restore deleted example

Author: ahuber21

examples/cpp/shared/example_vamana_with_compression.cpp

@@ -0,0 +1,101 @@
+/*
+ * Copyright 2025 Intel Corporation
+ *
+ * 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.
+ */
+
+// SVS
+#include "svs/core/recall.h"
+#include "svs/extensions/flat/leanvec.h"
+#include "svs/extensions/flat/lvq.h"
+#include "svs/extensions/vamana/leanvec.h"
+#include "svs/extensions/vamana/lvq.h"
+#include "svs/orchestrators/dynamic_vamana.h"
+#include "svs/orchestrators/exhaustive.h"
+#include "svs/orchestrators/vamana.h"
+
+int main() {
+    // STEP 1: Compress Data with LeanVec, reducing dimensionality to leanvec_dim dimensions
+    // and using 4 and 8 bits for primary and secondary levels respectively.
+    //! [Compress data]
+    const size_t num_threads = 4;
+    size_t padding = 32;
+    size_t leanvec_dim = 64;
+    auto threadpool = svs::threads::as_threadpool(num_threads);
+    auto loaded =
+        svs::VectorDataLoader<float>(std::filesystem::path(SVS_DATA_DIR) / "data_f32.svs")
+            .load();
+    auto data = svs::leanvec::LeanDataset<
+        svs::leanvec::UsingLVQ<4>,
+        svs::leanvec::UsingLVQ<8>,
+        svs::Dynamic,
+        svs::Dynamic>::
+        reduce(
+            loaded,
+            std::nullopt,
+            threadpool,
+            padding,
+            svs::lib::MaybeStatic<svs::Dynamic>(leanvec_dim)
+        );
+    //! [Compress data]
+
+    // STEP 2: Build Vamana Index
+    //! [Index Build]
+    auto parameters = svs::index::vamana::VamanaBuildParameters{};
+    svs::Vamana index = svs::Vamana::build<float>(
+        parameters, data, svs::distance::DistanceL2(), num_threads
+    );
+    //! [Index Build]
+
+    // STEP 3: Search the Index
+    //! [Perform Queries]
+    const size_t search_window_size = 50;
+    const size_t n_neighbors = 10;
+    index.set_search_window_size(search_window_size);
+
+    auto queries =
+        svs::load_data<float>(std::filesystem::path(SVS_DATA_DIR) / "queries_f32.fvecs");
+    auto results = index.search(queries, n_neighbors);
+    //! [Perform Queries]
+
+    //! [Recall]
+    auto groundtruth = svs::load_data<int>(
+        std::filesystem::path(SVS_DATA_DIR) / "groundtruth_euclidean.ivecs"
+    );
+    double recall = svs::k_recall_at_n(groundtruth, results, n_neighbors, n_neighbors);
+
+    fmt::print("Recall@{} = {:.4f}\n", n_neighbors, recall);
+    //! [Recall]
+
+    // STEP 4: Saving and reloading the index
+    //! [Saving Loading]
+    index.save("config", "graph", "data");
+    index = svs::Vamana::assemble<float>(
+        "config",
+        svs::GraphLoader("graph"),
+        svs::lib::load_from_disk<svs::leanvec::LeanDataset<
+            svs::leanvec::UsingLVQ<4>,
+            svs::leanvec::UsingLVQ<8>,
+            svs::Dynamic,
+            svs::Dynamic>>("data", padding),
+        svs::distance::DistanceL2(),
+        num_threads
+    );
+    //! [Saving Loading]
+    index.set_search_window_size(search_window_size);
+    recall = svs::k_recall_at_n(groundtruth, results, n_neighbors, n_neighbors);
+
+    fmt::print("Recall@{} after saving and reloading = {:.4f}\n", n_neighbors, recall);
+
+    return 0;
+}