当你在C++中遇到错误 'unordered_map' in namespace 'std' does not name a template type 时,这通常意味着编译器无法识别 std::unordered_map。这个问题可能由几个不同的原因引起。以下是一些可能的解决方案,你可以按照这些步骤逐一排查: 确认已包含必要的头文件: std::unordered_map 需要包含头文件 <unord...
managers who in the face of complexity choose to resort to the most advanced form of systems thinking: critical systems thinking (Jackson2019). These managers focus on what is practically useful for them in their specific context, guided by an ambition of realising systemic improvements through ...
#include<string> #include<unordered_map> usingnamespacestd; voidIs(string str){ unordered_map<char,int>map; for(charch:str){ map[ch]++; } if(map[str[0]]==3||map[str[1]]==3) cout<<"Yes"<<endl; else cout<<"No"<<endl; } intmain(){ intn; cin>>n; for(inti=0;i<n;i...
unordered_map<char,int>mp; vector<unordered_map<int,int>>dp; const int MOD = 1e9 + 7;定义了一个常数,用于结果取模,以防止溢出。 int T;用于存储测试用例的数量。 string s;存储输入字符串。 int n;存储状态转移的步数或长度。 unordered_map<char, int> mp;用于将字符映射到整数,以便后续处理。
#include<unordered_map> #include<algorithm> using namespace std; int solution(string &S) { unordered_map<char, int> char_map; for (char c : S) { if (c == 'B' || c == 'A' || c == 'N') char_map[c] += 2; else if (c == 'L' || c == 'O') char_map[c] +=...
.//include/bmnn_utils.h:115:10: error: ‘unordered_map’ in namespace ‘std’ does not name a template type std::unordered_map<std::string, bm_tensor_t*> m_mapOutputs; 网上搜了一下给出的答案大多是说增加std=c++11标准,但是我的cmake里面已经有-std=c++11了,后来发现是没有包含头文件,...
Since decoding complexity is proportional to the number of trellis states and branches, this tends to become excessively computationally expensive. 3.4.2 STBC Space-time block codes, as the name suggests, are block rather than trellis-based. In their best known form they avoid the complexity ...
解决办法:error: ‘unordered_map’ in namespace ‘std’ does not name a template type,加上编译选项:g++-std=c++11
unordered_map<char,int>mp;// 字符到其唯一索引的映射 vector<unordered_map<int,int>>dp;// DP数组,存储状态结果 MOD是用来避免整型溢出的大质数。 T,s,n用于输入处理。 mp将字符映射到整数索引,以便后续处理。 dp是动态规划表格,用于缓存计算过的状态以提高效率。
The computational complexity of the proposed method is analyzed below. As described, the proposed method contains two main modules: spatiotemporal feature map construction and cross-view spatiotemporal matching. For the real scene above, the running time of the first module is about 123.9 s. In ...