    getTopLeft(xs_br, inputImages_width, xi_r, xWeight_r);
    getTopLeft(ys_br, inputImages_height, yi_b, yWeight_b);
 
+
+   #if __CUDA_ARCH__>=200
+      printf("%d %d %d %d \n", xi_l, xi_r, yi_t, yi_b);
+      return;
+   #endif
+
    bool topLeftIsIn = between(xi_l, 0, width-1) && between(yi_t, 0, height-1);
    bool topRightIsIn = between(xi_r, 0, width-1) && between(yi_t, 0, height-1);
    bool bottomLeftIsIn = between(xi_l, 0, width-1) && between(yi_b, 0, height-1);

       if (!between(y, 0, height-1)) continue;
       for (int x = xi_l; x <= xi_r; ++x) {
         if (!between(x, 0, width-1)) continue;
         float weight = __expf((x - xf) * (x - xf) + (y - yf) * (y - yf));
         weight_sum += weight;
         weights[id_point] = weight;
         int address = masks_strideBatch * b + masks_strideHeight * y + masks_strideWidth * x;

         if (!between(y, 0, height-1)) continue;
         for (int x = xi_l; x <= xi_r; ++x) {
           if (!between(x, 0, width-1)) continue;
           bias_x[id_point] = 2 * (x - xf); // multiply 2 since it is derivative of square
           bias_y[id_point] = 2 * (y - yf); // multiply 2 since it is derivative of square
           float weight = __expf(-bias_x[id_point] * bias_x[id_point] - bias_y[id_point] * bias_y[id_point]);
           bias_x_weighted += weight * bias_x[id_point];
           bias_y_weighted += weight * bias_y[id_point];
           weight_sum += weight;
