/**
 * 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.
 */

/*
 * Implementation of Hamming related functions (distances, smallest distance
 * selection with regular heap|radix and probabilistic heap|radix.
 *
 * IMPLEMENTATION NOTES
 * Optimal speed is typically obtained for vector sizes of multiples of 64
 * bits.
 *
 * hamdis_t is used for distances because at this time
 * it is not clear how we will need to balance
 * - flexibility in vector size (unclear more than 2^16 or even 2^8 bitvectors)
 * - memory usage
 * - cache-misses when dealing with large volumes of data (lower bits is better)
 *
 */

#include <faiss/utils/hamming.h>

#include <math.h>
#include <stdio.h>
#include <algorithm>
#include <memory>
#include <vector>

#include <faiss/impl/AuxIndexStructures.h>
#include <faiss/impl/FaissAssert.h>
#include <faiss/utils/Heap.h>
#include <faiss/utils/approx_topk_hamming/approx_topk_hamming.h>
#include <faiss/utils/utils.h>

static const size_t BLOCKSIZE_QUERY = 8192;

namespace faiss {

size_t hamming_batch_size = 65536;

template <size_t nbits>
void hammings(
        const uint64_t* __restrict bs1,
        const uint64_t* __restrict bs2,
        size_t n1,
        size_t n2,
        hamdis_t* __restrict dis)

{
    size_t i, j;
    const size_t nwords = nbits / 64;
    for (i = 0; i < n1; i++) {
        const uint64_t* __restrict bs1_ = bs1 + i * nwords;
        hamdis_t* __restrict dis_ = dis + i * n2;
        for (j = 0; j < n2; j++)
            dis_[j] = hamming<nbits>(bs1_, bs2 + j * nwords);
    }
}

void hammings(
        const uint64_t* __restrict bs1,
        const uint64_t* __restrict bs2,
        size_t n1,
        size_t n2,
        size_t nwords,
        hamdis_t* __restrict dis) {
    size_t i, j;
    n1 *= nwords;
    n2 *= nwords;
    for (i = 0; i < n1; i += nwords) {
        const uint64_t* bs1_ = bs1 + i;
        for (j = 0; j < n2; j += nwords)
            dis[j] = hamming(bs1_, bs2 + j, nwords);
    }
}

/* Count number of matches given a max threshold */
template <size_t nbits>
void hamming_count_thres(
        const uint64_t* __restrict bs1,
        const uint64_t* __restrict bs2,
        size_t n1,
        size_t n2,
        hamdis_t ht,
        size_t* __restrict nptr) {
    const size_t nwords = nbits / 64;
    size_t i, j, posm = 0;
    const uint64_t* bs2_ = bs2;

    for (i = 0; i < n1; i++) {
        bs2 = bs2_;
        for (j = 0; j < n2; j++) {
            /* collect the match only if this satisfies the threshold */
            if (hamming<nbits>(bs1, bs2) <= ht)
                posm++;
            bs2 += nwords;
        }
        bs1 += nwords; /* next signature */
    }
    *nptr = posm;
}

template <size_t nbits>
void crosshamming_count_thres(
        const uint64_t* __restrict dbs,
        size_t n,
        int ht,
        size_t* __restrict nptr) {
    const size_t nwords = nbits / 64;
    size_t i, j, posm = 0;
    const uint64_t* bs1 = dbs;
    for (i = 0; i < n; i++) {
        const uint64_t* bs2 = bs1 + 2;
        for (j = i + 1; j < n; j++) {
            /* collect the match only if this satisfies the threshold */
            if (hamming<nbits>(bs1, bs2) <= ht)
                posm++;
            bs2 += nwords;
        }
        bs1 += nwords;
    }
    *nptr = posm;
}

template <size_t nbits>
size_t match_hamming_thres(
        const uint64_t* __restrict bs1,
        const uint64_t* __restrict bs2,
        size_t n1,
        size_t n2,
        int ht,
        int64_t* __restrict idx,
        hamdis_t* __restrict hams) {
    const size_t nwords = nbits / 64;
    size_t i, j, posm = 0;
    hamdis_t h;
    const uint64_t* bs2_ = bs2;
    for (i = 0; i < n1; i++) {
        bs2 = bs2_;
        for (j = 0; j < n2; j++) {
            /* Here perform the real work of computing the distance */
            h = hamming<nbits>(bs1, bs2);

