          
          x = self.upscale(384, kernel_initializer=RandomNormal(0, 0.02))(inpt)
          x = self.upscale(256-32, kernel_initializer=RandomNormal(0, 0.02))(x)
          x = self.upscale(self.IMAGE_SHAPE[0], kernel_initializer=RandomNormal(0, 0.02))(x)
  <<<<<<< HEAD
          
          x = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
          
          return KerasModel(inpt, x)
      
      
  =======
          
          x = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
          
          return KerasModel(inpt, x)
      
 
</s> remove >>>>>>> 721e80dd773c850769ba6af82daa9f5ec95812bb
 </s> add  </s> remove >>>>>>> 721e80dd773c850769ba6af82daa9f5ec95812bb
 </s> add  </s> remove <<<<<<< HEAD


=======
 </s> add  </s> remove =======
 </s> add  </s> remove <<<<<<< HEAD
 </s> add 
          
          x = self.upscale(384, kernel_initializer=RandomNormal(0, 0.02))(inpt)
          x = self.upscale(256-32, kernel_initializer=RandomNormal(0, 0.02))(x)
          x = self.upscale(self.IMAGE_SHAPE[0], kernel_initializer=RandomNormal(0, 0.02))(x)








          
          x = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
          
          return KerasModel(inpt, x)
      
keep keep keep keep replace replace replace replace replace replace replace replace keep keep keep keep keep
 added OriginalHighRes model state save 
plugins/Model_OriginalHighRes/Model.py