Initial commit

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/1-Flat.cpp

@@ -0,0 +1,101 @@
+/*
+ * 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 <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexFlat.h>
+
+// 64-bit int
+using idx_t = faiss::idx_t;
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[d * nb];
+    float* xq = new float[d * nq];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++)
+            xb[d * i + j] = distrib(rng);
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++)
+            xq[d * i + j] = distrib(rng);
+        xq[d * i] += i / 1000.;
+    }
+
+    faiss::IndexFlatL2 index(d); // call constructor
+    printf("is_trained = %s\n", index.is_trained ? "true" : "false");
+    index.add(nb, xb); // add vectors to the index
+    printf("ntotal = %zd\n", index.ntotal);
+
+    int k = 4;
+
+    { // sanity check: search 5 first vectors of xb
+        idx_t* I = new idx_t[k * 5];
+        float* D = new float[k * 5];
+
+        index.search(5, xb, k, D, I);
+
+        // print results
+        printf("I=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5zd ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("D=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%7g ", D[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    { // search xq
+        idx_t* I = new idx_t[k * nq];
+        float* D = new float[k * nq];
+
+        index.search(nq, xq, k, D, I);
+
+        // print results
+        printf("I (5 first results)=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5zd ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("D (5 last results)=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5f ", D[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/2-IVFFlat.cpp

@@ -0,0 +1,79 @@
+/*
+ * 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 <cassert>
+#include <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexFlat.h>
+#include <faiss/IndexIVFFlat.h>
+
+using idx_t = faiss::idx_t;
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[d * nb];
+    float* xq = new float[d * nq];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++)
+            xb[d * i + j] = distrib(rng);
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++)
+            xq[d * i + j] = distrib(rng);
+        xq[d * i] += i / 1000.;
+    }
+
+    int nlist = 100;
+    int k = 4;
+
+    faiss::IndexFlatL2 quantizer(d); // the other index
+    faiss::IndexIVFFlat index(&quantizer, d, nlist);
+    assert(!index.is_trained);
+    index.train(nb, xb);
+    assert(index.is_trained);
+    index.add(nb, xb);
+
+    { // search xq
+        idx_t* I = new idx_t[k * nq];
+        float* D = new float[k * nq];
+
+        index.search(nq, xq, k, D, I);
+
+        printf("I=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5zd ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("D=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5f ", D[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/3-IVFPQ.cpp

@@ -0,0 +1,95 @@
+/*
+ * 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 <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexFlat.h>
+#include <faiss/IndexIVFPQ.h>
+
+using idx_t = faiss::idx_t;
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[d * nb];
+    float* xq = new float[d * nq];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++)
+            xb[d * i + j] = distrib(rng);
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++)
+            xq[d * i + j] = distrib(rng);
+        xq[d * i] += i / 1000.;
+    }
+
+    int nlist = 100;
+    int k = 4;
+    int m = 8;                       // bytes per vector
+    faiss::IndexFlatL2 quantizer(d); // the other index
+    faiss::IndexIVFPQ index(&quantizer, d, nlist, m, 8);
+
+    index.train(nb, xb);
+    index.add(nb, xb);
+
+    { // sanity check
+        idx_t* I = new idx_t[k * 5];
+        float* D = new float[k * 5];
+
+        index.search(5, xb, k, D, I);
+
+        printf("I=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5zd ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("D=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%7g ", D[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    { // search xq
+        idx_t* I = new idx_t[k * nq];
+        float* D = new float[k * nq];
+
+        index.nprobe = 10;
+        index.search(nq, xq, k, D, I);
+
+        printf("I=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5zd ", I[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/4-GPU.cpp

@@ -0,0 +1,120 @@
+/*
+ * 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 <cassert>
+#include <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexFlat.h>
+#include <faiss/gpu/GpuIndexFlat.h>
+#include <faiss/gpu/GpuIndexIVFFlat.h>
+#include <faiss/gpu/StandardGpuResources.h>
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[d * nb];
+    float* xq = new float[d * nq];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++)
+            xb[d * i + j] = distrib(rng);
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++)
+            xq[d * i + j] = distrib(rng);
+        xq[d * i] += i / 1000.;
+    }
+
+    faiss::gpu::StandardGpuResources res;
+
+    // Using a flat index
+
+    faiss::gpu::GpuIndexFlatL2 index_flat(&res, d);
+
+    printf("is_trained = %s\n", index_flat.is_trained ? "true" : "false");
+    index_flat.add(nb, xb); // add vectors to the index
+    printf("ntotal = %ld\n", index_flat.ntotal);
+
+    int k = 4;
+
+    { // search xq
+        long* I = new long[k * nq];
+        float* D = new float[k * nq];
+
+        index_flat.search(nq, xq, k, D, I);
+
+        // print results
+        printf("I (5 first results)=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("I (5 last results)=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    // Using an IVF index
+
+    int nlist = 100;
+    faiss::gpu::GpuIndexIVFFlat index_ivf(&res, d, nlist, faiss::METRIC_L2);
+
+    assert(!index_ivf.is_trained);
+    index_ivf.train(nb, xb);
+    assert(index_ivf.is_trained);
+    index_ivf.add(nb, xb); // add vectors to the index
+
+    printf("is_trained = %s\n", index_ivf.is_trained ? "true" : "false");
+    printf("ntotal = %ld\n", index_ivf.ntotal);
+
+    { // search xq
+        long* I = new long[k * nq];
+        float* D = new float[k * nq];
+
+        index_ivf.search(nq, xq, k, D, I);
+
+        // print results
+        printf("I (5 first results)=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("I (5 last results)=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/5-Multiple-GPUs.cpp

