// if not embedding then break const nlohmann::json& j = j_layers_array[i]; auto...>>& embeddings, Embedding_t embedding_type, const nlohmann::json& config, const std::shared_ptr<ResourceManager...= nullptr) { for (unsigned int i = 1; i < j_array.size(); i++) { // 遍历json数组 const nlohmann...::json& j = j_array[i]; const auto layer_type_name = get_value_from_json(j, "type");...static InputOutputInfo get_input_tensor_and_output_name( const nlohmann::json& json, const std::vector
observable &o, const std::shared_ptr& arg) = 0; }; using observer_ptr_type = std::shared_ptr...* * @param arg any object. */ void notifyObservers(const std::shared_ptr& arg)...) :tmpl_listener(tmpl_listener) {} virtual void update(const observable::observable &, const std::shared_ptr...************************* // 添加值改变侦听器 // @param const std::function& listener 侦听函数...::setValue(const nlohmann::json & optionValue) { fields[__J_NAME(value)] = optionValue; /** 当值被修改时调用
` 表示 可选字段 针对 可选字段 的 JSON 序列化/反序列化 扩展代码,见 `optional_json.h`(参考:How do I convert third-party types?...(const nlohmann::json& j, SimpleStruct& value) { j.at("_bool").get_to(value.bool_); j.at("_int")....= j.cend()) { j.at("_optional").get_to(value.optional_); } } void to_json(nlohmann::json& j, const...(const nlohmann::json& j, NestedStruct& value) { j.at("_nested").get_to(value.nested_); j.at("_vector.../反序列化操作,参考 How do I convert third-party types?
的 JSON 序列化/反序列化 扩展代码,见 `optional_json.h`(参考:How do I convert third-party types?...(const nlohmann::json& j, SimpleStruct& value) { j.at("_bool").get_to(value.bool_); j.at("_int")....= j.cend()) { j.at("_optional").get_to(value.optional_); } } void to_json(nlohmann::json& j, const...(const nlohmann::json& j, NestedStruct& value) { j.at("_nested").get_to(value.nested_); j.at("_vector.../反序列化操作,参考 How do I convert third-party types?
= 0; i < j_sparse.size(); i++) { const std::string& sparse_name = sparse_names[i]; // 根据名字找到...代码如下: const std::vector &get_sparse_tensors(const std::string &name) { if (output..., const nlohmann::json& config, const std::shared_ptr&..., float scaler, const nlohmann::json& j_layers,...auto bottom_name = get_value_from_json(j_layers, "bottom"); auto top_name = get_value_from_json
Logger get_node_logger (const rcl_node_t *node) Return a named logger using an rcl_node_t....&sub_namespace) std::string _to_json_dict_entry (const Parameter ¶m) Return a json...It's able to get a std::shared_ptr to a NodeBaseInterface so long as the class has a method called get_node_base_interface...This function can take any form of a topic or service name, i.e. it does not have to be a fully qualified...& sub_namespace ) inline ◆ _to_json_dict_entry() std::string rclcpp::_to_json_dict_entry
p_.reset(); } P const & get() const { return p_; } }; shared_ptr make_shared_from_another...int Data; std::map, Data> userData; // or std::map, Data> userData;...explicit pointer(T * p): p_(p) { } shared_ptr operator->() const { p_->prefix...X(X const & rhs): this_(this, null_deleter()), i_(rhs.i_) { } // do not forget to not assign...this_ in the copy assignment X & operator=(X const & rhs) { i_ = rhs.i_; }
(const json& j) { return{ j.template get() }; } static void to_json(json& j,...(const basic_json& j) { return{ j.template get() }; } template<template...= nlohmann::adl_serializer, \ class BinaryType = std::vector #endif // !...get() }; } _BASIC_JSON_TPL_DECLARATION_ static void to_json(_BASIC_JSON_TPL_& j,..."; // 保存到json j["uri"] = u; // 从json中读取uri对象 uri u2 = j["uri"].get(); std::cout << "u2:" <<
j["uri"] = u; // 从json中读取uri对象 uri u2 = j["uri"].get(); std::cout { static uri from_json(const json& j) { // 反序列化 // 从json中获取std::string,调用uri的构造函数 // uri...uri对象 return{ j.template get() }; } static void to_json(json& j, const uri &u) {...uri u2 = j["uri"].get(); std::cout << "u2:" << u2.to_string() << std::endl; }
************************************/ template auto Trie::Get(std::string_view key) const -...nullptr; } std::shared_ptr cur = this->root_; for (size_t i = 0; i < key.length..._; lock.unlock(); // 获取键值 const T *val = root.Get(key); // 封装 if (val !...Think of how you can achieve this. // The logic should be somehow similar to `TrieStore::Get`. //...Think of how you can achieve this. // The logic should be somehow similar to `TrieStore::Get`. //
virtual uint32_t writeI16_virt(const int16_t i16) = 0; virtual uint32_t writeI32_virt(const int32...Status Init() { for (int i = 0; i < num_threads_; ++i) { std::stringstream...std::string & name, const std::shared_ptr & processor, int port)...::shared_ptr ThriftThreadFactory::newThread(std::shared_ptr runnable) const...::shared_ptr runnable, Promise * promise) { promise->Set(get_current
