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157 lines
5.2 KiB
C++
157 lines
5.2 KiB
C++
// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements. See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership. The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License. You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include <faiss/IndexFlat.h>
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#include <gtest/gtest.h>
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#include <string>
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#include "utils/CommonUtil.h"
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#include "wrapper/utils.h"
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namespace {
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static const char* CONFIG_STR =
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"# All the following configurations are default values.\n"
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"\n"
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"server_config:\n"
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" address: 0.0.0.0 # milvus server ip address (IPv4)\n"
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" port: 19530 # port range: 1025 ~ 65534\n"
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" deploy_mode: single \n"
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" time_zone: UTC+8\n"
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"\n"
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"db_config:\n"
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" primary_path: /tmp/milvus # path used to store data and meta\n"
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" secondary_path: # path used to store data only, split by semicolon\n"
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"\n"
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" backend_url: sqlite://:@:/ # URI format: dialect://username:password@host:port/database\n"
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" \n"
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" # Replace 'dialect' with 'mysql' or 'sqlite'\n"
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"\n"
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" insert_buffer_size: 4 # GB, maximum insert buffer size allowed\n"
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"\n"
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"metric_config:\n"
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" enable_monitor: false # enable monitoring or not\n"
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" collector: prometheus # prometheus\n"
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" prometheus_config:\n"
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" port: 8080 # port prometheus used to fetch metrics\n"
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"\n"
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"cache_config:\n"
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" cpu_mem_capacity: 16 # GB, CPU memory used for cache\n"
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" cpu_mem_threshold: 0.85 # percentage of data kept when cache cleanup triggered\n"
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" cache_insert_data: false # whether load inserted data into cache\n"
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"\n"
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"engine_config:\n"
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" blas_threshold: 20\n"
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"\n"
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"resource_config:\n"
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#ifdef MILVUS_CPU_VERSION
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" search_resources:\n"
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" - cpu\n"
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" index_build_device: cpu # CPU used for building index";
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#else
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" search_resources:\n"
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" - cpu\n"
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" - gpu0\n"
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" index_build_device: gpu0 # GPU used for building index";
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#endif
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void
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WriteToFile(const std::string& file_path, const char* content) {
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std::fstream fs(file_path.c_str(), std::ios_base::out);
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// write data to file
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fs << content;
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fs.close();
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}
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} // namespace
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void
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KnowhereTest::SetUp() {
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std::string config_path(CONFIG_PATH);
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milvus::server::CommonUtil::CreateDirectory(config_path);
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WriteToFile(config_path + CONFIG_FILE, CONFIG_STR);
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}
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void
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KnowhereTest::TearDown() {
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std::string config_path(CONFIG_PATH);
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milvus::server::CommonUtil::DeleteDirectory(config_path);
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}
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void
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DataGenBase::GenData(const int& dim, const int& nb, const int& nq, float* xb, float* xq, int64_t* ids, const int& k,
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int64_t* gt_ids, float* gt_dis) {
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for (auto i = 0; i < nb; ++i) {
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for (auto j = 0; j < dim; ++j) {
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// p_data[i * d + j] = float(base + i);
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xb[i * dim + j] = drand48();
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}
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xb[dim * i] += i / 1000.;
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ids[i] = i;
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}
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for (size_t i = 0; i < nq * dim; ++i) {
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xq[i] = xb[i];
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}
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faiss::IndexFlatL2 index(dim);
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// index.add_with_ids(nb, xb, ids);
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index.add(nb, xb);
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index.search(nq, xq, k, gt_dis, gt_ids);
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}
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void
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DataGenBase::GenData(const int& dim, const int& nb, const int& nq, std::vector<float>& xb, std::vector<float>& xq,
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std::vector<int64_t>& ids, const int& k, std::vector<int64_t>& gt_ids,
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std::vector<float>& gt_dis) {
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xb.clear();
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xq.clear();
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ids.clear();
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gt_ids.clear();
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gt_dis.clear();
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xb.resize(nb * dim);
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xq.resize(nq * dim);
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ids.resize(nb);
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gt_ids.resize(nq * k);
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gt_dis.resize(nq * k);
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GenData(dim, nb, nq, xb.data(), xq.data(), ids.data(), k, gt_ids.data(), gt_dis.data());
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}
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void
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DataGenBase::AssertResult(const std::vector<int64_t>& ids, const std::vector<float>& dis) {
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EXPECT_EQ(ids.size(), nq * k);
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EXPECT_EQ(dis.size(), nq * k);
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for (auto i = 0; i < nq; i++) {
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EXPECT_EQ(ids[i * k], gt_ids[i * k]);
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// EXPECT_EQ(dis[i * k], gt_dis[i * k]);
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}
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int match = 0;
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for (int i = 0; i < nq; ++i) {
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for (int j = 0; j < k; ++j) {
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for (int l = 0; l < k; ++l) {
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if (ids[i * nq + j] == gt_ids[i * nq + l])
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match++;
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}
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}
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}
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auto precision = float(match) / (nq * k);
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EXPECT_GT(precision, 0.5);
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std::cout << std::endl << "Precision: " << precision << ", match: " << match << ", total: " << nq * k << std::endl;
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}
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