float train_networks(network *nets, int n, data d, int interval)
{
int i;
int batch = nets[0].batch;
int subdivisions = nets[0].subdivisions;
assert(batch * subdivisions * n == d.X.rows);
pthread_t *threads = (pthread_t *) calloc(n, sizeof(pthread_t));
float *errors = (float *) calloc(n, sizeof(float));
float sum = 0;
for(i = 0; i < n; ++i){
data p = get_data_part(d, i, n);
threads[i] = train_network_in_thread(nets[i], p, errors + i);
}
for(i = 0; i < n; ++i){
pthread_join(threads[i], 0);
//printf("%f\n", errors[i]);
sum += errors[i];
}
//cudaDeviceSynchronize();
if (get_current_batch(nets[0]) % interval == 0) {
printf("Syncing... ");
fflush(stdout);
sync_nets(nets, n, interval);
printf("Done!\n");
}
//cudaDeviceSynchronize();
free(threads);
free(errors);
return (float)sum/(n);
}
const gchar *
get_data_f (xml_dayf *data,
forecast type)
{
gchar *p, *str = NULL;
if (data)
{
switch (type & 0x0F00)
{
case ITEMS:
switch(type)
{
case WDAY: str = data->day; break;
case TEMP_MIN: str = data->low; break;
case TEMP_MAX: str = data->hi; break;
default: str = g_strdup("-"); break;
}
break;
case NPART:
str = get_data_part(data->part[1], type);
break;
case DPART:
str = get_data_part(data->part[0], type);
break;
}
}
if (!str)
str = "-";
p = copy_buffer(str);
//DBG ("value: %s", p);
return p;
}
