              logger.debug("Switching to phase: %s", self._current_phase)
  
      # <<< INTERNAL METHODS >>> #
      @property
      def _parallel_scaling(self):
          """ dict: key is number of parallel plugins being loaded, value is the scaling factor that
          the total base vram for those plugins should be scaled by
  
          Notes
          -----
 
</s> remove         logger.trace("%s: %s", qname, retval)
 </s> add         logger.trace("%s: %s", qname, retval)  # type: ignore </s> remove             # Cleanup queues
            for q_name in self._queues:
                queue_manager.del_queue(q_name)
 </s> add  </s> remove         logger.trace(retval)
 </s> add         logger.trace(retval)  # type: ignore </s> remove     def _set_extractor_batchsize(self):
 </s> add     def _set_extractor_batchsize(self) -> None: </s> remove     def passes(self):
 </s> add     def passes(self) -> int:
    def _parallel_scaling(self) -> Dict[int, float]:
              logger.debug("Switching to phase: %s", self._current_phase)
  
      # <<< INTERNAL METHODS >>> #
      @property
    def _parallel_scaling(self) -> Dict[int, float]:
          """ dict: key is number of parallel plugins being loaded, value is the scaling factor that
          the total base vram for those plugins should be scaled by
  
          Notes
          -----
keep keep keep keep replace keep keep keep keep keep
 extract: Add batch processing mode 
plugins/extract/pipeline.py