/**
 * Copyright (c) Facebook, Inc. and its affiliates.
 *
 * This source code is licensed under the MIT license found in the
 * LICENSE file in the root directory of this source tree.
 */

// -*- c++ -*-

#include <faiss/impl/HNSW.h>

#include <string>

#include <faiss/impl/AuxIndexStructures.h>
#include <faiss/impl/DistanceComputer.h>
#include <faiss/impl/IDSelector.h>

namespace faiss {

/**************************************************************
 * HNSW structure implementation
 **************************************************************/

int HNSW::nb_neighbors(int layer_no) const {
    return cum_nneighbor_per_level[layer_no + 1] -
            cum_nneighbor_per_level[layer_no];
}

void HNSW::set_nb_neighbors(int level_no, int n) {
    FAISS_THROW_IF_NOT(levels.size() == 0);
    int cur_n = nb_neighbors(level_no);
    for (int i = level_no + 1; i < cum_nneighbor_per_level.size(); i++) {
        cum_nneighbor_per_level[i] += n - cur_n;
    }
}

int HNSW::cum_nb_neighbors(int layer_no) const {
    return cum_nneighbor_per_level[layer_no];
}

void HNSW::neighbor_range(idx_t no, int layer_no, size_t* begin, size_t* end)
        const {
    size_t o = offsets[no];
    *begin = o + cum_nb_neighbors(layer_no);
    *end = o + cum_nb_neighbors(layer_no + 1);
}

HNSW::HNSW(int M) : rng(12345) {
    set_default_probas(M, 1.0 / log(M));
    max_level = -1;
    entry_point = -1;
    efSearch = 16;
    efConstruction = 40;
    upper_beam = 1;
    offsets.push_back(0);
}

int HNSW::random_level() {
    double f = rng.rand_float();
    // could be a bit faster with bissection
    for (int level = 0; level < assign_probas.size(); level++) {
        if (f < assign_probas[level]) {
            return level;
        }
        f -= assign_probas[level];
    }
    // happens with exponentially low probability
    return assign_probas.size() - 1;
}

void HNSW::set_default_probas(int M, float levelMult) {
    int nn = 0;
    cum_nneighbor_per_level.push_back(0);
    for (int level = 0;; level++) {
        float proba = exp(-level / levelMult) * (1 - exp(-1 / levelMult));
        if (proba < 1e-9)
            break;
        assign_probas.push_back(proba);
        nn += level == 0 ? M * 2 : M;
        cum_nneighbor_per_level.push_back(nn);
    }
}

void HNSW::clear_neighbor_tables(int level) {
    for (int i = 0; i < levels.size(); i++) {
        size_t begin, end;
        neighbor_range(i, level, &begin, &end);
        for (size_t j = begin; j < end; j++) {
            neighbors[j] = -1;
        }
    }
}

void HNSW::reset() {
    max_level = -1;
    entry_point = -1;
    offsets.clear();
    offsets.push_back(0);
    levels.clear();
    neighbors.clear();
}

void HNSW::print_neighbor_stats(int level) const {
    FAISS_THROW_IF_NOT(level < cum_nneighbor_per_level.size());
    printf("stats on level %d, max %d neighbors per vertex:\n",
           level,
           nb_neighbors(level));
    size_t tot_neigh = 0, tot_common = 0, tot_reciprocal = 0, n_node = 0;
#pragma omp parallel for reduction(+: tot_neigh) reduction(+: tot_common) \
  reduction(+: tot_reciprocal) reduction(+: n_node)
    for (int i = 0; i < levels.size(); i++) {
        if (levels[i] > level) {
            n_node++;
            size_t begin, end;
            neighbor_range(i, level, &begin, &end);
            std::unordered_set<int> neighset;
            for (size_t j = begin; j < end; j++) {
                if (neighbors[j] < 0)
                    break;
                neighset.insert(neighbors[j]);
            }
            int n_neigh = neighset.size();
            int n_common = 0;
            int n_reciprocal = 0;
            for (size_t j = begin; j < end; j++) {
                storage_idx_t i2 = neighbors[j];
                if (i2 < 0)
                    break;
                FAISS_ASSERT(i2 != i);
                size_t begin2, end2;
                neighbor_range(i2, level, &begin2, &end2);
                for (size_t j2 = begin2; j2 < end2; j2++) {
                    storage_idx_t i3 = neighbors[j2];
                    if (i3 < 0)
                        break;
                    if (i3 == i) {
                        n_reciprocal++;
                        continue;
                    }
                    if (neighset.count(i3)) {
                        neighset.erase(i3);
                        n_common++;
                    }
                }
            }
            tot_neigh += n_neigh;
            tot_common += n_common;
            tot_reciprocal += n_reciprocal;
        }
    }
    float normalizer = n_node;
    printf("   nb of nodes at that level %zd\n", n_node);
    printf("   neighbors per node: %.2f (%zd)\n",
           tot_neigh / normalizer,
           tot_neigh);
    printf("   nb of reciprocal neighbors: %.2f\n",
           tot_reciprocal / normalizer);
    printf("   nb of neighbors that are also neighbor-of-neighbors: %.2f (%zd)\n",
           tot_common / normalizer,
           tot_common);
}

