1094 The Largest Generation

本文介绍了一种通过递归深度优先搜索算法统计家族树中各代人数的方法,并实现了寻找人数最多的代的任务。输入包括家族成员总数及有子女的成员信息,输出最大人口数量及其对应的代数。

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1094 The Largest Generation (25 分)
A family hierarchy is usually presented by a pedigree tree where all the nodes on the same level belong to the same generation. Your task is to find the generation with the largest population.

Input Specification:
Each input file contains one test case. Each case starts with two positive integers N (<100) which is the total number of family members in the tree (and hence assume that all the members are numbered from 01 to N), and M (<N) which is the number of family members who have children. Then M lines follow, each contains the information of a family member in the following format:

ID K ID[1] ID[2] … ID[K]
where ID is a two-digit number representing a family member, K (>0) is the number of his/her children, followed by a sequence of two-digit ID’s of his/her children. For the sake of simplicity, let us fix the root ID to be 01. All the numbers in a line are separated by a space.

Output Specification:
For each test case, print in one line the largest population number and the level of the corresponding generation. It is assumed that such a generation is unique, and the root level is defined to be 1.

Sample Input:
23 13
21 1 23
01 4 03 02 04 05
03 3 06 07 08
06 2 12 13
13 1 21
08 2 15 16
02 2 09 10
11 2 19 20
17 1 22
05 1 11
07 1 14
09 1 17
10 1 18
Sample Output:9 4
题意:
输入树的结点个数N,非叶子结点个数M,然后输入M个非叶子结点各自的孩子结点编号,求结点个数最多的一层,(根结点层号为1)。

#include<cstdio>
#include<vector>
using namespace std;
const int maxn=110;
vector<int> Node[maxn];
int hashTable[maxn]={0};//记录每层的结点个数
void DFS(int index,int level)
{
	hashTable[level]++;
	for(int j=0;j<Node[index].size();j++)
	{
		DFS(Node[index][j],level+1);
	}
} 
int main()
{
	int n,m,parent,k,child;
	scanf("%d%d", &n, &m);
	for(int i=0;i<m;i++)
	{
		scanf("%d%d",&parent,&k);//父亲结点编号,孩子个数
		for(int j=0;j<k;j++)
		{
			scanf("%d", &child);//孩子结点编号
			Node[parent].push_back(child);//建树 
		} 
	}
	DFS(1,1);//根结点为1号结点,层号为1
	int maxLevel=-1,maxValue=0;
	for(int i=1;i<maxn;i++) 
	{
		if(hashTable[i]>maxValue)
		{
			maxValue=hashTable[i];
			maxLevel=i;
		}
	}
	printf("%d %d\n",maxValue,maxLevel);//输出最大结点数与该层层号
	return 0; 
}
import time import torch, torch_npu from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig # 替换成本地的模型权重路径 MODEL_PATH = "/models/z50051264/Qwen2.5-7B-Instruct" bnb_config = BitsAndBytesConfig( load_in_4bit=True, bnb_4bit_compute_dtype=torch.float16, # Support torch.float16, torch.float32, torch.bfloat16 bnb_4bit_quant_type="nf4", bnb_4bit_use_double_quant=False, bnb_4bit_quant_storage=torch.uint8 ) torch.npu.synchronize() start_time = time.time() model = AutoModelForCausalLM.from_pretrained( MODEL_PATH, device_map={"":0}, quantization_config=bnb_config, low_cpu_mem_usage=True, torch_dtype=torch.float16 # Support torch.float16, torch.float32, torch.bfloat16 ) torch.npu.synchronize() print(f"[+] load time: {time.time() - start_time:.6}s") tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH) model.eval() prompt = "Once upon a time, " inputs = tokenizer([prompt], return_tensors="pt") input_ids = inputs.input_ids.npu() attention_mask = inputs.attention_mask.npu() torch.npu.synchronize() start_time = time.time() generated_ids = model.generate( input_ids=input_ids, attention_mask=attention_mask, max_new_tokens=32, do_sample=False, ) torch.npu.synchronize() print(f"[+] inference time: {time.time() - start_time:.6}s") print(tokenizer.batch_decode(generated_ids)) 我在使用npu版本的bitsandbytes,但是执行以上代码,出现错误: [root@190f3c453709 inference]# python nf4.py /usr/local/python3.10.17/lib/python3.10/site-packages/torch_npu/utils/storage.py:38: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() if self.device.type != 'cpu': Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████| 4/4 [00:13<00:00, 3.26s/it] [+] load time: 14.9728s The following generation flags are not valid and may be ignored: ['temperature', 'top_p', 'top_k']. Set `TRANSFORMERS_VERBOSITY=info` for more details. [+] inference time: 3.78472s ['Once upon a time, 123456789 was the largest known prime number. If a new prime number, 123456789'] 请分析问题原因,并给出详细解决方法
最新发布
07-23
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