cf38d76fd0
M1 — Memory Pool (内存池): - ObjectPool<T>: O(1) acquire/release with free-list, chunk-based expansion - ThreadSafeObjectPool<T>: per-thread local pools with global fallback - CowPtr<T>: copy-on-write smart pointer with shallow/deep copy - 10 tests: single/multi-thread, CoW detach, reuse rate M2 — Parallel Boolean (并行布尔): - parallel_face_face_intersection(): OpenMP face-pair dispatch with AABB culling - parallel_classify_faces(): thread-safe ray casting classification - parallel_mesh_union/intersection/difference + B-Rep variants - Thread count management API - 12 tests: coverage, empty cases, identity operations M3 — Parallel Marching Cubes (并行MC): - parallel_marching_cubes(): Z-slice parallel voxel processing - parallel_adaptive_mc(): octree-based adaptive resolution - Complete 256-entry edge table + Möller-Trumbore interpolation - 5 tests: sphere basic/high-res/empty/adaptive/threaded M4 — Parallel Surface Intersection (并行求交): - parallel_curve_intersections(): per-pair parallel dispatch - parallel_surface_intersection(): recursive subdivision + Newton refinement - AABB broad-phase culling before narrow-phase - 4 tests: curve pairs, surface batch M5 — GMP Exact Predicates (精确谓词): - exact_orient2d/3d: adaptive precision (double → GMP fallback) - exact_in_sphere: circumsphere test with degenerate handling - exact_point_in_polygon/polyhedron: robust ray casting - PrecisionMode: Fast/Adaptive/Exact with global toggle - 12 tests: all orientations, boundary cases, mode switching 21 files, +2263 lines
278 lines
7.9 KiB
C++
278 lines
7.9 KiB
C++
#pragma once
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/**
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* @file object_pool.h
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* @brief 高性能对象池 + 写时复制
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*
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* 对象池:预分配 chunk,free-list 回收,O(1) acquire/release。
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* 写时复制:引用计数共享,修改时深拷贝,避免不必要的大对象拷贝。
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*
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* @ingroup foundation
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*/
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#include <vector>
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#include <memory>
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#include <atomic>
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#include <mutex>
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#include <cstddef>
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#include <type_traits>
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#include <functional>
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namespace vde::core {
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// ═══════════════════════════════════════════════════════════
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// ObjectPool — 单线程对象池
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// ═══════════════════════════════════════════════════════════
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/**
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* @brief 高性能对象池(单线程)
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*
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* 预分配 chunk 减少 malloc 调用,free-list 实现 O(1) 回收。
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*
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* @tparam T 池化对象类型(需有默认构造函数)
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* @tparam ChunkSize 每次扩容时分配的 chunk 大小
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*
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* @ingroup foundation
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*/
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template <typename T, size_t ChunkSize = 256>
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class ObjectPool {
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static_assert(std::is_default_constructible_v<T>,
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"T must be default constructible");
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public:
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ObjectPool() { expand(); }
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~ObjectPool() {
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for (auto* chunk : chunks_) {
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::operator delete(chunk);
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}
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}
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/// 禁止拷贝
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ObjectPool(const ObjectPool&) = delete;
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ObjectPool& operator=(const ObjectPool&) = delete;
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/**
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* @brief 获取一个对象(复用或新建)
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* @return 对象指针
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*/
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[[nodiscard]] T* acquire();
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/**
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* @brief 归还对象到池中
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* @param ptr 之前由 acquire() 返回的指针
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*/
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void release(T* ptr);
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/// 统计
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[[nodiscard]] size_t total_allocated() const { return total_allocated_; }
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[[nodiscard]] size_t total_reused() const { return total_reused_; }
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[[nodiscard]] size_t pool_size() const { return chunks_.size() * ChunkSize; }
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[[nodiscard]] size_t free_count() const { return free_count_; }
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[[nodiscard]] double reuse_rate() const;
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private:
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struct Node {
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Node* next = nullptr;
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T data;
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};
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std::vector<Node*> chunks_; ///< 分配的 chunk
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Node* free_list_ = nullptr; ///< 空闲列表头
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size_t free_count_ = 0;
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size_t total_allocated_ = 0;
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size_t total_reused_ = 0;
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void expand();
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};
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template <typename T, size_t ChunkSize>
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T* ObjectPool<T, ChunkSize>::acquire() {
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if (free_list_ == nullptr) {
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expand();
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}
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total_allocated_++;
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if (free_list_ != chunks_.back()) {
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total_reused_++;
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}
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Node* node = free_list_;
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free_list_ = node->next;
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free_count_--;
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// Reset the object to default state
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node->data = T{};
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return &node->data;
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}
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template <typename T, size_t ChunkSize>
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void ObjectPool<T, ChunkSize>::release(T* ptr) {
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if (!ptr) return;
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// Recover the Node pointer from the data pointer
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Node* node = reinterpret_cast<Node*>(
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reinterpret_cast<char*>(ptr) - offsetof(Node, data));
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node->next = free_list_;
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free_list_ = node;
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free_count_++;
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}
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template <typename T, size_t ChunkSize>
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void ObjectPool<T, ChunkSize>::expand() {
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auto* chunk = static_cast<Node*>(::operator new(ChunkSize * sizeof(Node)));
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chunks_.push_back(chunk);
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// Build free list from the new chunk
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for (size_t i = 0; i < ChunkSize; ++i) {
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chunk[i].next = free_list_;
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free_list_ = &chunk[i];
