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/*
* Copyright (c) Meta Platforms, Inc. and affiliates.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <gtest/gtest.h>
#include <faiss/impl/FaissAssert.h>
#include <faiss/utils/hamming.h>
#include <random>
#include <cstdint>
using namespace ::testing;
template <typename T>
std::string print_data(
std::shared_ptr<std::vector<T>> data,
const size_t divider) {
std::string ret;
for (int i = 0; i < data->size(); ++i) {
if (i % divider) {
ret += " ";
} else {
ret += "|";
}
ret += std::to_string((*data)[i]);
}
ret += "|";
return ret;
}
std::stringstream get_correct_hamming_example(
const size_t na, // number of queries
const size_t nb, // number of candidates
const size_t k,
const size_t code_size,
std::shared_ptr<std::vector<uint8_t>> a,
std::shared_ptr<std::vector<uint8_t>> b,
std::shared_ptr<std::vector<int64_t>> true_ids,
// regular Hamming (bit-level distances)
std::shared_ptr<std::vector<int>> true_bit_distances,
// generalized Hamming (byte-level distances)
std::shared_ptr<std::vector<int>> true_byte_distances) {
assert(nb >= k);
// Initialization
std::default_random_engine rng(123);
std::uniform_int_distribution<int32_t> uniform(0, nb - 1);
const size_t nresults = na * k;
a->clear();
a->resize(na * code_size, 1); // query vectors are all 1
b->clear();
b->resize(nb * code_size, 2); // database vectors are all 2
true_ids->clear();
true_ids->reserve(nresults);
true_bit_distances->clear();
true_bit_distances->reserve(nresults);
true_byte_distances->clear();
true_byte_distances->reserve(nresults);
// define correct ids (must be unique)
std::set<int64_t> correct_ids;
do {
correct_ids.insert(uniform(rng));
} while (correct_ids.size() < k);
// replace database vector at id with vector more similar to query
// ordered, so earlier ids must be more similar
for (size_t nmatches = k; nmatches > 0; --nmatches) {
// get id and erase it
const auto id = *correct_ids.begin();
*correct_ids.erase(correct_ids.begin());
// assemble true id and distance at locations
true_ids->push_back(id);
true_bit_distances->push_back(
(code_size > nmatches ? code_size - nmatches : 0) *
/* per-code distance between 1 and 2 (0b01 and 0b10) */
2);
true_byte_distances->push_back(
(code_size > nmatches ? code_size - nmatches : 0));
for (size_t i = 0; i < nmatches; ++i) {
b->begin()[id * code_size + i] = 1; // query byte value
}
}
// true_ids, true_bit_distances, true_byte_distances only contain results
// for the first query.
// Query vectors are identical (all 1s), so copy the first sets of k
// distances na-1 times.
for (size_t i = 1; i < na; ++i) {
true_ids->insert(
true_ids->end(), true_ids->begin(), true_ids->begin() + k);
true_bit_distances->insert(
true_bit_distances->end(),
true_bit_distances->begin(),
true_bit_distances->begin() + k);
true_byte_distances->insert(
true_byte_distances->end(),
true_byte_distances->begin(),
true_byte_distances->begin() + k);
}
// assemble string for debugging
std::stringstream ret;
ret << "na: " << na << std::endl
<< "nb: " << nb << std::endl
<< "k: " << k << std::endl
<< "code_size: " << code_size << std::endl
<< "a: " << print_data(a, code_size) << std::endl
<< "b: " << print_data(b, code_size) << std::endl
<< "true_ids: " << print_data(true_ids, k) << std::endl
<< "true_bit_distances: " << print_data(true_bit_distances, k)
<< std::endl
<< "true_byte_distances: " << print_data(true_byte_distances, k)
<< std::endl;
return ret;
}
TEST(TestHamming, test_crosshamming_count_thres) {
if constexpr (sizeof(long) == 8) {
// Initialize randomizer
std::default_random_engine rng(123);
std::uniform_int_distribution<int32_t> uniform(0, 255);
// Initialize inputs
const size_t n = 10; // number of codes
const hamdis_t hamming_threshold = 20;
// one for each case - 65 is default
for (auto ncodes : {8, 16, 32, 64, 65}) {
// initialize inputs
const int nbits = ncodes * 8;
const size_t nwords = nbits / 64;
// 8 to for later conversion to uint64_t, and 2 for buffer
std::vector<uint8_t> dbs(nwords * n * 8 * 2);
for (int i = 0; i < dbs.size(); ++i) {
dbs[i] = uniform(rng);
}
// get true distance
size_t true_count = 0;
uint64_t* bs1 = (uint64_t*)dbs.data();
for (int i = 0; i < n; ++i) {
uint64_t* bs2 = bs1 + 2;
for (int j = i + 1; j < n; ++j) {
if (faiss::hamming(bs1 + i * nwords, bs2 + j * nwords, nwords) <
hamming_threshold) {
++true_count;
}
}
}
// run test and check correctness
size_t count;
if (ncodes == 65) {
ASSERT_THROW(
