package engine

import (
    "sync"
    "syscall"
    "unsafe"
)

// ModelConfig 模型配置
type ModelConfig struct {
    Path         string // 模型文件路径
    MemoryMode   string // 内存模式：mmap/load
    Quantization string // 量化类型：fp16/int8/int4
}

// ModelInstance 模型实例
type ModelInstance struct {
    config    *ModelConfig
    weights   []byte       // 权重数据
    mmapAddr  uintptr      // mmap地址
    refCount  int32        // 引用计数
    mu        sync.Mutex
    isLoaded  bool
}

// LoadModel 加载模型
func LoadModel(cfg *ModelConfig) (*ModelInstance, error) {
    inst := &ModelInstance{
        config: cfg,
    }

    switch cfg.MemoryMode {
    case "mmap":
        // 使用内存映射加载模型，支持大文件零拷贝
        fd, err := syscall.Open(cfg.Path, syscall.O_RDONLY, 0)
        if err != nil {
            return nil, err
        }
        defer syscall.Close(fd)

        // 获取文件大小
        stat := &syscall.Stat_t{}
        if err := syscall.Fstat(fd, stat); err != nil {
            return nil, err
        }
        fileSize := stat.Size

        // 映射到虚拟内存
        addr, err := syscall.Mmap(fd, 0, int(fileSize), 
            syscall.PROT_READ, syscall.MAP_SHARED)
        if err != nil {
            return nil, err
        }
        inst.mmapAddr = uintptr(unsafe.Pointer(&addr[0]))
        inst.weights = addr

    case "load":
        // 直接加载到内存，适合小模型
        data, err := os.ReadFile(cfg.Path)
        if err != nil {
            return nil, err
        }
        inst.weights = data
    }

    inst.isLoaded = true
    return inst, nil
}

// UnloadModel 卸载模型
func (m *ModelInstance) UnloadModel() error {
    m.mu.Lock()
    defer m.mu.Unlock()

    if !m.isLoaded {
        return nil
    }

    if m.config.MemoryMode == "mmap" {
        // 解除内存映射
        if err := syscall.Munmap(m.weights); err != nil {
            return err
        }
    }

    m.weights = nil
    m.isLoaded = false
    return nil
}

// GetWeightPointer 获取权重指针（零拷贝操作）
func (m *ModelInstance) GetWeightPointer(offset, size int) unsafe.Pointer {
    if m.config.MemoryMode == "mmap" {
        return unsafe.Pointer(m.mmapAddr + uintptr(offset))
    }
    return unsafe.Pointer(&m.weights[offset])
}

package quantization

import (
    "math"
    "unsafe"
)

// Int4Quantizer INT4量化器
type Int4Quantizer struct {
    scale float32   // 缩放因子
    zero  int8      // 零点偏移
}

// QuantizeInt4 将FP32权重量化为INT4
func (q *Int4Quantizer) QuantizeInt4(data []float32) []byte {
    // 计算动态范围
    minVal, maxVal := float32(math.Inf(1)), float32(math.Inf(-1))
    for _, v := range data {
        if v < minVal {
            minVal = v
        }
        if v > maxVal {
            maxVal = v
        }
    }

    // INT4范围[-7, 7]
    q.scale = (maxVal - minVal) / 14.0
    q.zero = int8(math.Round(float64(-minVal / q.scale)))

    // 打包为字节数组（每字节2个INT4值）
    packed := make([]byte, (len(data)+1)/2)
    for i := 0; i < len(data); i++ {
        quantized := int8(math.Round(float64(data[i] / q.scale))) + q.zero
        if quantized > 7 {
            quantized = 7
        } else if quantized < -7 {
            quantized = -7
        }

        // 低4位存储第一个值，高4位存储第二个值
        if i%2 == 0 {
            packed[i/2] = byte(quantized) & 0x0F
        } else {
            packed[i/2] |= byte(quantized) << 4
        }
    }
    return packed
}

// DequantizeInt4 反量化INT4到FP32
func (q *Int4Quantizer) DequantizeInt4(packed []byte) []float32 {
    result := make([]float32, len(packed)*2)
    for i := 0; i < len(packed); i++ {
        // 提取低4位
        low := int8(packed[i] & 0x0F)
        if low > 7 {
            low -= 16 // 符号扩展
        }
        result[i*2] = (float32(low) - float32(q.zero)) * q.scale

        // 提取高4位
        high := int8(packed[i] >> 4)
        if high > 7 {
            high -= 16
        }
        result[i*2+1] = (float32(high) - float32(q.zero)) * q.scale
    }
    return result
}

// Int4MatMul INT4矩阵乘法（优化实现）
func Int4MatMul(a []byte, b []byte, m, n, k int) []float32 {
    // a: m x k, b: k x n, 结果: m x n
    result := make([]float32, m*n)
    
    // 使用Go的并发特性进行分块计算
    blockSize := 64
    var wg sync.WaitGroup
    
    for i := 0; i < m; i += blockSize {
        for j := 0; j < n; j += blockSize {
            wg.Add(1)
            go func(iStart, jStart int) {
                defer wg.Done()
                iEnd := iStart + blockSize
                if iEnd > m {
                    iEnd = m
                }
                jEnd := jStart + blockSize
                if jEnd > n {
                    jEnd = n
                }
                