            /* collect the match only if this satisfies the threshold */
            if (h <= ht) {
                /* Enough space to store another match ? */
                *idx = i;
                idx++;
                *idx = j;
                idx++;
                *hams = h;
                hams++;
                posm++;
            }
            bs2 += nwords; /* next signature */
        }
        bs1 += nwords;
    }
    return posm;
}

namespace {

/* Return closest neighbors w.r.t Hamming distance, using a heap. */
template <class HammingComputer>
void hammings_knn_hc(
        int bytes_per_code,
        int_maxheap_array_t* __restrict ha,
        const uint8_t* __restrict bs1,
        const uint8_t* __restrict bs2,
        size_t n2,
        bool order = true,
        bool init_heap = true,
        ApproxTopK_mode_t approx_topk_mode = ApproxTopK_mode_t::EXACT_TOPK) {
    size_t k = ha->k;
    if (init_heap)
        ha->heapify();

    const size_t block_size = hamming_batch_size;
    for (size_t j0 = 0; j0 < n2; j0 += block_size) {
        const size_t j1 = std::min(j0 + block_size, n2);
#pragma omp parallel for
        for (int64_t i = 0; i < ha->nh; i++) {
            HammingComputer hc(bs1 + i * bytes_per_code, bytes_per_code);

            const uint8_t* __restrict bs2_ = bs2 + j0 * bytes_per_code;
            hamdis_t dis;
            hamdis_t* __restrict bh_val_ = ha->val + i * k;
            int64_t* __restrict bh_ids_ = ha->ids + i * k;

            // if larger number of k is required, then ::bs_addn() needs to be
            // used instead of ::addn()
#define HANDLE_APPROX(NB, BD)                                                \
    case ApproxTopK_mode_t::APPROX_TOPK_BUCKETS_B##NB##_D##BD:               \
        FAISS_THROW_IF_NOT_FMT(                                              \
                k <= NB * BD,                                                \
                "The chosen mode (%d) of approximate top-k supports "        \
                "up to %d values, but %zd is requested.",                    \
                (int)(ApproxTopK_mode_t::APPROX_TOPK_BUCKETS_B##NB##_D##BD), \
                NB * BD,                                                     \
                k);                                                          \
        HeapWithBucketsForHamming32<                                         \
                CMax<hamdis_t, int64_t>,                                     \
                NB,                                                          \
                BD,                                                          \
                HammingComputer>::                                           \
                addn(j1 - j0, hc, bs2_, k, bh_val_, bh_ids_);                \
        break;

            switch (approx_topk_mode) {
                HANDLE_APPROX(8, 3)
                HANDLE_APPROX(8, 2)
                HANDLE_APPROX(16, 2)
                HANDLE_APPROX(32, 2)
                default: {
                    for (size_t j = j0; j < j1; j++, bs2_ += bytes_per_code) {
                        dis = hc.hamming(bs2_);
                        if (dis < bh_val_[0]) {
                            faiss::maxheap_replace_top<hamdis_t>(
                                    k, bh_val_, bh_ids_, dis, j);
                        }
                    }
                } break;
            }
        }
    }
    if (order)
        ha->reorder();
}

/* Return closest neighbors w.r.t Hamming distance, using max count. */
template <class HammingComputer>
void hammings_knn_mc(
        int bytes_per_code,
        const uint8_t* __restrict a,
        const uint8_t* __restrict b,
        size_t na,
        size_t nb,
        size_t k,
        int32_t* __restrict distances,
        int64_t* __restrict labels) {
    const int nBuckets = bytes_per_code * 8 + 1;
    std::vector<int> all_counters(na * nBuckets, 0);
    std::unique_ptr<int64_t[]> all_ids_per_dis(new int64_t[na * nBuckets * k]);

    std::vector<HCounterState<HammingComputer>> cs;
    for (size_t i = 0; i < na; ++i) {
        cs.push_back(HCounterState<HammingComputer>(
                all_counters.data() + i * nBuckets,
                all_ids_per_dis.get() + i * nBuckets * k,
                a + i * bytes_per_code,
                8 * bytes_per_code,
                k));
    }

