code: def __create_sync_layer(self, weights):
          
          sync_layer = syncnet(weights, 0.0, initial_phases = initial_type.RANDOM_GAUSSIAN, ccore = False);
          
          for oscillator_index1 in range(0, len(sync_layer)):
              for oscillator_index2 in range(oscillator_index1 + 1, len(sync_layer)):
                  if (self.__has_object_connection(oscillator_index1, oscillator_index2)):
                      sync_layer.set_connection(oscillator_index1, oscillator_index2);
          
          return sync_layer;
docs: !
          @brief Creates second layer of the network.
          
          @param[in] weights (list): List of weights of SOM neurons.
          
          @return (syncnet) Second layer of the network.