@@ -0,0 +1,99 @@
+/*
+ * 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 <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexFlat.h>
+#include <faiss/gpu/GpuAutoTune.h>
+#include <faiss/gpu/GpuCloner.h>
+#include <faiss/gpu/GpuIndexFlat.h>
+#include <faiss/gpu/StandardGpuResources.h>
+#include <faiss/gpu/utils/DeviceUtils.h>
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[d * nb];
+    float* xq = new float[d * nq];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++)
+            xb[d * i + j] = distrib(rng);
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++)
+            xq[d * i + j] = distrib(rng);
+        xq[d * i] += i / 1000.;
+    }
+
+    int ngpus = faiss::gpu::getNumDevices();
+
+    printf("Number of GPUs: %d\n", ngpus);
+
+    std::vector<faiss::gpu::GpuResourcesProvider*> res;
+    std::vector<int> devs;
+    for (int i = 0; i < ngpus; i++) {
+        res.push_back(new faiss::gpu::StandardGpuResources);
+        devs.push_back(i);
+    }
+
+    faiss::IndexFlatL2 cpu_index(d);
+
+    faiss::Index* gpu_index =
+            faiss::gpu::index_cpu_to_gpu_multiple(res, devs, &cpu_index);
+
+    printf("is_trained = %s\n", gpu_index->is_trained ? "true" : "false");
+    gpu_index->add(nb, xb); // add vectors to the index
+    printf("ntotal = %ld\n", gpu_index->ntotal);
+
+    int k = 4;
+
+    { // search xq
+        long* I = new long[k * nq];
+        float* D = new float[k * nq];
+
+        gpu_index->search(nq, xq, k, D, I);
+
+        // print results
+        printf("I (5 first results)=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("I (5 last results)=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    delete gpu_index;
+
+    for (int i = 0; i < ngpus; i++) {
+        delete res[i];
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/6-HNSW.cpp

@@ -0,0 +1,73 @@
+/*
+ * 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 <cassert>
+#include <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexHNSW.h>
+
+using idx_t = faiss::idx_t;
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[d * nb];
+    float* xq = new float[d * nq];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++)
+            xb[d * i + j] = distrib(rng);
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++)
+            xq[d * i + j] = distrib(rng);
+        xq[d * i] += i / 1000.;
+    }
+
+    int k = 4;
+
+    faiss::IndexHNSWFlat index(d, 32);
+    index.add(nb, xb);
+
+    { // search xq
+        idx_t* I = new idx_t[k * nq];
+        float* D = new float[k * nq];
+
+        index.search(nq, xq, k, D, I);
+
+        printf("I=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5zd ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("D=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5f ", D[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/7-PQFastScan.cpp

@@ -0,0 +1,75 @@
+/*
+ * 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 <cassert>
+#include <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexPQFastScan.h>
+
+using idx_t = faiss::idx_t;
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[(int)(d * nb)];
+    float* xq = new float[(int)(d * nq)];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++) {
+            xb[d * i + j] = distrib(rng);
+        }
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++) {
+            xq[d * i + j] = distrib(rng);
+        }
+        xq[d * i] += i / 1000.;
+    }
+
+    int m = 8;
+    int n_bit = 4;
+
+    faiss::IndexPQFastScan index(d, m, n_bit);
+    printf("Index is trained? %s\n", index.is_trained ? "true" : "false");
+    index.train(nb, xb);
+    printf("Index is trained? %s\n", index.is_trained ? "true" : "false");
+    index.add(nb, xb);
+
+    int k = 4;
+
+    { // search xq
+        idx_t* I = new idx_t[(int)(k * nq)];
+        float* D = new float[(int)(k * nq)];
+
+        index.search(nq, xq, k, D, I);
+
+        printf("I=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++) {
+                printf("%5zd ", I[i * k + j]);
+            }
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+} // namespace facebook::detail

