          list:
              The jobs to be undertaken split into phases that fit into GPU RAM
          """
          force_single_process = not multiprocess or get_backend() == "amd"
          phases = []
          current_phase = []
          available = self._vram_stats["vram_free"]
          for phase in self._flow:
              num_plugins = len([p for p in current_phase if self._vram_per_phase[p] > 0])
              num_plugins += 1 if self._vram_per_phase[phase] > 0 else 0
              scaling = self._parallel_scaling.get(num_plugins, self._scaling_fallback)
              required = sum(self._vram_per_phase[p] for p in current_phase + [phase]) * scaling
 
</s> remove         if plugins_required + batch_required <= self._vram_stats["vram_free"]:
 </s> add         if plugins_required + batch_required <= cast(int, self._vram_stats["vram_free"]): </s> remove     def _total_vram_required(self):
 </s> add     def _total_vram_required(self) -> float: </s> remove         self._post_process = PostProcess(arguments)
 </s> add  </s> remove         logger.trace(retval)
 </s> add         logger.trace(retval)  # type: ignore </s> remove     def _all_plugins(self):
 </s> add     def _all_plugins(self) -> List["PluginExtractor"]:
        phases: List[List[str]] = []
        current_phase: List[str] = []
        available = cast(int, self._vram_stats["vram_free"])
          list:
              The jobs to be undertaken split into phases that fit into GPU RAM
          """
          force_single_process = not multiprocess or get_backend() == "amd"
        phases: List[List[str]] = []
        current_phase: List[str] = []
        available = cast(int, self._vram_stats["vram_free"])
        phases: List[List[str]] = []
        current_phase: List[str] = []
        available = cast(int, self._vram_stats["vram_free"])
        phases: List[List[str]] = []
        current_phase: List[str] = []
        available = cast(int, self._vram_stats["vram_free"])
          for phase in self._flow:
              num_plugins = len([p for p in current_phase if self._vram_per_phase[p] > 0])
              num_plugins += 1 if self._vram_per_phase[phase] > 0 else 0
              scaling = self._parallel_scaling.get(num_plugins, self._scaling_fallback)
              required = sum(self._vram_per_phase[p] for p in current_phase + [phase]) * scaling
keep keep keep keep replace replace replace keep keep keep keep keep
 extract: Add batch processing mode 
plugins/extract/pipeline.py