologies Co.,Ltd.
*
* IndexSDK is licensed under Mulan PSL v2.
* You can use this software according to the terms and conditions of the Mulan PSL v2.
* You may obtain a copy of Mulan PSL v2 at:
*
* http://license.coscl.org.cn/MulanPSL2
*
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND,
* EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT,
* MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE.
* See the Mulan PSL v2 for more details.
* -------------------------------------------------------------------------
*/
#include <faiss/ascend/AscendCloner.h>
#include <faiss/ascend/AscendIndexInt8Flat.h>
#include <faiss/index_io.h>
#include <gtest/gtest.h>
#include <sys/time.h>
#include <iostream>
#include <random>
namespace
{
using recallMap = std::unordered_map<int, float>;
const int RECMAP_KEY_1 = 1;
const int RECMAP_KEY_10 = 10;
const int RECMAP_KEY_100 = 100;
const int MILLI_SECOND = 1000;
inline double GetMillisecs()
{
struct timeval tv
{
0, 0
};
gettimeofday(&tv, nullptr);
return tv.tv_sec * 1e3 + tv.tv_usec * 1e-3;
}
inline void AssertInt8Equal(size_t count, const int8_t *gt, const int8_t *data)
{
for (size_t i = 0; i < count; i++)
{
ASSERT_TRUE(gt[i] == data[i]) << "i: " << i << " gt: " << int(gt[i]) << " data: " << int(data[i]) << std::endl;
}
}
inline void sqEncode(const faiss::ScalarQuantizer sq, const float *base, int8_t *baseInt8, const size_t n)
{
const int offset = 128;
std::vector<uint8_t> queryUint8(n * sq.code_size);
sq.compute_codes(base, queryUint8.data(), n);
for (size_t i = 0; i < n * sq.code_size; i++)
{
baseInt8[i] = queryUint8[i] - offset;
}
}
void computeRecall(recallMap &recMap, int j)
{
recMap[RECMAP_KEY_100]++;
switch (j)
{
case 0:
recMap[RECMAP_KEY_1]++;
recMap[RECMAP_KEY_10]++;
break;
case 1 ... 9:
recMap[RECMAP_KEY_10]++;
break;
default:
break;
}
}
template <class T>
recallMap calRecall(std::vector<T> label, int64_t *gt, int queryNum)
{
recallMap Map;
Map[RECMAP_KEY_1] = 0;
Map[RECMAP_KEY_10] = 0;
Map[RECMAP_KEY_100] = 0;
if (queryNum == 0)
{
std::cerr << "Error: Invalid queryNum value." << std::endl;
return Map;
}
int k = label.size() / queryNum;
for (int i = 0; i < queryNum; i++)
{
std::set<int> labelSet(label.begin() + i * k, label.begin() + i * k + k);
if (labelSet.size() != static_cast<size_t>(k))
{
printf("current query have duplicated labels!!! \n");
}
for (int j = 0; j < k; j++)
{
if (gt[i * k] == label[i * k + j])
{
computeRecall(Map, j);
break;
}
}
}
Map[RECMAP_KEY_1] = Map[RECMAP_KEY_1] / queryNum * 100;
Map[RECMAP_KEY_10] = Map[RECMAP_KEY_10] / queryNum * 100;
Map[RECMAP_KEY_100] =
Map[RECMAP_KEY_100] / queryNum * 100;
return Map;
}
TEST(TestAscendIndexInt8Flat, QPS)
{
int dim = 256;
size_t ntotal = 1000000;
std::vector<int> searchNum = {8, 16, 32, 64, 128, 256};
try
{
faiss::ascend::AscendIndexInt8FlatConfig conf({0}, 1024 * 1024 * 1024);
faiss::ascend::AscendIndexInt8Flat index(dim, faiss::METRIC_INNER_PRODUCT, conf);
index.verbose = true;
printf("start generate data\n");
std::vector<int8_t> base(ntotal * dim);
std::vector<float> baseFp(ntotal * dim);
for (size_t i = 0; i < ntotal * dim; i++)
{
baseFp[i] = drand48();
}
printf("generate data finished\n");
faiss::ScalarQuantizer sq = faiss::ScalarQuantizer(dim, faiss::ScalarQuantizer::QuantizerType::QT_8bit);
sq.train(ntotal, baseFp.data());
sqEncode(sq, baseFp.data(), base.data(), ntotal);
printf("add data\n");
index.add(ntotal, base.data());
int warmUpTimes = 10;
std::vector<float> distw(127 * 10, 0);
std::vector<faiss::idx_t> labelw(127 * 10, 0);
for (int i = 0; i < warmUpTimes; i++)
{
index.search(127, base.data(), 10, distw.data(), labelw.data());
}
for (size_t n = 0; n < searchNum.size(); n++)
{
int k = 100;
int loopTimes = 10;
std::vector<float> dist(searchNum[n] * k, 0);
std::vector<faiss::idx_t> label(searchNum[n] * k, 0);
double ts = GetMillisecs();
std::vector<int8_t> query(searchNum[n] * dim);
sqEncode(sq, baseFp.data(), query.data(), searchNum[n]);
for (int l = 0; l < loopTimes; l++)
{
index.search(searchNum[n], query.data(), k, dist.data(), label.data());
}
double te = GetMillisecs();
printf("case[%zu]: base:%zu, dim:%d, search num:%d, QPS:%.4f\n", n, ntotal, dim, searchNum[n],
MILLI_SECOND * searchNum[n] * loopTimes / (te - ts));
}
}
catch (std::exception &e)
{
printf("%s\n", e.what());
}
}
TEST(TestAscendIndexInt8Flat, Recall)
{
int dim = 256;
size_t ntotal = 1000000;
int searchNum = 8;
try
{
faiss::ascend::AscendIndexInt8FlatConfig conf({0}, 1024 * 1024 * 1024);
faiss::ascend::AscendIndexInt8Flat index(dim, faiss::METRIC_INNER_PRODUCT, conf);
index.verbose = true;
printf("start generate data\n");
std::vector<int8_t> base(ntotal * dim);
std::vector<float> baseFp(ntotal * dim);
for (size_t i = 0; i < ntotal * dim; i++)
{
baseFp[i] = drand48();
}
printf("generate data finished\n");
faiss::ScalarQuantizer sq = faiss::ScalarQuantizer(dim, faiss::ScalarQuantizer::QuantizerType::QT_8bit);
sq.train(ntotal, baseFp.data());
sqEncode(sq, baseFp.data(), base.data(), ntotal);
printf("add data\n");
index.add(ntotal, base.data());
int k = 100;
std::vector<faiss::idx_t> gt(searchNum * k, 0);
for (int i = 0; i < searchNum; i++)
{
gt[i * k] = i;
}
std::vector<float> dist(searchNum * k, 0);
std::vector<faiss::idx_t> label(searchNum * k, 0);
std::vector<int8_t> query(searchNum * dim);
sqEncode(sq, baseFp.data(), query.data(), searchNum);
index.search(searchNum, query.data(), k, dist.data(), label.data());
recallMap Top = calRecall(label, gt.data(), searchNum);
printf("TOPK %d: t1 = %.2f, t10 = %.2f, t100 = %.2f\n", k, Top[1], Top[10], Top[100]);
}
catch (std::exception &e)
{
printf("%s\n", e.what());
}
}
}
int main(int argc, char **argv)
{
testing::InitGoogleTest(&argc, argv);
return RUN_ALL_TESTS();
}