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/8-PQFastScanRefine.cpp

@@ -0,0 +1,84 @@
+/*
+ * 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 <cassert>
+#include <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexPQFastScan.h>
+#include <faiss/IndexRefine.h>
+
+using idx_t = faiss::idx_t;
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[(int)(d * nb)];
+    float* xq = new float[(int)(d * nq)];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++) {
+            xb[d * i + j] = distrib(rng);
+        }
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++) {
+            xq[d * i + j] = distrib(rng);
+        }
+        xq[d * i] += i / 1000.;
+    }
+
+    int m = 8;
+    int n_bit = 4;
+
+    faiss::IndexPQFastScan index(d, m, n_bit);
+    faiss::IndexRefineFlat index_refine(&index);
+    // refine index after PQFastScan
+
+    printf("Index is trained? %s\n",
+           index_refine.is_trained ? "true" : "false");
+    index_refine.train(nb, xb);
+    printf("Index is trained? %s\n",
+           index_refine.is_trained ? "true" : "false");
+    index_refine.add(nb, xb);
+
+    int k = 4;
+    { // search xq
+        idx_t* I = new idx_t[(int)(k * nq)];
+        float* D = new float[(int)(k * nq)];
+        float k_factor = 3;
+        faiss::IndexRefineSearchParameters* params =
+                new faiss::IndexRefineSearchParameters();
+        params->k_factor = k_factor;
+        index_refine.search(nq, xq, k, D, I, params);
+
+        printf("I=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++) {
+                printf("%5zd ", I[i * k + j]);
+            }
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+        delete params;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/9-RefineComparison.cpp

@@ -0,0 +1,104 @@
+/*
+ * 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 <cassert>
+#include <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexPQFastScan.h>
+#include <faiss/IndexRefine.h>
+#include <faiss/index_factory.h>
+using idx_t = faiss::idx_t;
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[(int)(d * nb)];
+    float* xq = new float[(int)(d * nq)];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++) {
+            xb[d * i + j] = distrib(rng);
+        }
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++) {
+            xq[d * i + j] = distrib(rng);
+        }
+        xq[d * i] += i / 1000.;
+    }
+
+    // Constructing the refine PQ index with SQfp16 with index factory
+    faiss::Index* index_fp16;
+    index_fp16 = faiss::index_factory(
+            d, "PQ32x4fs,Refine(SQfp16)", faiss::METRIC_L2);
+    index_fp16->train(nb, xb);
+    index_fp16->add(nb, xb);
+
+    // Constructing the refine PQ index with SQ8
+    faiss::Index* index_sq8;
+    index_sq8 =
+            faiss::index_factory(d, "PQ32x4fs,Refine(SQ8)", faiss::METRIC_L2);
+    index_sq8->train(nb, xb);
+    index_sq8->add(nb, xb);
+
+    int k = 10;
+    { // search xq
+        idx_t* I_fp16 = new idx_t[(int)(k * nq)];
+        float* D_fp16 = new float[(int)(k * nq)];
+        idx_t* I_sq8 = new idx_t[(int)(k * nq)];
+        float* D_sq8 = new float[(int)(k * nq)];
+
+        // Parameterization on k factor while doing search for index refinement
+        float k_factor = 3;
+        faiss::IndexRefineSearchParameters* params =
+                new faiss::IndexRefineSearchParameters();
+        params->k_factor = k_factor;
+
+        // Perform index search using different index refinement
+        index_fp16->search(nq, xq, k, D_fp16, I_fp16, params);
+        index_sq8->search(nq, xq, k, D_sq8, I_sq8, params);
+
+        printf("I_fp16=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++) {
+                printf("%5zd ", I_fp16[i * k + j]);
+            }
+            printf("\n");
+        }
+
+        printf("I_sq8=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++) {
+                printf("%5zd ", I_sq8[i * k + j]);
+            }
+            printf("\n");
+        }
+
+        delete[] I_fp16;
+        delete[] D_fp16;
+        delete[] I_sq8;
+        delete[] D_sq8;
+        delete params;
+
+        delete index_fp16;
+        delete index_sq8;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/CMakeLists.txt

@@ -0,0 +1,31 @@
+# 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.
+
+add_executable(1-Flat EXCLUDE_FROM_ALL 1-Flat.cpp)
+target_link_libraries(1-Flat PRIVATE faiss)
+
+add_executable(2-IVFFlat EXCLUDE_FROM_ALL 2-IVFFlat.cpp)
+target_link_libraries(2-IVFFlat PRIVATE faiss)
+
+add_executable(3-IVFPQ EXCLUDE_FROM_ALL 3-IVFPQ.cpp)
+target_link_libraries(3-IVFPQ PRIVATE faiss)
+
+add_executable(4-GPU EXCLUDE_FROM_ALL 4-GPU.cpp)
+target_link_libraries(4-GPU PRIVATE faiss)
+
+add_executable(5-Multiple-GPUs EXCLUDE_FROM_ALL 5-Multiple-GPUs.cpp)
+target_link_libraries(5-Multiple-GPUs PRIVATE faiss)
+
+add_executable(6-HNSW EXCLUDE_FROM_ALL 6-HNSW.cpp)
+target_link_libraries(6-HNSW PRIVATE faiss)
+
+add_executable(7-PQFastScan EXCLUDE_FROM_ALL 7-PQFastScan.cpp)
+target_link_libraries(7-PQFastScan PRIVATE faiss)
+
+add_executable(8-PQFastScanRefine EXCLUDE_FROM_ALL 8-PQFastScanRefine.cpp)
+target_link_libraries(8-PQFastScanRefine PRIVATE faiss)
+
+add_executable(9-RefineComparison EXCLUDE_FROM_ALL 9-RefineComparison.cpp)
+target_link_libraries(9-RefineComparison PRIVATE faiss)