I am asked to implement the following part of code into kernel code. Actually, I have tried but not sure about thestd::array.

This is the original code for the function.

int KNN_classifier(array<array<int, 20>, 4344>& array_X_train, array<int, 4344>& array_Y_train,    int k, array<int, 20>& data_point) {    // Calculate the distance between data_point and all points.   int index = 0;   static array<pair<int, float>, 4344> array_dist{};    pair<int, float> pair_tmp;    //Apply uroll:__attribute__((opencl_unroll_hint(n)))    for (size_t i = 0; i < array_X_train.size(); ++i) {        pair_tmp = make_pair(i, Euclidean_distance(array_X_train[i], data_point));        //  dist_vec.push_back(pair_tmp);        array_dist[index] = pair_tmp;        index++;           }

This is the kernel code:

  #define N1 20 //num of cols#define N2 4344 //num of rowsinline float Euclidean_distance(array<int, 20>& array_point_A, array<int, 20>& array_point_B) {    float sum = 0.0;    static array<float, 20> w = { 0.0847282, 0.0408621, 0.105036, 0.0619821, 0.0595455, 0.0416739, 0.0181147, 0.00592921,     0.040049, 0.0766054, 0.0441091, 0.0376111, 0.0124285, 0.0733558, 0.0587338, 0.0303001, 0.0579207, 0.0449221,          0.0530462, 0.0530462 };     for (size_t i = 0; i < array_point_A.size(); ++i) {        int a = array_point_A[i] - array_point_B[i];        float wieghted_distance = w[i] * (static_cast<float> (a) * static_cast<float> (a));         sum += wieghted_distance;    }    return sqrt(sum);}__kernel int  KNN_classifier(__global const int* restrict array_X_train, __global const int* restrict array_Y_train,    __global const int* restrict data_point, int k){    int index = 0;    static array<pair<int, float>, 4344> array_dist{};    pair<int, float> pair_tmp;    for (size_t i = 0; i < array_X_train.size(); ++i) {        pair_tmp = make_pair(i, Euclidean_distance(array_X_train[i], data_point));        array_dist[index] = pair_tmp;        index++;    }

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