faiss::crosshamming_count_thres(
dbs.data(), n, hamming_threshold, ncodes, &count),
faiss::FaissException);
continue;
}
faiss::crosshamming_count_thres(
dbs.data(), n, hamming_threshold, ncodes, &count);
ASSERT_EQ(count, true_count) << "ncodes = " << ncodes;
}
}
}
TEST(TestHamming, test_hamming_thres) {
// Initialize randomizer
std::default_random_engine rng(123);
std::uniform_int_distribution<int32_t> uniform(0, 255);
// Initialize inputs
const size_t n1 = 10;
const size_t n2 = 15;
const hamdis_t hamming_threshold = 100;
// one for each case - 65 is default
for (auto ncodes : {8, 16, 32, 64, 65}) {
// initialize inputs
const int nbits = ncodes * 8;
const size_t nwords = nbits / 64;
std::vector<uint8_t> bs1(nwords * n1 * 8);
std::vector<uint8_t> bs2(nwords * n2 * 8);
for (int i = 0; i < bs1.size(); ++i) {
bs1[i] = uniform(rng);
}
for (int i = 0; i < bs2.size(); ++i) {
bs2[i] = uniform(rng);
}
// get true distance
size_t true_count = 0;
std::vector<int64_t> true_idx;
std::vector<hamdis_t> true_dis;
uint64_t* bs1_64 = (uint64_t*)bs1.data();
uint64_t* bs2_64 = (uint64_t*)bs2.data();
for (int i = 0; i < n1; ++i) {
for (int j = 0; j < n2; ++j) {
hamdis_t ham_dist = faiss::hamming(
bs1_64 + i * nwords, bs2_64 + j * nwords, nwords);
if (ham_dist < hamming_threshold) {
++true_count;
true_idx.push_back(i);
true_idx.push_back(j);
true_dis.push_back(ham_dist);
}
}
}
// run test and check correctness for both
// match_hamming_thres and hamming_count_thres
std::vector<int64_t> idx(true_idx.size());
std::vector<hamdis_t> dis(true_dis.size());
if (ncodes == 65) {
ASSERT_THROW(
faiss::match_hamming_thres(
bs1.data(),
bs2.data(),
n1,
n2,
hamming_threshold,
ncodes,
idx.data(),
dis.data()),
faiss::FaissException);
ASSERT_THROW(
faiss::hamming_count_thres(
bs1.data(),
bs2.data(),
n1,
n2,
hamming_threshold,
ncodes,
nullptr),
faiss::FaissException);
continue;
}
size_t match_count = faiss::match_hamming_thres(
bs1.data(),
bs2.data(),
n1,
n2,
hamming_threshold,
ncodes,
idx.data(),
dis.data());
size_t count_count;
faiss::hamming_count_thres(
bs1.data(),
bs2.data(),
n1,
n2,
hamming_threshold,
ncodes,
&count_count);
ASSERT_EQ(match_count, true_count) << "ncodes = " << ncodes;
ASSERT_EQ(count_count, true_count) << "ncodes = " << ncodes;
ASSERT_EQ(idx, true_idx) << "ncodes = " << ncodes;
ASSERT_EQ(dis, true_dis) << "ncodes = " << ncodes;
}
}
TEST(TestHamming, test_hamming_knn) {
if constexpr (sizeof(long) == 8) {
// Initialize randomizer
std::default_random_engine rng(123);
std::uniform_int_distribution<int32_t> uniform(0, 32);
// Initialize inputs
const size_t na = 4;
const size_t nb = 12; // number of candidates
const size_t k = 6;
auto a = std::make_shared<std::vector<uint8_t>>();
auto b = std::make_shared<std::vector<uint8_t>>();
auto true_ids = std::make_shared<std::vector<int64_t>>();
auto true_bit_distances = std::make_shared<std::vector<int>>();
auto true_byte_distances = std::make_shared<std::vector<int>>();
// 8, 16, 32 are cases - 24 will hit default case
// all should be multiples of 8
for (auto code_size : {8, 16, 24, 32}) {
// get example
std::stringstream assert_str = get_correct_hamming_example(
na,
nb,
k,
code_size,
a,
b,
true_ids,
true_bit_distances,
true_byte_distances);
// run test on generalized_hammings_knn_hc
std::vector<int64_t> ids_gen(na * k);
std::vector<int> dist_gen(na * k);
faiss::int_maxheap_array_t res = {
na, k, ids_gen.data(), dist_gen.data()};
faiss::generalized_hammings_knn_hc(
&res, a->data(), b->data(), nb, code_size, true);
ASSERT_EQ(ids_gen, *true_ids) << assert_str.str();
ASSERT_EQ(dist_gen, *true_byte_distances) << assert_str.str();
// run test on hammings_knn
std::vector<int64_t> ids_ham_knn(na * k, 0);
std::vector<int> dist_ham_knn(na * k, 0);
res = {na, k, ids_ham_knn.data(), dist_ham_knn.data()};
faiss::hammings_knn(&res, a->data(), b->data(), nb, code_size, true);
ASSERT_EQ(ids_ham_knn, *true_ids) << assert_str.str();
ASSERT_EQ(dist_ham_knn, *true_bit_distances) << assert_str.str();
}
for (auto code_size : {8, 16, 24, 32}) {
std::stringstream assert_str = get_correct_hamming_example(
na,
nb,
/* k */ nb, // faiss::hammings computes all distances
code_size,
a,
b,
true_ids,
true_bit_distances,
true_byte_distances);
std::vector<hamdis_t> dist_gen(na * nb);
faiss::hammings(
a->data(), b->data(), na, nb, code_size, dist_gen.data());
EXPECT_EQ(dist_gen, *true_bit_distances) << assert_str.str();
}
}
}
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