Обновление директив OpenACC

Когда у меня есть ядро ​​в верхнем цикле, почему я не могу использовать эти 2 директивы:

#pragma acc update device(hbias[0:n_hidden],W[0:n_hidden][0:n_visible])
#pragma acc update device(vbias[0:n_visible)

Мне нужно обновить эти переменные hbias, vbias, W в приведенном ниже коде, но он не будет работать:

void RBM::contrastive_divergence(int train_X[6][6], double learning_rate, int k) {
double r= rand() / (RAND_MAX + 1.0);

int * input = new int[n_visible];
double *ph_mean = new double[n_hidden];
int *ph_sample = new int[n_hidden];
double *nv_means = new double[n_visible];
int *nv_samples = new int[n_visible];
double *nh_means = new double[n_hidden];
int *nh_samples = new int[n_hidden];

#pragma acc kernels
for (int i = 0; i<train_N; i++) {for (int j = 0; j< n_visible; j++){
input[j] = train_X[i][j];
}sample_h_given_v(input, ph_mean, ph_sample,r);

for (int step = 0; step<k; step++) {
if (step == 0) {
gibbs_hvh(ph_sample, nv_means, nv_samples, nh_means, nh_samples,r);
}
else {
gibbs_hvh(nh_samples, nv_means, nv_samples, nh_means, nh_samples,r);
}
}for (int i = 0; i<n_hidden; i++) {
for (int j = 0; j<n_visible; j++) {

W[i][j] += learning_rate * (ph_mean[i] * input[j] - nh_means[i] * nv_samples[j]) / N;

}
hbias[i] += learning_rate * (ph_sample[i] - nh_means[i]) / N;

}
//this directive
#pragma acc update device(hbias[0:n_hidden],W[0:n_hidden][0:n_visible])for (int i = 0; i<n_visible; i++) {
vbias[i] += learning_rate * (input[i] - nv_samples[i]) / N;
}
//and this directive
#pragma acc update device(vbias[0:n_visible)
}

delete[] input;
delete[] ph_mean;
delete[] ph_sample;
delete[] nv_means;
delete[] nv_samples;
delete[] nh_means;
delete[] nh_samples;
}

Но когда у меня есть много отдельных ядер, работающих над каждым вложенным циклом, я могу обновить переменные:

   void RBM::contrastive_divergence(int train_X[6][6], double learning_rate, int k) {
double r= rand() / (RAND_MAX + 1.0);

int * input = new int[n_visible];
double *ph_mean = new double[n_hidden];
int *ph_sample = new int[n_hidden];
double *nv_means = new double[n_visible];
int *nv_samples = new int[n_visible];
double *nh_means = new double[n_hidden];
int *nh_samples = new int[n_hidden];for (int i = 0; i<train_N; i++) {

#pragma acc kernels
for (int j = 0; j< n_visible; j++){
input[j] = train_X[i][j];
}sample_h_given_v(input, ph_mean, ph_sample,r);
#pragma acc kernels
for (int step = 0; step<k; step++) {
if (step == 0) {
gibbs_hvh(ph_sample, nv_means, nv_samples, nh_means, nh_samples,r);
}
else {
gibbs_hvh(nh_samples, nv_means, nv_samples, nh_means, nh_samples,r);
}
}

#pragma acc kernels
{
for (int i = 0; i<unhidden; i++) {
for (int j = 0; j<n_visible; j++) {

W[i][j] += learning_rate * (ph_mean[i] * input[j] - nh_means[i] * nv_samples[j]) / N;

}
hbias[i] += learning_rate * (ph_sample[i] - nh_means[i]) / N;

}
//this directive
#pragma acc update device(hbias[0:n_hidden],W[0:n_hidden][0:n_visible])
}#pragma acc kernels
{
for (int i = 0; i<n_visible; i++) {
vbias[i] += learning_rate * (input[i] - nv_samples[i]) / N;
}

//and this directive
#pragma acc update device(vbias[0:n_visible)
}
}

delete[] input;
delete[] ph_mean;
delete[] ph_sample;
delete[] nv_means;
delete[] nv_samples;
delete[] nh_means;
delete[] nh_samples;
}