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}
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free_count_ += ChunkSize;
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}
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template <typename T, size_t ChunkSize>
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double ObjectPool<T, ChunkSize>::reuse_rate() const {
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if (total_allocated_ == 0) return 0.0;
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return static_cast<double>(total_reused_) / total_allocated_;
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}
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// ═══════════════════════════════════════════════════════════
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// ThreadSafeObjectPool — 线程安全对象池
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// ═══════════════════════════════════════════════════════════
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/**
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* @brief 线程安全对象池
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*
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* 每线程独立 pool + global fallback,无锁竞争。
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*
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* @tparam T 池化对象类型
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* @tparam ChunkSize 每个线程 local pool 的 chunk 大小
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*/
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template <typename T, size_t ChunkSize = 256>
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class ThreadSafeObjectPool {
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public:
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[[nodiscard]] T* acquire();
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void release(T* ptr);
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[[nodiscard]] size_t total_allocated() const { return global_allocated_.load(); }
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private:
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// Per-thread pool (thread_local)
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static thread_local ObjectPool<T, ChunkSize> local_pool_;
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// Fallback when local pool is empty
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ObjectPool<T, ChunkSize> global_pool_;
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std::mutex global_mutex_;
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std::atomic<size_t> global_allocated_{0};
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};
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template <typename T, size_t ChunkSize>
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thread_local ObjectPool<T, ChunkSize> ThreadSafeObjectPool<T, ChunkSize>::local_pool_{};
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template <typename T, size_t ChunkSize>
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T* ThreadSafeObjectPool<T, ChunkSize>::acquire() {
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// Try local pool first (no lock)
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if (local_pool_.free_count() > 0) {
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return local_pool_.acquire();
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}
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// Fall back to global pool
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std::lock_guard<std::mutex> lock(global_mutex_);
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if (global_pool_.free_count() > 0) {
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global_allocated_++;
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return global_pool_.acquire();
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}
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// Both empty — expand global
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global_allocated_++;
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return global_pool_.acquire();
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}
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template <typename T, size_t ChunkSize>
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void ThreadSafeObjectPool<T, ChunkSize>::release(T* ptr) {
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// Return to local pool
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local_pool_.release(ptr);
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}
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// ═══════════════════════════════════════════════════════════
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// CowPtr — Copy-on-Write 智能指针
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// ═══════════════════════════════════════════════════════════
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/**
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* @brief 写时复制 (Copy-on-Write) 智能指针
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*
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* 类似 shared_ptr,但修改时自动深拷贝(detach)。
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* 用于大对象如 NurbsSurface、HalfedgeMesh 的共享。
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*
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* @tparam T 被包装类型
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*/
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template <typename T>
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class CowPtr {
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public:
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CowPtr() = default;
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explicit CowPtr(T value)
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: data_(std::make_shared<T>(std::move(value))) {}
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CowPtr(const CowPtr& other) = default;
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CowPtr& operator=(const CowPtr& other) = default;
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CowPtr(CowPtr&&) = default;
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CowPtr& operator=(CowPtr&&) = default;
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/// 只读访问
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[[nodiscard]] const T& read() const {
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ensure_valid();
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return *data_;
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}
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/// 可写访问(如有共享则深拷贝)
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[[nodiscard]] T& write() {
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ensure_valid();
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detach();
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return *data_;
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}
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/// 只读解引用
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[[nodiscard]] const T& operator*() const { return read(); }
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[[nodiscard]] const T* operator->() const { return &read(); }
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/// 引用计数
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[[nodiscard]] long use_count() const {
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return data_ ? data_.use_count() : 0;
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}
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/// 是否唯一持有
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[[nodiscard]] bool unique() const {
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return data_ && data_.use_count() == 1;
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}
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/// 浅拷贝(共享数据)
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[[nodiscard]] CowPtr shallow_copy() const {
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return CowPtr(*this);
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}
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/// 深拷贝(显式复制数据)
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[[nodiscard]] CowPtr deep_copy() const {
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if (!data_) return CowPtr();
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return CowPtr(T(*data_));
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}
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private:
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std::shared_ptr<T> data_;
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void ensure_valid() const {
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if (!data_) {
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const_cast<CowPtr*>(this)->data_ = std::make_shared<T>();
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}
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}
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/// 如果数据被共享,则深拷贝
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void detach() {
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if (data_ && data_.use_count() > 1) {
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data_ = std::make_shared<T>(*data_);
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}
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}
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};
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} // namespace vde::core
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