                // 计算子块
                for ii := iStart; ii < iEnd; ii++ {
                    for jj := jStart; jj < jEnd; jj++ {
                        var sum float32
                        for kk := 0; kk < k; kk++ {
                            // 手动展开INT4解包
                            aIdx := (ii*k + kk) / 2
                            bIdx := (kk*n + jj) / 2
                            
                            aVal := extractInt4(a[aIdx], (ii*k+kk)%2)
                            bVal := extractInt4(b[bIdx], (kk*n+jj)%2)
                            sum += float32(aVal) * float32(bVal)
                        }
                        result[ii*n+jj] = sum
                    }
                }
            }(i, j)
        }
    }
    wg.Wait()
    return result
}

// extractInt4 从打包字节中提取INT4值
func extractInt4(packed byte, isHigh bool) int8 {
    var val int8
    if isHigh {
        val = int8(packed >> 4)
    } else {
        val = int8(packed & 0x0F)
    }
    // 符号扩展
    if val > 7 {
        val -= 16
    }
    return val
}

package scheduler

import (
    "container/heap"
    "sync"
    "time"
)

// Priority 请求优先级
type Priority int

const (
    PriorityLow    Priority = 0
    PriorityNormal Priority = 1
    PriorityHigh   Priority = 2
)

// InferenceRequest 推理请求
type InferenceRequest struct {
    ID        string
    Input     []int32
    Priority  Priority
    Deadline  time.Time
    ResultCh  chan *InferenceResult
}

// InferenceResult 推理结果
type InferenceResult struct {
    RequestID string
    Output    []float32
    Latency   time.Duration
    Error     error
}

// PriorityQueue 优先级队列
type PriorityQueue []*InferenceRequest

func (pq PriorityQueue) Len() int { return len(pq) }

func (pq PriorityQueue) Less(i, j int) bool {
    if pq[i].Priority != pq[j].Priority {
        return pq[i].Priority > pq[j].Priority // 高优先级在前
    }
    return pq[i].Deadline.Before(pq[j].Deadline) // 截止时间早的在前
}

func (pq PriorityQueue) Swap(i, j int) {
    pq[i], pq[j] = pq[j], pq[i]
}

func (pq *PriorityQueue) Push(x interface{}) {
    *pq = append(*pq, x.(*InferenceRequest))
}

func (pq *PriorityQueue) Pop() interface{} {
    old := *pq
    n := len(old)
    item := old[n-1]
    *pq = old[0 : n-1]
    return item
}

// Scheduler 推理调度器
type Scheduler struct {
    queue      PriorityQueue
    mu         sync.Mutex
    cond       *sync.Cond
    maxWorkers int
    workers    []*worker
    stopCh     chan struct{}
}

// worker 工作协程
type worker struct {
    id      int
    engine  *InferenceEngine
    sched   *Scheduler
}

// NewScheduler 创建调度器
func NewScheduler(maxWorkers int) *Scheduler {
    s := &Scheduler{
        queue:      make(PriorityQueue, 0),
        maxWorkers: maxWorkers,
        stopCh:     make(chan struct{}),
    }
    s.cond = sync.NewCond(&s.mu)
    
    // 创建工作协程
    for i := 0; i < maxWorkers; i++ {
        w := &worker{
            id:    i,
            sched: s,
        }
        s.workers = append(s.workers, w)
        go w.run()
    }
    
    return s
}

// Submit 提交推理请求
func (s *Scheduler) Submit(req *InferenceRequest) {
    s.mu.Lock()
    heap.Push(&s.queue, req)
    s.mu.Unlock()
    s.cond.Signal() // 唤醒一个等待的工作协程
}

// worker.run 工作协程主循环
func (w *worker) run() {
    for {
        w.sched.mu.Lock()
        // 等待队列中有请求
        for w.sched.queue.Len() == 0 {
            w.sched.cond.Wait()
            select {
            case <-w.sched.stopCh:
                w.sched.mu.Unlock()
                return
            default:
            }
        }
        
        // 获取最高优先级请求
        req := heap.Pop(&w.sched.queue).(*InferenceRequest)
        w.sched.mu.Unlock()
        
        // 执行推理
        start := time.Now()
        result, err := w.engine.Infer(req.Input)
        latency := time.Since(start)
        
        // 返回结果
        if req.ResultCh != nil {
            req.ResultCh <- &InferenceResult{
                RequestID: req.ID,
                Output:    result,
                Latency:   latency,
                Error:     err,
            }
        }
    }
}

// Stop 停止调度器
func (s *Scheduler) Stop() {
    close(s.stopCh)
    s.cond.Broadcast() // 唤醒所有等待的协程
}