void HNSW::fill_with_random_links(size_t n) {
    int max_level = prepare_level_tab(n);
    RandomGenerator rng2(456);

    for (int level = max_level - 1; level >= 0; --level) {
        std::vector<int> elts;
        for (int i = 0; i < n; i++) {
            if (levels[i] > level) {
                elts.push_back(i);
            }
        }
        printf("linking %zd elements in level %d\n", elts.size(), level);

        if (elts.size() == 1)
            continue;

        for (int ii = 0; ii < elts.size(); ii++) {
            int i = elts[ii];
            size_t begin, end;
            neighbor_range(i, 0, &begin, &end);
            for (size_t j = begin; j < end; j++) {
                int other = 0;
                do {
                    other = elts[rng2.rand_int(elts.size())];
                } while (other == i);

                neighbors[j] = other;
            }
        }
    }
}

int HNSW::prepare_level_tab(size_t n, bool preset_levels) {
    size_t n0 = offsets.size() - 1;

    if (preset_levels) {
        FAISS_ASSERT(n0 + n == levels.size());
    } else {
        FAISS_ASSERT(n0 == levels.size());
        for (int i = 0; i < n; i++) {
            int pt_level = random_level();
            levels.push_back(pt_level + 1);
        }
    }

    int max_level = 0;
    for (int i = 0; i < n; i++) {
        int pt_level = levels[i + n0] - 1;
        if (pt_level > max_level)
            max_level = pt_level;
        offsets.push_back(offsets.back() + cum_nb_neighbors(pt_level + 1));
        neighbors.resize(offsets.back(), -1);
    }

    return max_level;
}

/** Enumerate vertices from farthest to nearest from query, keep a
 * neighbor only if there is no previous neighbor that is closer to
 * that vertex than the query.
 */
void HNSW::shrink_neighbor_list(
        DistanceComputer& qdis,
        std::priority_queue<NodeDistFarther>& input,
        std::vector<NodeDistFarther>& output,
        int max_size) {
    while (input.size() > 0) {
        NodeDistFarther v1 = input.top();
        input.pop();
        float dist_v1_q = v1.d;

        bool good = true;
        for (NodeDistFarther v2 : output) {
            float dist_v1_v2 = qdis.symmetric_dis(v2.id, v1.id);

            if (dist_v1_v2 < dist_v1_q) {
                good = false;
                break;
            }
        }

        if (good) {
            output.push_back(v1);
            if (output.size() >= max_size) {
                return;
            }
        }
    }
}

namespace {

using storage_idx_t = HNSW::storage_idx_t;
using NodeDistCloser = HNSW::NodeDistCloser;
using NodeDistFarther = HNSW::NodeDistFarther;

/**************************************************************
 * Addition subroutines
 **************************************************************/

