解释void loadFromFile() { Spot spotsFromFile[MAX_SPOT_NUM]; // 存储所有景点信息 int spotFromFileCount = 0; FILE* fp; fp = fopen("spots.txt", "r"); if (fp == NULL) { printf("文件打开失败!\n"); return; } while (1) { Spot s; if (fscanf(fp, "%s %s %d", s.name, s.info, &s.price) != 3) { break; } spotsFromFile[spotFromFileCount++] = s; } fclose(fp); printf("读取成功!\n"); printf("景点信息如下:\n"); for (int i = 0; i < spotFromFileCount; i++) { printf("%d. 名称:%s,信息:%s,票价:%d\n", i + 1,spotsFromFile[i].name, spotsFromFile[i].info, spotsFromFile[i].price); } }
时间: 2024-03-07 19:53:40 浏览: 18
这段代码定义了一个名为loadFromFile的函数,它的作用是从文件中读取景点信息并打印出来。在函数内部,它首先定义了一个大小为MAX_SPOT_NUM的Spot类型数组spotsFromFile,用于存储所有的景点信息。接着定义了一个整型变量spotFromFileCount,用于记录读取到的景点数量。
函数打开一个名为spots.txt的文件,如果文件打开失败则会打印出“文件打开失败!”并直接返回。然后进入一个while循环,每次从文件中读取一条景点信息,如果读取失败则跳出循环,否则将读取到的景点信息存储到spotsFromFile数组中,同时spotFromFileCount加1。
最后,函数关闭文件,打印出“读取成功!”,并逐一打印出所有的景点信息,格式为“序号. 名称:xxx,信息:xxx,票价:xxx”。
相关问题
python web_demo.py Explicitly passing a `revision` is encouraged when loading a model with custom code to ensure no malicious code has been contributed in a newer revision. Traceback (most recent call last): File "/home/nano/THUDM/ChatGLM-6B/web_demo.py", line 5, in <module> tokenizer = AutoTokenizer.from_pretrained("/home/nano/THUDM/chatglm-6b", trust_remote_code=True) File "/home/nano/.local/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 679, in from_pretrained return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs) File "/home/nano/.local/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 1804, in from_pretrained return cls._from_pretrained( File "/home/nano/.local/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 1958, in _from_pretrained tokenizer = cls(*init_inputs, **init_kwargs) File "/home/nano/.cache/huggingface/modules/transformers_modules/chatglm-6b/tokenization_chatglm.py", line 221, in __init__ self.sp_tokenizer = SPTokenizer(vocab_file, num_image_tokens=num_image_tokens) File "/home/nano/.cache/huggingface/modules/transformers_modules/chatglm-6b/tokenization_chatglm.py", line 64, in __init__ self.text_tokenizer = TextTokenizer(vocab_file) File "/home/nano/.cache/huggingface/modules/transformers_modules/chatglm-6b/tokenization_chatglm.py", line 22, in __init__ self.sp.Load(model_path) File "/home/nano/.local/lib/python3.10/site-packages/sentencepiece/__init__.py", line 905, in Load return self.LoadFromFile(model_file) File "/home/nano/.local/lib/python3.10/site-packages/sentencepiece/__init__.py", line 310, in LoadFromFile return _sentencepiece.SentencePieceProcessor_LoadFromFile(self, arg) RuntimeError: Internal: src/sentencepiece_processor.cc(1101) [model_proto->ParseFromArray(serialized.data(), serialized.size())]什么错误
根据您提供的错误信息,看起来是加载模型时出现了一些问题。具体来说,这个错误是由于加载了一个具有自定义代码的模型,并且在加载时没有明确指定修订版本。为了确保没有恶意代码被贡献到较新的修订版本中,建议显式地传递一个`revision`参数。
您可以尝试以下解决方法:
在`web_demo.py`文件中,将以下代码行:
```python
tokenizer = AutoTokenizer.from_pretrained("/home/nano/THUDM/chatglm-6b", trust_remote_code=True)
```
替换为:
```python
tokenizer = AutoTokenizer.from_pretrained("/home/nano/THUDM/chatglm-6b", trust_remote_code=True, revision="main")
```
这样会明确指定修订版本为"main",以避免加载模型时出现安全问题。请确保您已经下载了正确的模型文件并将路径指向正确的位置。
如果问题仍然存在,请提供更多详细信息,以便我能够更好地帮助您解决问题。
void loadFromFile(const string& filename) { ifstream file(filename); string line; int number = 1; while (getline(file, line)) { float result = stof(line); Athlete* newAthlete = new Athlete{ number++, result, nullptr }; if (head == nullptr) { head = newAthlete; } else { Athlete* current = head; while (current->next != nullptr) { current = current->next; } current->next = newAthlete; } } }*/ void loadFromFile(const string& filename) { ifstream file(filename); string line; int number = 1; Athlete* current = new Athlete{ 0, 0, nullptr }; head = current; while (getline(file, line)) { float result = stof(line); Athlete* newAthlete = new Athlete{ number++, result, nullptr }; current->next = newAthlete; current = newAthlete; } current->next = nullptr; current = head; head = head->next; delete current; }改写成能读取文件所有数据并且排序
以下是改写后的代码:
```
void loadFromFile(const string& filename) {
ifstream file(filename);
string line;
vector<float> results;
while (getline(file, line)) {
float result = stof(line);
results.push_back(result);
}
sort(results.begin(), results.end());
int number = 1;
Athlete* current = new Athlete{ 0, 0, nullptr };
head = current;
for (float result : results) {
Athlete* newAthlete = new Athlete{ number++, result, nullptr };
current->next = newAthlete;
current = newAthlete;
}
current->next = nullptr;
current = head;
head = head->next;
delete current;
}
```
这里使用了一个 `vector` 来存储所有的结果,然后使用 `sort` 函数进行排序,最后再按照顺序构建链表。注意,原来的代码中没有进行排序,所以这里加了排序的步骤。
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