    const size_t block_size = hamming_batch_size;
    for (size_t j0 = 0; j0 < nb; j0 += block_size) {
        const size_t j1 = std::min(j0 + block_size, nb);
#pragma omp parallel for
        for (int64_t i = 0; i < na; ++i) {
            for (size_t j = j0; j < j1; ++j) {
                cs[i].update_counter(b + j * bytes_per_code, j);
            }
        }
    }

    for (size_t i = 0; i < na; ++i) {
        HCounterState<HammingComputer>& csi = cs[i];

        int nres = 0;
        for (int b = 0; b < nBuckets && nres < k; b++) {
            for (int l = 0; l < csi.counters[b] && nres < k; l++) {
                labels[i * k + nres] = csi.ids_per_dis[b * k + l];
                distances[i * k + nres] = b;
                nres++;
            }
        }
        while (nres < k) {
            labels[i * k + nres] = -1;
            distances[i * k + nres] = std::numeric_limits<int32_t>::max();
            ++nres;
        }
    }
}

template <class HammingComputer>
void hamming_range_search(
        const uint8_t* a,
        const uint8_t* b,
        size_t na,
        size_t nb,
        int radius,
        size_t code_size,
        RangeSearchResult* res) {
#pragma omp parallel
    {
        RangeSearchPartialResult pres(res);

#pragma omp for
        for (int64_t i = 0; i < na; i++) {
            HammingComputer hc(a + i * code_size, code_size);
            const uint8_t* yi = b;
            RangeQueryResult& qres = pres.new_result(i);

            for (size_t j = 0; j < nb; j++) {
                int dis = hc.hamming(yi);
                if (dis < radius) {
                    qres.add(dis, j);
                }
                yi += code_size;
            }
        }
        pres.finalize();
    }
}

struct Run_hammings_knn_hc {
    using T = void;
    template <class HammingComputer, class... Types>
    void f(Types... args) {
        hammings_knn_hc<HammingComputer>(args...);
    }
};

struct Run_hammings_knn_mc {
    using T = void;
    template <class HammingComputer, class... Types>
    void f(Types... args) {
        hammings_knn_mc<HammingComputer>(args...);
    }
};

struct Run_hamming_range_search {
    using T = void;
    template <class HammingComputer, class... Types>
    void f(Types... args) {
        hamming_range_search<HammingComputer>(args...);
    }
};

} // namespace

/* Functions to maps vectors to bits. Assume proper allocation done beforehand,
   meaning that b should be be able to receive as many bits as x may produce. */

/*
 * dimension 0 corresponds to the least significant bit of b[0], or
 * equivalently to the lsb of the first byte that is stored.
 */
void fvec2bitvec(const float* __restrict x, uint8_t* __restrict b, size_t d) {
    for (int i = 0; i < d; i += 8) {
        uint8_t w = 0;
        uint8_t mask = 1;
        int nj = i + 8 <= d ? 8 : d - i;
        for (int j = 0; j < nj; j++) {
            if (x[i + j] >= 0)
                w |= mask;
            mask <<= 1;
        }
        *b = w;
        b++;
    }
}

/* Same but for n vectors.
   Ensure that the ouptut b is byte-aligned (pad with 0s). */
void fvecs2bitvecs(
        const float* __restrict x,
        uint8_t* __restrict b,
        size_t d,
        size_t n) {
    const int64_t ncodes = ((d + 7) / 8);
#pragma omp parallel for if (n > 100000)
    for (int64_t i = 0; i < n; i++)
        fvec2bitvec(x + i * d, b + i * ncodes, d);
}

void bitvecs2fvecs(
        const uint8_t* __restrict b,
        float* __restrict x,
        size_t d,
        size_t n) {
    const int64_t ncodes = ((d + 7) / 8);
#pragma omp parallel for if (n > 100000)
    for (int64_t i = 0; i < n; i++) {
        binary_to_real(d, b + i * ncodes, x + i * d);
    }
}

/* Reverse bit (NOT a optimized function, only used for print purpose) */
static uint64_t uint64_reverse_bits(uint64_t b) {
    int i;
    uint64_t revb = 0;
    for (i = 0; i < 64; i++) {
        revb <<= 1;
        revb |= b & 1;
        b >>= 1;
    }
    return revb;
}