/*
#include "fused_kernels.h"
*/
import "C"

func fusedLayerNormAddGeLU(input, residual, gamma, beta []float32, 
    batch, hidden int) []float32 {
    output := make([]float32, len(input))
    C.fused_ln_add_gelu(
        (*C.float)(&input[0]),
        (*C.float)(&residual[0]),
        (*C.float)(&gamma[0]),
        (*C.float)(&beta[0]),
        (*C.float)(&output[0]),
        C.int(batch),
        C.int(hidden),
    )
    return output
}

package memory

import (
    "sync"
)

// BufferPool 缓冲区池
type BufferPool struct {
    pools map[int]*sync.Pool // key为缓冲区大小
    mu    sync.RWMutex
}

// NewBufferPool 创建缓冲区池
func NewBufferPool(sizes []int) *BufferPool {
    bp := &BufferPool{
        pools: make(map[int]*sync.Pool),
    }
    for _, size := range sizes {
        size := size // 捕获变量
        bp.pools[size] = &sync.Pool{
            New: func() interface{} {
                return make([]float32, size)
            },
        }
    }
    return bp
}

// Get 获取缓冲区
func (bp *BufferPool) Get(size int) []float32 {
    bp.mu.RLock()
    pool, ok := bp.pools[size]
    bp.mu.RUnlock()
    
    if !ok {
        // 动态创建新大小的池
        bp.mu.Lock()
        pool = &sync.Pool{
            New: func() interface{} {
                return make([]float32, size)
            },
        }
        bp.pools[size] = pool
        bp.mu.Unlock()
    }
    
    return pool.Get().([]float32)
}

// Put 归还缓冲区
func (bp *BufferPool) Put(buf []float32) {
    size := cap(buf)
    bp.mu.RLock()
    pool, ok := bp.pools[size]
    bp.mu.RUnlock()
    
    if ok {
        // 清空缓冲区但不释放内存
        for i := range buf {
            buf[i] = 0
        }
        pool.Put(buf)
    }
}

// BatchManager 批处理管理器
type BatchManager struct {
    maxBatchSize int
    timeout      time.Duration
    buffer       []*InferenceRequest
    mu           sync.Mutex
    cond         *sync.Cond
}

// Run 启动批处理循环
func (bm *BatchManager) Run() {
    ticker := time.NewTicker(bm.timeout)
    defer ticker.Stop()
    
    for {
        select {
        case <-ticker.C:
            bm.mu.Lock()
            if len(bm.buffer) > 0 {
                batch := bm.buffer
                bm.buffer = nil
                bm.mu.Unlock()
                bm.processBatch(batch)
            } else {
                bm.mu.Unlock()
            }
        default:
            bm.mu.Lock()
            if len(bm.buffer) >= bm.maxBatchSize {
                batch := bm.buffer
                bm.buffer = nil
                bm.mu.Unlock()
                bm.processBatch(batch)
            } else {
                bm.mu.Unlock()
                time.Sleep(1 * time.Millisecond)
            }
        }
    }
}

// processBatch 处理批次
func (bm *BatchManager) processBatch(requests []*InferenceRequest) {
    // 将多个输入拼接为批次
    batchInput := make([][]int32, len(requests))
    for i, req := range requests {
        batchInput[i] = req.Input
    }
    
    // 执行批量推理
    results := bm.engine.BatchInfer(batchInput)
    
    // 分发结果
    for i, req := range requests {
        req.ResultCh <- &InferenceResult{
            RequestID: req.ID,
            Output:    results[i],
        }
    }
}

# docker-compose.yaml
version: '3.8'
services:
  inference-engine:
    image: edge-slm:1.0
    ports:
      - "8080:8080"
    volumes:
      - ./models:/models
    environment:
      - MODEL_PATH=/models/phi-3-mini-int4.bin
      - MEMORY_MODE=mmap
      - MAX_BATCH_SIZE=4
      - WORKER_COUNT=2
    devices:
      - /dev/npu0:/dev/npu0  # 映射NPU设备
    deploy:
      resources:
        limits:
          cpus: '4'
          memory: 2G

// MetricsCollector 指标收集器
type MetricsCollector struct {
    latencyHistogram *prometheus.HistogramVec
    requestCounter   *prometheus.CounterVec
    memoryGauge      prometheus.Gauge
}

func NewMetricsCollector() *MetricsCollector {
    return &MetricsCollector{
        latencyHistogram: prometheus.NewHistogramVec(
            prometheus.HistogramOpts{
                Name:    "inference_latency_ms",
                Help:    "Inference latency in milliseconds",
                Buckets: []float64{50, 100, 200, 500, 1000},
            },
            []string{"model", "quantization"},
        ),
        requestCounter: prometheus.NewCounterVec(
            prometheus.CounterOpts{
                Name: "inference_requests_total",
                Help: "Total number of inference requests",
            },
            []string{"status"},
        ),
        memoryGauge: prometheus.NewGauge(
            prometheus.GaugeOpts{
                Name: "model_memory_bytes",
                Help: "Current model memory usage",
            },
        ),
    }
}

// RecordLatency 记录延迟
func (mc *MetricsCollector) RecordLatency(model, quantization string, latency time.Duration) {
    mc.latencyHistogram.WithLabelValues(model, quantization).
        Observe(float64(latency.Milliseconds()))
}