/// remove neighbors from the list to make it smaller than max_size
void shrink_neighbor_list(
        DistanceComputer& qdis,
        std::priority_queue<NodeDistCloser>& resultSet1,
        int max_size) {
    if (resultSet1.size() < max_size) {
        return;
    }
    std::priority_queue<NodeDistFarther> resultSet;
    std::vector<NodeDistFarther> returnlist;

    while (resultSet1.size() > 0) {
        resultSet.emplace(resultSet1.top().d, resultSet1.top().id);
        resultSet1.pop();
    }

    HNSW::shrink_neighbor_list(qdis, resultSet, returnlist, max_size);

    for (NodeDistFarther curen2 : returnlist) {
        resultSet1.emplace(curen2.d, curen2.id);
    }
}

/// add a link between two elements, possibly shrinking the list
/// of links to make room for it.
void add_link(
        HNSW& hnsw,
        DistanceComputer& qdis,
        storage_idx_t src,
        storage_idx_t dest,
        int level) {
    size_t begin, end;
    hnsw.neighbor_range(src, level, &begin, &end);
    if (hnsw.neighbors[end - 1] == -1) {
        // there is enough room, find a slot to add it
        size_t i = end;
        while (i > begin) {
            if (hnsw.neighbors[i - 1] != -1)
                break;
            i--;
        }
        hnsw.neighbors[i] = dest;
        return;
    }

    // otherwise we let them fight out which to keep

    // copy to resultSet...
    std::priority_queue<NodeDistCloser> resultSet;
    resultSet.emplace(qdis.symmetric_dis(src, dest), dest);
    for (size_t i = begin; i < end; i++) { // HERE WAS THE BUG
        storage_idx_t neigh = hnsw.neighbors[i];
        resultSet.emplace(qdis.symmetric_dis(src, neigh), neigh);
    }

    shrink_neighbor_list(qdis, resultSet, end - begin);

    // ...and back
    size_t i = begin;
    while (resultSet.size()) {
        hnsw.neighbors[i++] = resultSet.top().id;
        resultSet.pop();
    }
    // they may have shrunk more than just by 1 element
    while (i < end) {
        hnsw.neighbors[i++] = -1;
    }
}

/// search neighbors on a single level, starting from an entry point
void search_neighbors_to_add(
        HNSW& hnsw,
        DistanceComputer& qdis,
        std::priority_queue<NodeDistCloser>& results,
        int entry_point,
        float d_entry_point,
        int level,
        VisitedTable& vt) {
    // top is nearest candidate
    std::priority_queue<NodeDistFarther> candidates;

    NodeDistFarther ev(d_entry_point, entry_point);
    candidates.push(ev);
    results.emplace(d_entry_point, entry_point);
    vt.set(entry_point);

    while (!candidates.empty()) {
        // get nearest
        const NodeDistFarther& currEv = candidates.top();

        if (currEv.d > results.top().d) {
            break;
        }
        int currNode = currEv.id;
        candidates.pop();

        // loop over neighbors
        size_t begin, end;
        hnsw.neighbor_range(currNode, level, &begin, &end);
        for (size_t i = begin; i < end; i++) {
            storage_idx_t nodeId = hnsw.neighbors[i];
            if (nodeId < 0)
                break;
            if (vt.get(nodeId))
                continue;
            vt.set(nodeId);

            float dis = qdis(nodeId);
            NodeDistFarther evE1(dis, nodeId);

            if (results.size() < hnsw.efConstruction || results.top().d > dis) {
                results.emplace(dis, nodeId);
                candidates.emplace(dis, nodeId);
                if (results.size() > hnsw.efConstruction) {
                    results.pop();
                }
            }
        }
    }
    vt.advance();
}

/**************************************************************
 * Searching subroutines
 **************************************************************/

/// greedily update a nearest vector at a given level
void greedy_update_nearest(
        const HNSW& hnsw,
        DistanceComputer& qdis,
        int level,
        storage_idx_t& nearest,
        float& d_nearest) {
    for (;;) {
        storage_idx_t prev_nearest = nearest;

        size_t begin, end;
        hnsw.neighbor_range(nearest, level, &begin, &end);
        for (size_t i = begin; i < end; i++) {
            storage_idx_t v = hnsw.neighbors[i];
            if (v < 0)
                break;
            float dis = qdis(v);
            if (dis < d_nearest) {
                nearest = v;
                d_nearest = dis;
            }
        }
        if (nearest == prev_nearest) {
            return;
        }
    }
}