/* print the bit vector */
void bitvec_print(const uint8_t* b, size_t d) {
    size_t i, j;
    for (i = 0; i < d;) {
        uint64_t brev = uint64_reverse_bits(*(uint64_t*)b);
        for (j = 0; j < 64 && i < d; j++, i++) {
            printf("%d", (int)(brev & 1));
            brev >>= 1;
        }
        b += 8;
        printf(" ");
    }
}

void bitvec_shuffle(
        size_t n,
        size_t da,
        size_t db,
        const int* __restrict order,
        const uint8_t* __restrict a,
        uint8_t* __restrict b) {
    for (size_t i = 0; i < db; i++) {
        FAISS_THROW_IF_NOT(order[i] >= 0 && order[i] < da);
    }
    size_t lda = (da + 7) / 8;
    size_t ldb = (db + 7) / 8;

#pragma omp parallel for if (n > 10000)
    for (int64_t i = 0; i < n; i++) {
        const uint8_t* ai = a + i * lda;
        uint8_t* bi = b + i * ldb;
        memset(bi, 0, ldb);
        for (size_t j = 0; j < db; j++) {
            int o = order[j];
            uint8_t the_bit = (ai[o >> 3] >> (o & 7)) & 1;
            bi[j >> 3] |= the_bit << (j & 7);
        }
    }
}

/*----------------------------------------*/
/* Hamming distance computation and k-nn  */

#define C64(x) ((uint64_t*)x)

/* Compute a set of Hamming distances */
void hammings(
        const uint8_t* __restrict a,
        const uint8_t* __restrict b,
        size_t na,
        size_t nb,
        size_t ncodes,
        hamdis_t* __restrict dis) {
    FAISS_THROW_IF_NOT(ncodes % 8 == 0);
    switch (ncodes) {
        case 8:
            faiss::hammings<64>(C64(a), C64(b), na, nb, dis);
            return;
        case 16:
            faiss::hammings<128>(C64(a), C64(b), na, nb, dis);
            return;
        case 32:
            faiss::hammings<256>(C64(a), C64(b), na, nb, dis);
            return;
        case 64:
            faiss::hammings<512>(C64(a), C64(b), na, nb, dis);
            return;
        default:
            faiss::hammings(C64(a), C64(b), na, nb, ncodes * 8, dis);
            return;
    }
}

void hammings_knn(
        int_maxheap_array_t* __restrict ha,
        const uint8_t* __restrict a,
        const uint8_t* __restrict b,
        size_t nb,
        size_t ncodes,
        int order) {
    hammings_knn_hc(ha, a, b, nb, ncodes, order);
}

void hammings_knn_hc(
        int_maxheap_array_t* __restrict ha,
        const uint8_t* __restrict a,
        const uint8_t* __restrict b,
        size_t nb,
        size_t ncodes,
        int order,
        ApproxTopK_mode_t approx_topk_mode) {
    Run_hammings_knn_hc r;
    dispatch_HammingComputer(
            ncodes, r, ncodes, ha, a, b, nb, order, true, approx_topk_mode);
}

void hammings_knn_mc(
        const uint8_t* __restrict a,
        const uint8_t* __restrict b,
        size_t na,
        size_t nb,
        size_t k,
        size_t ncodes,
        int32_t* __restrict distances,
        int64_t* __restrict labels) {
    Run_hammings_knn_mc r;
    dispatch_HammingComputer(
            ncodes, r, ncodes, a, b, na, nb, k, distances, labels);
}

void hamming_range_search(
        const uint8_t* a,
        const uint8_t* b,
        size_t na,
        size_t nb,
        int radius,
        size_t code_size,
        RangeSearchResult* result) {
    Run_hamming_range_search r;
    dispatch_HammingComputer(
            code_size, r, a, b, na, nb, radius, code_size, result);
}

/* Count number of matches given a max threshold            */
void hamming_count_thres(
        const uint8_t* bs1,
        const uint8_t* bs2,
        size_t n1,
        size_t n2,
        hamdis_t ht,
        size_t ncodes,
        size_t* nptr) {
    switch (ncodes) {
        case 8:
            faiss::hamming_count_thres<64>(
                    C64(bs1), C64(bs2), n1, n2, ht, nptr);
            return;
        case 16:
            faiss::hamming_count_thres<128>(
                    C64(bs1), C64(bs2), n1, n2, ht, nptr);
            return;
        case 32:
            faiss::hamming_count_thres<256>(
                    C64(bs1), C64(bs2), n1, n2, ht, nptr);
            return;
        case 64:
            faiss::hamming_count_thres<512>(
                    C64(bs1), C64(bs2), n1, n2, ht, nptr);
            return;
        default:
            FAISS_THROW_FMT("not implemented for %zu bits", ncodes);
    }
}

