首页 \ 问答 \ 用本地指针分段错误?(Segmentation fault with local pointer?)

用本地指针分段错误?(Segmentation fault with local pointer?)

这是一个函数调用(因此它只是整个程序的一部分)。 它会产生分段错误。 我猜这是由“指针是一个局部变量”引起的?

int fileExists(const char *fname){
    int i = 0;
    fseek(fs, sizeof(NODE)*i, SEEK_SET);
    NODE* pointer;
    fread(pointer, sizeof(NODE), 1, fs);
    return 1;
}

更新:

typedef struct node {
    char fname[MAX_NAME];
    short fstart;
} NODE;

int findStart (const char *fname){
    fs = fopen("Directory", "w+");
    NODE* pointer = malloc(sizeof(NODE));
    int i;
    for(i=0;i<numberNodes;i++){
        fseek(fs, sizeof(NODE)*i, SEEK_SET);
        fread(pointer, sizeof(NODE), 1, fs);
        if(strcmp(pointer->fname, fname)==0)
            return pointer->fstart;
    }
    return 0;
}

因此,如果我想运行目录文件中的节点并找到正确节点的“fstart”,我是否可以实现这一点而无需释放分配给“指针”的内存?


This is a function call (so it is just a part of the whole program). It will generate a segmentation fault. I guess it is caused by "pointer being a local variable"?

int fileExists(const char *fname){
    int i = 0;
    fseek(fs, sizeof(NODE)*i, SEEK_SET);
    NODE* pointer;
    fread(pointer, sizeof(NODE), 1, fs);
    return 1;
}

Updated:

typedef struct node {
    char fname[MAX_NAME];
    short fstart;
} NODE;

int findStart (const char *fname){
    fs = fopen("Directory", "w+");
    NODE* pointer = malloc(sizeof(NODE));
    int i;
    for(i=0;i<numberNodes;i++){
        fseek(fs, sizeof(NODE)*i, SEEK_SET);
        fread(pointer, sizeof(NODE), 1, fs);
        if(strcmp(pointer->fname, fname)==0)
            return pointer->fstart;
    }
    return 0;
}

So if I want to run through the nodes in the directory file and find the "fstart" of the right node, can I achieve that without the need of free-ing the memory allocated to "pointer"?


原文:https://stackoverflow.com/questions/8147619
更新时间:2023-07-08 06:07

最满意答案

所以我发现没有可以使用的predict()方法。 相反,我们需要使用transform()方法进行预测。 只需删除标签列并创建一个新的数据框。 例如,就我而言,我做了,

pred = sqlContext.createDataFrame([("What are liver enzymes ?" ,)], ["sentence"])

prediction = model.transform(pred)

然后我们可以使用select()方法找到预测结果。 至少现在,这个解决方案为我成功地工作。 请让我知道是否有任何改正或比这更好的方法。


So I figured it out that there is no predict() method that can be used. So instead, we need to use the transform() method to make predictions. Just remove the label column and create a new dataframe. For example, in my case, I did,

pred = sqlContext.createDataFrame([("What are liver enzymes ?" ,)], ["sentence"])

prediction = model.transform(pred)

And then we can find the prediction using the select() method. Atleast for now, this solution worked successfully for me. Please do let me know if there is any correction or a better approach than this.

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