          return KerasModel(inpt, x)
      
      
      def save_weights(self):
          from threading import Thread
          from time import sleep
          
          model_dir = str(self.model_dir)
 
</s> remove     def Decoder(self):
        inp = Input(shape=(8, 8, 512))
        x = self.upscale(384)(inp)
        x = self.res_block(384)(x)
        x = self.upscale_sep(192)(x)
        x = self.res_block(192)(x)
        x = self.upscale(128)(x)
        x = self.res_block(128)(x)
        x = self.upscale(64)(x)
        x = self.res_block(64)(x)                    
        
#         rb = Conv2D(64, kernel_size=3, padding="same", dilation_rate=2)(x)
#         rb = LeakyReLU(alpha=0.2)(rb)
#         rb = Conv2D(64, kernel_size=3, padding="same", dilation_rate=2)(rb)
#         x = add([rb, x])
# 
        #x = self.upscale(32)(x)        
                        
        out = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
                
        return KerasModel(inp, out)
 </s> add     def Decoder_original(self):       
        decoder_shape = self.IMAGE_SHAPE[0]//8        
        inpt = Input(shape=(decoder_shape, decoder_shape, 512))
        
        x = self.upscale(512, kernel_initializer=RandomNormal(0, 0.02))(inpt)
        x = self.upscale(256, kernel_initializer=RandomNormal(0, 0.02))(x)
        x = self.upscale(self.IMAGE_SHAPE[0], kernel_initializer=RandomNormal(0, 0.02))(x) </s> remove from keras.layers.core import Activation
 </s> add from .instance_normalization import InstanceNormalization </s> remove             mydll.SetProcessDPIAware(True)        
 </s> add             mydll.SetProcessDPIAware(True)                               
        
        self._encoder_type = encoder_type
    def Decoder_shaoanlu(self):       
        decoder_shape = self.IMAGE_SHAPE[0]//8        
        inpt = Input(shape=(decoder_shape, decoder_shape, 512))
        
        x = self.upscale_sep3(512)(inpt)
        x = self.upscale_sep3(256)(x)
        x = self.upscale_sep3(self.IMAGE_SHAPE[0])(x)
        
        x = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
        
        return KerasModel(inpt, x)    


          return KerasModel(inpt, x)
      
      
    def Decoder_shaoanlu(self):       
        decoder_shape = self.IMAGE_SHAPE[0]//8        
        inpt = Input(shape=(decoder_shape, decoder_shape, 512))
        
        x = self.upscale_sep3(512)(inpt)
        x = self.upscale_sep3(256)(x)
        x = self.upscale_sep3(self.IMAGE_SHAPE[0])(x)
        
        x = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
        
        return KerasModel(inpt, x)    


      def save_weights(self):
          from threading import Thread
          from time import sleep
          
          model_dir = str(self.model_dir)
keep keep add keep keep keep keep keep
 model update (#417)

New, functional Original 128 model 
plugins/Model_OriginalHighRes/Model.py