add and verify filter option

split out common subroutines

1 files changed, 295 insertions, 0 deletions

diff --git a/eval/src/tests/ann/gist_benchmark.cpp b/eval/src/tests/ann/gist_benchmark.cpp
new file mode 100644
index 00000000000..45559fc2557
--- /dev/null
+++ b/eval/src/tests/ann/gist_benchmark.cpp
@@ -0,0 +1,295 @@
+// Copyright 2020 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+
+#include <vespa/vespalib/testkit/test_kit.h>
+#include <vespa/vespalib/util/priority_queue.h>
+#include <sys/types.h>
+#include <sys/stat.h>
+#include <fcntl.h>
+#include <unistd.h>
+#include <stdio.h>
+#include <chrono>
+
+#define NUM_DIMS 960
+#define NUM_DOCS 200000
+#define NUM_REACH 10000
+#define NUM_Q 1000
+
+#include "doc_vector_access.h"
+#include "nns.h"
+#include "for-sift-hit.h"
+#include "for-sift-top-k.h"
+
+std::vector<TopK> bruteforceResults;
+
+struct PointVector {
+    float v[NUM_DIMS];
+    using ConstArr = vespalib::ConstArrayRef<float>;
+    operator ConstArr() const { return ConstArr(v, NUM_DIMS); }
+};
+
+static PointVector *aligned_alloc(size_t num) {
+    size_t num_bytes = num * sizeof(PointVector);
+    double mega_bytes = num_bytes / (1024.0*1024.0);
+    fprintf(stderr, "allocate %.2f MB of vectors\n", mega_bytes);
+    char *mem = (char *)malloc(num_bytes + 512);
+    mem += 512;
+    size_t val = (size_t)mem;
+    size_t unalign = val % 512;
+    mem -= unalign;
+    return reinterpret_cast<PointVector *>(mem);
+}
+
+static PointVector *generatedQueries = aligned_alloc(NUM_Q);
+static PointVector *generatedDocs = aligned_alloc(NUM_DOCS);
+
+struct DocVectorAdapter : public DocVectorAccess<float>
+{
+    vespalib::ConstArrayRef<float> get(uint32_t docid) const override {
+        ASSERT_TRUE(docid < NUM_DOCS);
+        return generatedDocs[docid];
+    }
+};
+
+double computeDistance(const PointVector &query, uint32_t docid) {
+    const PointVector &docvector = generatedDocs[docid];
+    return l2distCalc.l2sq_dist(query, docvector);
+}
+
+void read_queries(std::string fn) {
+    int fd = open(fn.c_str(), O_RDONLY);
+    ASSERT_TRUE(fd > 0);
+    int d;
+    size_t rv;
+    fprintf(stderr, "reading %u queries from %s\n", NUM_Q, fn.c_str());
+    for (uint32_t qid = 0; qid < NUM_Q; ++qid) {
+        rv = read(fd, &d, 4);
+        ASSERT_EQUAL(rv, 4u);
+        ASSERT_EQUAL(d, NUM_DIMS);
+        rv = read(fd, &generatedQueries[qid].v, NUM_DIMS*sizeof(float));
+        ASSERT_EQUAL(rv, sizeof(PointVector));
+    }
+    close(fd);
+}
+
+void read_docs(std::string fn) {
+    int fd = open(fn.c_str(), O_RDONLY);
+    ASSERT_TRUE(fd > 0);
+    int d;
+    size_t rv;
+    fprintf(stderr, "reading %u doc vectors from %s\n", NUM_DOCS, fn.c_str());
+    for (uint32_t docid = 0; docid < NUM_DOCS; ++docid) {
+        rv = read(fd, &d, 4);
+        ASSERT_EQUAL(rv, 4u);
+        ASSERT_EQUAL(d, NUM_DIMS);
+        rv = read(fd, &generatedDocs[docid].v, NUM_DIMS*sizeof(float));
+        ASSERT_EQUAL(rv, sizeof(PointVector));
+    }
+    close(fd);
+}
+
+using TimePoint = std::chrono::steady_clock::time_point;
+using Duration = std::chrono::steady_clock::duration;
+
+double to_ms(Duration elapsed) {
+    std::chrono::duration<double, std::milli> ms(elapsed);
+    return ms.count();
+}
+
+void read_data(std::string dir) {
+    TimePoint bef = std::chrono::steady_clock::now();
