  
  
  _DEFAULTS = {
      "batch-size": {
          "default": 8,
          "info": "The batch size to use. To a point, higher batch sizes equal better performance, "
                  "but setting it too high can harm performance.\n"
                  "\n\tNvidia users: If the batchsize is set higher than the your GPU can "
                  "accomodate then this will automatically be lowered.",
          "datatype": int,
 
</s> remove         "default": 8,
 </s> add         "default": 2, </s> remove         "default": 8,
 </s> add         "default": 12, </s> remove         "default": 8,
 </s> add         "default": 4, </s> remove     @property
    def _total_vram_required(self):
        """ Return vram required for all phases plus the buffer """
        retval = sum([getattr(self, "_{}".format(p)).vram for p in self._flow]) + self._vram_buffer
        logger.trace(retval)
        return retval

 </s> add  </s> remove         self.vram_per_batch = 208
 </s> add         self.vram_per_batch = 304
        "default": 6,
  
  
  _DEFAULTS = {
      "batch-size": {
        "default": 6,
          "info": "The batch size to use. To a point, higher batch sizes equal better performance, "
                  "but setting it too high can harm performance.\n"
                  "\n\tNvidia users: If the batchsize is set higher than the your GPU can "
                  "accomodate then this will automatically be lowered.",
          "datatype": int,
keep keep keep keep replace keep keep keep keep keep
 Optimize Extract parallel VRAM allocation 
plugins/extract/mask/vgg_clear_defaults.py