::cout << v << std::endl; } // main function int main() { const int a = 42; increase_and_square...char *)Buffer.data(); const std::size_t BufLen = Buffer.size(); unsigned I = 0; while (I < BufLen)...还是介绍json库,这个json库有insert_order的功能,这个json标准是不保证的 int main() { { nlohmann::json json{}; json["value..."] = 42; json["array"] = std::array{1, 2, 3}; std::cout << json.dump(); // prints {"array":[1,2,3...],"value":42} } { nlohmann::ordered_json json{}; json["value"] = 42; json["array"] = std::
" using json = nlohmann::json; using namespace std; using namespace placeholders; ChatServer::ChatServer..." using json = nlohmann::json; using namespace std; using namespace muduo; using namespace muduo::net...; //处理消息的事件回调方法类型 using MsgHandler = std::function<void(const TcpConnectionPtr &conn,json &js,Timestamp...TcpConnectionPtr &conn,json &js,Timestamp time); void reg(const TcpConnectionPtr &conn,json &js,...TcpConnectionPtr &conn,json &js,Timestamp time){ LOG_ERROR<<"msgid:"<<msgid<<"can not find
#include using json = nlohmann::json; using namespace std; using namespace placeholders...()->getHandle(js["msgid"].get()); //回调消息绑定好的事件处理器,执行相应的业务处理 msgHandler(conn,js,time...typedef std::function ConnectionCallback; ConnectionCallback 是一个函数对象,...typedef std::shared_ptr TcpConnectionPtr; 再多久不用说啦,说下去没完没了的了。...// the data has been read to (buf, len) typedef std::function<void (const TcpConnectionPtr&,
当然,对于不同的裸指针的 std::shared_ptr 实例,更是线程安全的 这里的 “成员函数” 指的是 std::shared_ptr 的成员函数,比如 get ()、reset ()、 operrator...reset non-const swap non-const get const operator*、operator-> const operator const use_count const unique...::make_shared(); std::vector operations; for (int i = 0; i std::shared_ptr atomic_exchange( std::shared_ptr* p, std...::shared_ptr r);
的定义如下: //torch/csrc/autograd/variable.cpp std::shared_ptr try_get_grad_accumulator(const Variable...const std::shared_ptr& graph_task, std::shared_ptr graph_root) override; std...>(); for (int i = 0; i < num_devices; ++i) { std::thread t(&Engine::thread_init, this, i, device_ready_queues..._[i], true); t.detach(); } // Wait for the threads to start { std::unique_lock& graph_task, Node* func, InputBuffer& inputs, const std::shared_ptr
DEM是栅格数据,可以通过GDAL进行读取;gltf是一种JSON格式,可以采用nlohmann/json进行读写。 2....include "fifo_map.hpp" #include using namespace std; using namespace nlohmann;...img) { printf("Can't Open Image!")...3.原生的nlohmann/json组件写出来的JSON格式是根据字符串顺序排序不是根据插入顺序排序的,查阅的时候不方便。所以这里使用了nlohmann::fifo_map容器专门化对象类型。 3....参考 [1] github上的gltf教程 [2] gltf教程中文翻译 [3] nlohmann/json关于保留插入顺序的讨论
}; // Good Idea class MyClass { public: void do_something(const int i); void do_something(const...m_int_value(t_int_value) { } const int& get_int_value() const { return m_int_value; }...int t_int_value) : m_int_value(t_int_value) { } int get_int_value() const { return...另外,避免使用```std::shared_ptr```保存数组[4]。 使用异常 返回值(例如boost::optional),可以被忽略,如果不检查,可能会导致崩溃或内存错误,而异常不能被忽略。...::shared_ptr保存数组: http://stackoverflow.com/questions/3266443/can-you-use-a-shared-ptr-for-raii-of-c-style-arrays
uint8_t *source, size_t len, char *target) { const uint16_t table[] = { 0x3030, 0x3130, 0x3230..._t)); return val; } uint32_t string_to_uint32(const char *data) { uint32_t val; std::memcpy(&val...auto alice = std::make_shared("Alice", 38); std::shared_ptr name(alice, &alice...alice 可能被乱搞,可能已经失效了,这个时候使用alice的name是有问题的 直接来个极端的例子 std::shared_ptr null; std::shared_ptr<std::...没有嗷别做梦了 I’m embedding my game assets into the executable, here’s how I did it… 手把手教你cmake嵌入复杂文件信息,tar
auto Engine::thread_main(const std::shared_ptr& graph_task) -> void { while (graph_task...; i < num_outputs; ++i) { // 遍历自己的输出 auto& output = outputs[i]; const auto& next = fn.next_edge...for (int i = 0; i < num_outputs; ++i) { // 遍历输入节点 const auto& next = fn.next_edge(i); // 查找下一个可以计算的节点...::make_shared(); for (int i = 0; i < num_devices; ++i) { std::thread t(&Engine...::make_shared(); for (int i = 0; i < num_devices; ++i) { std::thread t(&Engine
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