+    read_queries(dir + "/gist_query.fvecs");
+    TimePoint aft = std::chrono::steady_clock::now();
+    fprintf(stderr, "read queries: %.3f ms\n", to_ms(aft - bef));
+    bef = std::chrono::steady_clock::now();
+    read_docs(dir + "/gist_base.fvecs");
+    aft = std::chrono::steady_clock::now();
+    fprintf(stderr, "read docs: %.3f ms\n", to_ms(aft - bef));
+}
+
+
+struct BfHitComparator {
+    bool operator() (const Hit &lhs, const Hit& rhs) const {
+        if (lhs.distance < rhs.distance) return false;
+        if (lhs.distance > rhs.distance) return true;
+        return (lhs.docid > rhs.docid);
+    }
+};
+
+class BfHitHeap {
+private:
+    size_t _size;
+    vespalib::PriorityQueue<Hit, BfHitComparator> _priQ;
+public:
+    explicit BfHitHeap(size_t maxSize) : _size(maxSize), _priQ() {
+        _priQ.reserve(maxSize);
+    }
+    ~BfHitHeap() {}
+    void maybe_use(const Hit &hit) {
+        if (_priQ.size() < _size) {
+            _priQ.push(hit);
+        } else if (hit.distance < _priQ.front().distance) {
+            _priQ.front() = hit;
+            _priQ.adjust();
+        }
+    }
+    std::vector<Hit> bestHits() {
+        std::vector<Hit> result;
+        size_t i = _priQ.size();
+        result.resize(i);
+        while (i-- > 0) {
+            result[i] = _priQ.front();
+            _priQ.pop_front();
+        }
+        return result;
+    }
+};
+
+TopK bruteforce_nns(const PointVector &query) {
+    TopK result;
+    BfHitHeap heap(result.K);
+    for (uint32_t docid = 0; docid < NUM_DOCS; ++docid) {
+        const PointVector &docvector = generatedDocs[docid];
+        double d = l2distCalc.l2sq_dist(query, docvector);
+        Hit h(docid, d);
+        heap.maybe_use(h);
+    }
+    std::vector<Hit> best = heap.bestHits();
+    for (size_t i = 0; i < result.K; ++i) {
+        result.hits[i] = best[i];
+    }
+    return result;
+}
+
+void verifyBF(uint32_t qid) {
+    const PointVector &query = generatedQueries[qid];
+    TopK &result = bruteforceResults[qid];
+    double min_distance = result.hits[0].distance;
+    std::vector<double> all_c2;
+    for (uint32_t i = 0; i < NUM_DOCS; ++i) {
+        double dist = computeDistance(query, i);
+        if (dist < min_distance) {
+            fprintf(stderr, "WARN dist %.9g < mindist %.9g\n", dist, min_distance);
+        }
+        EXPECT_FALSE(dist+0.000001 < min_distance);
+        if (min_distance > 0.0) all_c2.push_back(dist / min_distance);
+    }
+    if (all_c2.size() != NUM_DOCS) return;
+    std::sort(all_c2.begin(), all_c2.end());
+    for (uint32_t idx : { 1, 3, 10, 30, 100, 300, 1000, 3000, NUM_DOCS/2, NUM_DOCS-1}) {
+        fprintf(stderr, "c2-factor[%u] = %.3f\n", idx, all_c2[idx]);
+    }
+}
+
+using NNS_API = NNS<float>;
+
+TEST("require that brute force works") {
+    TimePoint bef = std::chrono::steady_clock::now();
+    fprintf(stderr, "generating %u brute force results\n", NUM_Q);
+    bruteforceResults.reserve(NUM_Q);
+    for (uint32_t cnt = 0; cnt < NUM_Q; ++cnt) {
+        const PointVector &query = generatedQueries[cnt];
+        bruteforceResults.emplace_back(bruteforce_nns(query));
+    }
+    TimePoint aft = std::chrono::steady_clock::now();
+    fprintf(stderr, "timing for brute force: %.3f ms = %.3f ms per query\n",
+            to_ms(aft - bef), to_ms(aft - bef)/NUM_Q);
