mirror of
https://github.com/nomic-ai/gpt4all.git
synced 2024-10-01 01:06:10 -04:00
200 lines
5.1 KiB
C++
200 lines
5.1 KiB
C++
#pragma once
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#ifndef NO_MANUAL_VECTORIZATION
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#if (defined(__SSE__) || _M_IX86_FP > 0 || defined(_M_AMD64) || defined(_M_X64))
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#define USE_SSE
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#ifdef __AVX__
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#define USE_AVX
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#ifdef __AVX512F__
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#define USE_AVX512
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#endif
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#endif
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#endif
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#endif
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#if defined(USE_AVX) || defined(USE_SSE)
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#ifdef _MSC_VER
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#include <intrin.h>
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#include <stdexcept>
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void cpuid(int32_t out[4], int32_t eax, int32_t ecx) {
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__cpuidex(out, eax, ecx);
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}
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static __int64 xgetbv(unsigned int x) {
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return _xgetbv(x);
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}
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#else
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#include <x86intrin.h>
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#include <cpuid.h>
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#include <stdint.h>
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static void cpuid(int32_t cpuInfo[4], int32_t eax, int32_t ecx) {
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__cpuid_count(eax, ecx, cpuInfo[0], cpuInfo[1], cpuInfo[2], cpuInfo[3]);
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}
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static uint64_t xgetbv(unsigned int index) {
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uint32_t eax, edx;
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__asm__ __volatile__("xgetbv" : "=a"(eax), "=d"(edx) : "c"(index));
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return ((uint64_t)edx << 32) | eax;
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}
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#endif
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#if defined(USE_AVX512)
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#include <immintrin.h>
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#endif
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#if defined(__GNUC__)
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#define PORTABLE_ALIGN32 __attribute__((aligned(32)))
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#define PORTABLE_ALIGN64 __attribute__((aligned(64)))
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#else
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#define PORTABLE_ALIGN32 __declspec(align(32))
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#define PORTABLE_ALIGN64 __declspec(align(64))
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#endif
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// Adapted from https://github.com/Mysticial/FeatureDetector
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#define _XCR_XFEATURE_ENABLED_MASK 0
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static bool AVXCapable() {
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int cpuInfo[4];
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// CPU support
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cpuid(cpuInfo, 0, 0);
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int nIds = cpuInfo[0];
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bool HW_AVX = false;
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if (nIds >= 0x00000001) {
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cpuid(cpuInfo, 0x00000001, 0);
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HW_AVX = (cpuInfo[2] & ((int)1 << 28)) != 0;
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}
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// OS support
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cpuid(cpuInfo, 1, 0);
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bool osUsesXSAVE_XRSTORE = (cpuInfo[2] & (1 << 27)) != 0;
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bool cpuAVXSuport = (cpuInfo[2] & (1 << 28)) != 0;
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bool avxSupported = false;
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if (osUsesXSAVE_XRSTORE && cpuAVXSuport) {
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uint64_t xcrFeatureMask = xgetbv(_XCR_XFEATURE_ENABLED_MASK);
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avxSupported = (xcrFeatureMask & 0x6) == 0x6;
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}
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return HW_AVX && avxSupported;
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}
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static bool AVX512Capable() {
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if (!AVXCapable()) return false;
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int cpuInfo[4];
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// CPU support
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cpuid(cpuInfo, 0, 0);
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int nIds = cpuInfo[0];
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bool HW_AVX512F = false;
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if (nIds >= 0x00000007) { // AVX512 Foundation
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cpuid(cpuInfo, 0x00000007, 0);
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HW_AVX512F = (cpuInfo[1] & ((int)1 << 16)) != 0;
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}
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// OS support
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cpuid(cpuInfo, 1, 0);
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bool osUsesXSAVE_XRSTORE = (cpuInfo[2] & (1 << 27)) != 0;
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bool cpuAVXSuport = (cpuInfo[2] & (1 << 28)) != 0;
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bool avx512Supported = false;
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if (osUsesXSAVE_XRSTORE && cpuAVXSuport) {
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uint64_t xcrFeatureMask = xgetbv(_XCR_XFEATURE_ENABLED_MASK);
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avx512Supported = (xcrFeatureMask & 0xe6) == 0xe6;
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}
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return HW_AVX512F && avx512Supported;
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}
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#endif
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#include <queue>
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#include <vector>
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#include <iostream>
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#include <string.h>
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namespace hnswlib {
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typedef size_t labeltype;
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// This can be extended to store state for filtering (e.g. from a std::set)
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class BaseFilterFunctor {
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public:
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virtual bool operator()(hnswlib::labeltype id) { return true; }
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};
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template <typename T>
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class pairGreater {
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public:
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bool operator()(const T& p1, const T& p2) {
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return p1.first > p2.first;
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}
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};
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template<typename T>
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static void writeBinaryPOD(std::ostream &out, const T &podRef) {
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out.write((char *) &podRef, sizeof(T));
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}
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template<typename T>
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static void readBinaryPOD(std::istream &in, T &podRef) {
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in.read((char *) &podRef, sizeof(T));
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}
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template<typename MTYPE>
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using DISTFUNC = MTYPE(*)(const void *, const void *, const void *);
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template<typename MTYPE>
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class SpaceInterface {
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public:
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// virtual void search(void *);
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virtual size_t get_data_size() = 0;
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virtual DISTFUNC<MTYPE> get_dist_func() = 0;
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virtual void *get_dist_func_param() = 0;
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virtual ~SpaceInterface() {}
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};
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template<typename dist_t>
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class AlgorithmInterface {
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public:
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virtual void addPoint(const void *datapoint, labeltype label, bool replace_deleted = false) = 0;
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virtual std::priority_queue<std::pair<dist_t, labeltype>>
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searchKnn(const void*, size_t, BaseFilterFunctor* isIdAllowed = nullptr) const = 0;
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// Return k nearest neighbor in the order of closer fist
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virtual std::vector<std::pair<dist_t, labeltype>>
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searchKnnCloserFirst(const void* query_data, size_t k, BaseFilterFunctor* isIdAllowed = nullptr) const;
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virtual void saveIndex(const std::string &location) = 0;
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virtual ~AlgorithmInterface(){
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}
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};
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template<typename dist_t>
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std::vector<std::pair<dist_t, labeltype>>
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AlgorithmInterface<dist_t>::searchKnnCloserFirst(const void* query_data, size_t k,
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BaseFilterFunctor* isIdAllowed) const {
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std::vector<std::pair<dist_t, labeltype>> result;
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// here searchKnn returns the result in the order of further first
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auto ret = searchKnn(query_data, k, isIdAllowed);
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{
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size_t sz = ret.size();
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result.resize(sz);
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while (!ret.empty()) {
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result[--sz] = ret.top();
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ret.pop();
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}
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}
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return result;
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}
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} // namespace hnswlib
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#include "space_l2.h"
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#include "space_ip.h"
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#include "bruteforce.h"
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#include "hnswalg.h"
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