milvus/internal/core/unittest/test_reduce.cpp

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// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software distributed under the License
// is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
// or implied. See the License for the specific language governing permissions and limitations under the License
#include <gtest/gtest.h>
#include "query/SubQueryResult.h"
#include <vector>
#include <queue>
#include <random>
using namespace milvus;
using namespace milvus::query;
TEST(Reduce, SubQueryResult) {
int64_t num_queries = 512;
int64_t topk = 32;
int64_t iteration = 50;
constexpr int64_t limit = 100000000L;
auto metric_type = MetricType::METRIC_L2;
using queue_type = std::priority_queue<int64_t>;
std::vector<queue_type> ref_results(num_queries);
for (auto& ref_result : ref_results) {
for (int i = 0; i < topk; ++i) {
ref_result.push(limit);
}
}
std::default_random_engine e(42);
SubQueryResult final_result(num_queries, topk, metric_type);
for (int i = 0; i < iteration; ++i) {
std::vector<int64_t> labels;
std::vector<float> values;
for (int n = 0; n < num_queries; ++n) {
for (int k = 0; k < topk; ++k) {
auto gen_x = e() % limit;
ref_results[n].push(gen_x);
ref_results[n].pop();
labels.push_back(gen_x);
values.push_back(gen_x);
}
std::sort(labels.begin() + n * topk, labels.begin() + n * topk + topk);
std::sort(values.begin() + n * topk, values.begin() + n * topk + topk);
}
SubQueryResult sub_result(num_queries, topk, metric_type);
sub_result.mutable_values() = values;
sub_result.mutable_labels() = labels;
final_result.merge(sub_result);
}
for (int n = 0; n < num_queries; ++n) {
ASSERT_EQ(ref_results[n].size(), topk);
for (int k = 0; k < topk; ++k) {
auto ref_x = ref_results[n].top();
ref_results[n].pop();
auto index = n * topk + topk - 1 - k;
auto label = final_result.get_labels()[index];
auto value = final_result.get_values()[index];
ASSERT_EQ(label, ref_x);
ASSERT_EQ(value, ref_x);
}
}
}
TEST(Reduce, SubQueryResultDesc) {
int64_t num_queries = 512;
int64_t topk = 32;
int64_t iteration = 50;
constexpr int64_t limit = 100000000L;
constexpr int64_t init_value = 0;
auto metric_type = MetricType::METRIC_INNER_PRODUCT;
using queue_type = std::priority_queue<int64_t, std::vector<int64_t>, std::greater<int64_t>>;
std::vector<queue_type> ref_results(num_queries);
for (auto& ref_result : ref_results) {
for (int i = 0; i < topk; ++i) {
ref_result.push(init_value);
}
}
std::default_random_engine e(42);
SubQueryResult final_result(num_queries, topk, metric_type);
for (int i = 0; i < iteration; ++i) {
std::vector<int64_t> labels;
std::vector<float> values;
for (int n = 0; n < num_queries; ++n) {
for (int k = 0; k < topk; ++k) {
auto gen_x = e() % limit;
ref_results[n].push(gen_x);
ref_results[n].pop();
labels.push_back(gen_x);
values.push_back(gen_x);
}
std::sort(labels.begin() + n * topk, labels.begin() + n * topk + topk, std::greater<int64_t>());
std::sort(values.begin() + n * topk, values.begin() + n * topk + topk, std::greater<float>());
}
SubQueryResult sub_result(num_queries, topk, metric_type);
sub_result.mutable_values() = values;
sub_result.mutable_labels() = labels;
final_result.merge(sub_result);
}
for (int n = 0; n < num_queries; ++n) {
ASSERT_EQ(ref_results[n].size(), topk);
for (int k = 0; k < topk; ++k) {
auto ref_x = ref_results[n].top();
ref_results[n].pop();
auto index = n * topk + topk - 1 - k;
auto label = final_result.get_labels()[index];
auto value = final_result.get_values()[index];
ASSERT_EQ(label, ref_x);
ASSERT_EQ(value, ref_x);
}
}
}