} // namespace

/// Finds neighbors and builds links with them, starting from an entry
/// point. The own neighbor list is assumed to be locked.
void HNSW::add_links_starting_from(
        DistanceComputer& ptdis,
        storage_idx_t pt_id,
        storage_idx_t nearest,
        float d_nearest,
        int level,
        omp_lock_t* locks,
        VisitedTable& vt) {
    std::priority_queue<NodeDistCloser> link_targets;

    search_neighbors_to_add(
            *this, ptdis, link_targets, nearest, d_nearest, level, vt);

    // but we can afford only this many neighbors
    int M = nb_neighbors(level);

    ::faiss::shrink_neighbor_list(ptdis, link_targets, M);

    std::vector<storage_idx_t> neighbors;
    neighbors.reserve(link_targets.size());
    while (!link_targets.empty()) {
        storage_idx_t other_id = link_targets.top().id;
        add_link(*this, ptdis, pt_id, other_id, level);
        neighbors.push_back(other_id);
        link_targets.pop();
    }

    omp_unset_lock(&locks[pt_id]);
    for (storage_idx_t other_id : neighbors) {
        omp_set_lock(&locks[other_id]);
        add_link(*this, ptdis, other_id, pt_id, level);
        omp_unset_lock(&locks[other_id]);
    }
    omp_set_lock(&locks[pt_id]);
}

/**************************************************************
 * Building, parallel
 **************************************************************/

void HNSW::add_with_locks(
        DistanceComputer& ptdis,
        int pt_level,
        int pt_id,
        std::vector<omp_lock_t>& locks,
        VisitedTable& vt) {
    //  greedy search on upper levels

    storage_idx_t nearest;
#pragma omp critical
    {
        nearest = entry_point;

        if (nearest == -1) {
            max_level = pt_level;
            entry_point = pt_id;
        }
    }

    if (nearest < 0) {
        return;
    }

    omp_set_lock(&locks[pt_id]);

    int level = max_level; // level at which we start adding neighbors
    float d_nearest = ptdis(nearest);

    for (; level > pt_level; level--) {
        greedy_update_nearest(*this, ptdis, level, nearest, d_nearest);
    }

    for (; level >= 0; level--) {
        add_links_starting_from(
                ptdis, pt_id, nearest, d_nearest, level, locks.data(), vt);
    }

    omp_unset_lock(&locks[pt_id]);

    if (pt_level > max_level) {
        max_level = pt_level;
        entry_point = pt_id;
    }
}

/**************************************************************
 * Searching
 **************************************************************/

namespace {

using idx_t = HNSW::idx_t;
using MinimaxHeap = HNSW::MinimaxHeap;
using Node = HNSW::Node;
/** Do a BFS on the candidates list */

int search_from_candidates(
        const HNSW& hnsw,
        DistanceComputer& qdis,
        int k,
        idx_t* I,
        float* D,
        MinimaxHeap& candidates,
        VisitedTable& vt,
        HNSWStats& stats,
        int level,
        int nres_in = 0,
        const SearchParametersHNSW* params = nullptr) {
    int nres = nres_in;
    int ndis = 0;

    // can be overridden by search params
    bool do_dis_check = params ? params->check_relative_distance
                               : hnsw.check_relative_distance;
    int efSearch = params ? params->efSearch : hnsw.efSearch;
    const IDSelector* sel = params ? params->sel : nullptr;

    for (int i = 0; i < candidates.size(); i++) {
        idx_t v1 = candidates.ids[i];
        float d = candidates.dis[i];
        FAISS_ASSERT(v1 >= 0);
        if (!sel || sel->is_member(v1)) {
            if (nres < k) {
                faiss::maxheap_push(++nres, D, I, d, v1);
            } else if (d < D[0]) {
                faiss::maxheap_replace_top(nres, D, I, d, v1);
            }
        }
        vt.set(v1);
    }

    int nstep = 0;

    while (candidates.size() > 0) {
        float d0 = 0;
        int v0 = candidates.pop_min(&d0);

