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packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/8-PQFastScanRefine.cpp
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84
packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/8-PQFastScanRefine.cpp
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/*
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* Copyright (c) Meta Platforms, Inc. and affiliates.
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*
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* This source code is licensed under the MIT license found in the
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* LICENSE file in the root directory of this source tree.
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*/
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#include <cassert>
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#include <cstdio>
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#include <cstdlib>
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#include <random>
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#include <faiss/IndexPQFastScan.h>
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#include <faiss/IndexRefine.h>
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using idx_t = faiss::idx_t;
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int main() {
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int d = 64; // dimension
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int nb = 100000; // database size
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int nq = 10000; // nb of queries
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std::mt19937 rng;
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std::uniform_real_distribution<> distrib;
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float* xb = new float[(int)(d * nb)];
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float* xq = new float[(int)(d * nq)];
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for (int i = 0; i < nb; i++) {
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for (int j = 0; j < d; j++) {
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xb[d * i + j] = distrib(rng);
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}
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xb[d * i] += i / 1000.;
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}
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for (int i = 0; i < nq; i++) {
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for (int j = 0; j < d; j++) {
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xq[d * i + j] = distrib(rng);
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}
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xq[d * i] += i / 1000.;
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}
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int m = 8;
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int n_bit = 4;
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faiss::IndexPQFastScan index(d, m, n_bit);
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faiss::IndexRefineFlat index_refine(&index);
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// refine index after PQFastScan
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printf("Index is trained? %s\n",
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index_refine.is_trained ? "true" : "false");
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index_refine.train(nb, xb);
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printf("Index is trained? %s\n",
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index_refine.is_trained ? "true" : "false");
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index_refine.add(nb, xb);
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int k = 4;
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{ // search xq
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idx_t* I = new idx_t[(int)(k * nq)];
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float* D = new float[(int)(k * nq)];
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float k_factor = 3;
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faiss::IndexRefineSearchParameters* params =
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new faiss::IndexRefineSearchParameters();
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params->k_factor = k_factor;
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index_refine.search(nq, xq, k, D, I, params);
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printf("I=\n");
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for (int i = nq - 5; i < nq; i++) {
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for (int j = 0; j < k; j++) {
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printf("%5zd ", I[i * k + j]);
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}
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printf("\n");
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}
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delete[] I;
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delete[] D;
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delete params;
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}
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delete[] xb;
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delete[] xq;
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return 0;
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}
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