/* Count number of cross-matches given a threshold */
void crosshamming_count_thres(
        const uint8_t* dbs,
        size_t n,
        hamdis_t ht,
        size_t ncodes,
        size_t* nptr) {
    switch (ncodes) {
        case 8:
            faiss::crosshamming_count_thres<64>(C64(dbs), n, ht, nptr);
            return;
        case 16:
            faiss::crosshamming_count_thres<128>(C64(dbs), n, ht, nptr);
            return;
        case 32:
            faiss::crosshamming_count_thres<256>(C64(dbs), n, ht, nptr);
            return;
        case 64:
            faiss::crosshamming_count_thres<512>(C64(dbs), n, ht, nptr);
            return;
        default:
            FAISS_THROW_FMT("not implemented for %zu bits", ncodes);
    }
}

/* Returns all matches given a threshold */
size_t match_hamming_thres(
        const uint8_t* bs1,
        const uint8_t* bs2,
        size_t n1,
        size_t n2,
        hamdis_t ht,
        size_t ncodes,
        int64_t* idx,
        hamdis_t* dis) {
    switch (ncodes) {
        case 8:
            return faiss::match_hamming_thres<64>(
                    C64(bs1), C64(bs2), n1, n2, ht, idx, dis);
        case 16:
            return faiss::match_hamming_thres<128>(
                    C64(bs1), C64(bs2), n1, n2, ht, idx, dis);
        case 32:
            return faiss::match_hamming_thres<256>(
                    C64(bs1), C64(bs2), n1, n2, ht, idx, dis);
        case 64:
            return faiss::match_hamming_thres<512>(
                    C64(bs1), C64(bs2), n1, n2, ht, idx, dis);
        default:
            FAISS_THROW_FMT("not implemented for %zu bits", ncodes);
            return 0;
    }
}

#undef C64

/*************************************
 * generalized Hamming distances
 ************************************/

template <class HammingComputer>
static void hamming_dis_inner_loop(
        const uint8_t* __restrict ca,
        const uint8_t* __restrict cb,
        size_t nb,
        size_t code_size,
        int k,
        hamdis_t* __restrict bh_val_,
        int64_t* __restrict bh_ids_) {
    HammingComputer hc(ca, code_size);

    for (size_t j = 0; j < nb; j++) {
        int ndiff = hc.hamming(cb);
        cb += code_size;
        if (ndiff < bh_val_[0]) {
            maxheap_replace_top<hamdis_t>(k, bh_val_, bh_ids_, ndiff, j);
        }
    }
}

void generalized_hammings_knn_hc(
        int_maxheap_array_t* __restrict ha,
        const uint8_t* __restrict a,
        const uint8_t* __restrict b,
        size_t nb,
        size_t code_size,
        int ordered) {
    int na = ha->nh;
    int k = ha->k;

    if (ordered)
        ha->heapify();

#pragma omp parallel for
    for (int i = 0; i < na; i++) {
        const uint8_t* __restrict ca = a + i * code_size;
        const uint8_t* __restrict cb = b;

        hamdis_t* __restrict bh_val_ = ha->val + i * k;
        int64_t* __restrict bh_ids_ = ha->ids + i * k;

        switch (code_size) {
            case 8:
                hamming_dis_inner_loop<GenHammingComputer8>(
                        ca, cb, nb, 8, k, bh_val_, bh_ids_);
                break;
            case 16:
                hamming_dis_inner_loop<GenHammingComputer16>(
                        ca, cb, nb, 16, k, bh_val_, bh_ids_);
                break;
            case 32:
                hamming_dis_inner_loop<GenHammingComputer32>(
                        ca, cb, nb, 32, k, bh_val_, bh_ids_);
                break;
            default:
                hamming_dis_inner_loop<GenHammingComputerM8>(
                        ca, cb, nb, code_size, k, bh_val_, bh_ids_);
                break;
        }
    }

    if (ordered)
        ha->reorder();
}

} // namespace faiss