        if (do_dis_check) {
            // tricky stopping condition: there are more that ef
            // distances that are processed already that are smaller
            // than d0

            int n_dis_below = candidates.count_below(d0);
            if (n_dis_below >= efSearch) {
                break;
            }
        }

        size_t begin, end;
        hnsw.neighbor_range(v0, level, &begin, &end);

        for (size_t j = begin; j < end; j++) {
            int v1 = hnsw.neighbors[j];
            if (v1 < 0)
                break;
            if (vt.get(v1)) {
                continue;
            }
            vt.set(v1);
            ndis++;
            float d = qdis(v1);
            if (!sel || sel->is_member(v1)) {
                if (nres < k) {
                    faiss::maxheap_push(++nres, D, I, d, v1);
                } else if (d < D[0]) {
                    faiss::maxheap_replace_top(nres, D, I, d, v1);
                }
            }
            candidates.push(v1, d);
        }

        nstep++;
        if (!do_dis_check && nstep > efSearch) {
            break;
        }
    }

    if (level == 0) {
        stats.n1++;
        if (candidates.size() == 0) {
            stats.n2++;
        }
        stats.n3 += ndis;
    }

    return nres;
}

std::priority_queue<HNSW::Node> search_from_candidate_unbounded(
        const HNSW& hnsw,
        const Node& node,
        DistanceComputer& qdis,
        int ef,
        VisitedTable* vt,
        HNSWStats& stats) {
    int ndis = 0;
    std::priority_queue<Node> top_candidates;
    std::priority_queue<Node, std::vector<Node>, std::greater<Node>> candidates;

    top_candidates.push(node);
    candidates.push(node);

    vt->set(node.second);

    while (!candidates.empty()) {
        float d0;
        storage_idx_t v0;
        std::tie(d0, v0) = candidates.top();

        if (d0 > top_candidates.top().first) {
            break;
        }

        candidates.pop();

        size_t begin, end;
        hnsw.neighbor_range(v0, 0, &begin, &end);

        for (size_t j = begin; j < end; ++j) {
            int v1 = hnsw.neighbors[j];

            if (v1 < 0) {
                break;
            }
            if (vt->get(v1)) {
                continue;
            }

            vt->set(v1);

            float d1 = qdis(v1);
            ++ndis;

            if (top_candidates.top().first > d1 || top_candidates.size() < ef) {
                candidates.emplace(d1, v1);
                top_candidates.emplace(d1, v1);

                if (top_candidates.size() > ef) {
                    top_candidates.pop();
                }
            }
        }
    }

    ++stats.n1;
    if (candidates.size() == 0) {
        ++stats.n2;
    }
    stats.n3 += ndis;

    return top_candidates;
}

} // anonymous namespace

HNSWStats HNSW::search(
        DistanceComputer& qdis,
        int k,
        idx_t* I,
        float* D,
        VisitedTable& vt,
        const SearchParametersHNSW* params) const {
    HNSWStats stats;
    if (entry_point == -1) {
        return stats;
    }
    if (upper_beam == 1) {
        //  greedy search on upper levels
        storage_idx_t nearest = entry_point;
        float d_nearest = qdis(nearest);

        for (int level = max_level; level >= 1; level--) {
            greedy_update_nearest(*this, qdis, level, nearest, d_nearest);
        }

        int ef = std::max(efSearch, k);
        if (search_bounded_queue) { // this is the most common branch
            MinimaxHeap candidates(ef);

            candidates.push(nearest, d_nearest);

            search_from_candidates(
                    *this, qdis, k, I, D, candidates, vt, stats, 0, 0, params);
        } else {
            std::priority_queue<Node> top_candidates =
                    search_from_candidate_unbounded(
                            *this,
                            Node(d_nearest, nearest),
                            qdis,
                            ef,
                            &vt,
                            stats);

            while (top_candidates.size() > k) {
                top_candidates.pop();
            }

            int nres = 0;
            while (!top_candidates.empty()) {
                float d;
                storage_idx_t label;
                std::tie(d, label) = top_candidates.top();
                faiss::maxheap_push(++nres, D, I, d, label);
                top_candidates.pop();
            }
        }

        vt.advance();