+    for (int cnt = 0; cnt < NUM_Q; cnt = (cnt+1)*2) {
+        verifyBF(cnt);
+    }
+}
+
+#include "find-with-nns.h"
+#include "verify-top-k.h"
+
+void timing_nns(const char *name, NNS_API &nns, std::vector<uint32_t> sk_list) {
+    for (uint32_t search_k : sk_list) {
+        TimePoint bef = std::chrono::steady_clock::now();
+        for (int cnt = 0; cnt < NUM_Q; ++cnt) {
+            find_with_nns(search_k, nns, cnt);
+        }
+        TimePoint aft = std::chrono::steady_clock::now();
+        fprintf(stderr, "timing for %s search_k=%u: %.3f ms = %.3f ms/q\n",
+                name, search_k, to_ms(aft - bef), to_ms(aft - bef)/NUM_Q);
+    }
+}
+
+#include "quality-nns.h"
+
+template <typename FUNC>
+void bm_nns_simple(const char *name, FUNC creator, std::vector<uint32_t> sk_list) {
+    std::unique_ptr<NNS_API> nnsp = creator();
+    NNS_API &nns = *nnsp;
+    fprintf(stderr, "trying %s indexing...\n", name);
+    TimePoint bef = std::chrono::steady_clock::now();
+    for (uint32_t i = 0; i < NUM_DOCS; ++i) {
+        nns.addDoc(i);
+    }
+    TimePoint aft = std::chrono::steady_clock::now();
+    fprintf(stderr, "build %s index with %u docs: %.3f ms\n", name, NUM_DOCS, to_ms(aft - bef));
+    timing_nns(name, nns, sk_list);
+    fprintf(stderr, "Quality for %s [A] clean build with %u documents:\n", name, NUM_DOCS);
+    quality_nns(nns, sk_list);
+}
+
+template <typename FUNC>
+void benchmark_nns(const char *name, FUNC creator, std::vector<uint32_t> sk_list) {
+    bm_nns_simple(name, creator, sk_list);
+}
+
+#if 0
+TEST("require that Locality Sensitive Hashing mostly works") {
+    DocVectorAdapter adapter;
+    auto creator = [&adapter]() { return make_rplsh_nns(NUM_DIMS, adapter); };
+    benchmark_nns("RPLSH", creator, { 200, 1000 });
+}
+#endif
+
+#if 0
+TEST("require that Annoy via NNS api mostly works") {
+    DocVectorAdapter adapter;
+    auto creator = [&adapter]() { return make_annoy_nns(NUM_DIMS, adapter); };
+    benchmark_nns("Annoy", creator, { 8000, 10000 });
+}
+#endif
+
+#if 1
+TEST("require that HNSW via NNS api mostly works") {
+    DocVectorAdapter adapter;
+    auto creator = [&adapter]() { return make_hnsw_nns(NUM_DIMS, adapter); };
+    benchmark_nns("HNSW-like", creator, { 100, 150, 200 });
+}
+#endif
+
+#if 0
+TEST("require that HNSW wrapped api mostly works") {
+    DocVectorAdapter adapter;
+    auto creator = [&adapter]() { return make_hnsw_wrap(NUM_DIMS, adapter); };
+    benchmark_nns("HNSW-wrap", creator, { 100, 150, 200 });
+}
+#endif
+
+/**
+ * Before running the benchmark the ANN_GIST1M data set must be downloaded and extracted:
+ *   wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+ *   tar -xf gist.tar.gz
+ *
+ * The benchmark program will load the data set from $HOME/gist if no directory is specified.
+ *
+ * More information about the dataset is found here: http://corpus-texmex.irisa.fr/.
+ */
+int main(int argc, char **argv) {
+    TEST_MASTER.init(__FILE__);
+    std::string gist_dir = ".";
+    if (argc > 1) {
+        gist_dir = argv[1];
+    } else {
+        char *home = getenv("HOME");
+        if (home) {
+            gist_dir = home;
+            gist_dir += "/gist";
+        }
+    }
+    read_data(gist_dir);
+    TEST_RUN_ALL();
+    return (TEST_MASTER.fini() ? 0 : 1);
+}