AlexeyAB
2018-05-06 c9b8bdee1886df5f83973d91c3597c28f99a9e0c
src/network.c
@@ -767,6 +767,11 @@
      free_layer(net.layers[i]);
   }
   free(net.layers);
   free(net.scales);
   free(net.steps);
   free(net.seen);
#ifdef GPU
   if (gpu_index >= 0) cuda_free(net.workspace);
   else free(net.workspace);
@@ -800,14 +805,14 @@
            int f;
            for (f = 0; f < l->n; ++f)
            {
               l->biases[f] = l->biases[f] - l->scales[f] * l->rolling_mean[f] / (sqrtf(l->rolling_variance[f]) + .000001f);
               l->biases[f] = l->biases[f] - (double)l->scales[f] * l->rolling_mean[f] / (sqrt((double)l->rolling_variance[f]) + .000001f);
               const size_t filter_size = l->size*l->size*l->c;
               int i;
               for (i = 0; i < filter_size; ++i) {
                  int w_index = f*filter_size + i;
                  l->weights[w_index] = l->weights[w_index] * l->scales[f] / (sqrtf(l->rolling_variance[f]) + .000001f);
                  l->weights[w_index] = (double)l->weights[w_index] * l->scales[f] / (sqrt((double)l->rolling_variance[f]) + .000001f);
               }
            }