    } else {
        int candidates_size = upper_beam;
        MinimaxHeap candidates(candidates_size);

        std::vector<idx_t> I_to_next(candidates_size);
        std::vector<float> D_to_next(candidates_size);

        int nres = 1;
        I_to_next[0] = entry_point;
        D_to_next[0] = qdis(entry_point);

        for (int level = max_level; level >= 0; level--) {
            // copy I, D -> candidates

            candidates.clear();

            for (int i = 0; i < nres; i++) {
                candidates.push(I_to_next[i], D_to_next[i]);
            }

            if (level == 0) {
                nres = search_from_candidates(
                        *this, qdis, k, I, D, candidates, vt, stats, 0);
            } else {
                nres = search_from_candidates(
                        *this,
                        qdis,
                        candidates_size,
                        I_to_next.data(),
                        D_to_next.data(),
                        candidates,
                        vt,
                        stats,
                        level);
            }
            vt.advance();
        }
    }

    return stats;
}

void HNSW::search_level_0(
        DistanceComputer& qdis,
        int k,
        idx_t* idxi,
        float* simi,
        idx_t nprobe,
        const storage_idx_t* nearest_i,
        const float* nearest_d,
        int search_type,
        HNSWStats& search_stats,
        VisitedTable& vt) const {
    const HNSW& hnsw = *this;

    if (search_type == 1) {
        int nres = 0;

        for (int j = 0; j < nprobe; j++) {
            storage_idx_t cj = nearest_i[j];

            if (cj < 0)
                break;

            if (vt.get(cj))
                continue;

            int candidates_size = std::max(hnsw.efSearch, int(k));
            MinimaxHeap candidates(candidates_size);

            candidates.push(cj, nearest_d[j]);

            nres = search_from_candidates(
                    hnsw,
                    qdis,
                    k,
                    idxi,
                    simi,
                    candidates,
                    vt,
                    search_stats,
                    0,
                    nres);
        }
    } else if (search_type == 2) {
        int candidates_size = std::max(hnsw.efSearch, int(k));
        candidates_size = std::max(candidates_size, int(nprobe));

        MinimaxHeap candidates(candidates_size);
        for (int j = 0; j < nprobe; j++) {
            storage_idx_t cj = nearest_i[j];

            if (cj < 0)
                break;
            candidates.push(cj, nearest_d[j]);
        }

        search_from_candidates(
                hnsw, qdis, k, idxi, simi, candidates, vt, search_stats, 0);
    }
}

/**************************************************************
 * MinimaxHeap
 **************************************************************/

void HNSW::MinimaxHeap::push(storage_idx_t i, float v) {
    if (k == n) {
        if (v >= dis[0])
            return;
        faiss::heap_pop<HC>(k--, dis.data(), ids.data());
        --nvalid;
    }
    faiss::heap_push<HC>(++k, dis.data(), ids.data(), v, i);
    ++nvalid;
}

float HNSW::MinimaxHeap::max() const {
    return dis[0];
}

int HNSW::MinimaxHeap::size() const {
    return nvalid;
}

void HNSW::MinimaxHeap::clear() {
    nvalid = k = 0;
}

int HNSW::MinimaxHeap::pop_min(float* vmin_out) {
    assert(k > 0);
    // returns min. This is an O(n) operation
    int i = k - 1;
    while (i >= 0) {
        if (ids[i] != -1)
            break;
        i--;
    }
    if (i == -1)
        return -1;
    int imin = i;
    float vmin = dis[i];
    i--;
    while (i >= 0) {
        if (ids[i] != -1 && dis[i] < vmin) {
            vmin = dis[i];
            imin = i;
        }
        i--;
    }
    if (vmin_out)
        *vmin_out = vmin;
    int ret = ids[imin];
    ids[imin] = -1;
    --nvalid;

    return ret;
}

int HNSW::MinimaxHeap::count_below(float thresh) {
    int n_below = 0;
    for (int i = 0; i < k; i++) {
        if (dis[i] < thresh) {
            n_below++;
        }
    }

    return n_below;
}

} // namespace faiss
