          model_filename = "Nirkin_300_softmax_v1.h5"
          super().__init__(git_model_id=git_model_id, model_filename=model_filename, **kwargs)
          self.name = "VGG Clear"
          self.input_size = 300
          self.vram = 3104
          self.vram_warnings = 1088  # at BS 1. OOMs at higher batchsizes
          self.vram_per_batch = 96
          self.batchsize = self.config["batch-size"]
  
      def init_model(self):
 
</s> remove         self.vram_per_batch = 96
 </s> add         self.vram_per_batch = 400 </s> remove         self.vram_per_batch = 208
 </s> add         self.vram_per_batch = 304 </s> remove         self.vram = 4096
 </s> add         self.vram = 4112 </s> remove         self.vram = 3440
 </s> add         self.vram = 3424 </s> remove         self.vram_per_batch = 128
 </s> add         self.vram_per_batch = 208
        self.vram = 2944
          model_filename = "Nirkin_300_softmax_v1.h5"
          super().__init__(git_model_id=git_model_id, model_filename=model_filename, **kwargs)
          self.name = "VGG Clear"
          self.input_size = 300
        self.vram = 2944
          self.vram_warnings = 1088  # at BS 1. OOMs at higher batchsizes
          self.vram_per_batch = 96
          self.batchsize = self.config["batch-size"]
  
      def init_model(self):
keep keep keep keep replace keep keep keep keep keep
 Optimize Extract parallel VRAM allocation 
plugins/extract/mask/vgg_clear.py