          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)
          
      
      def Decoder_shaoanlu(self):       
          decoder_shape = self.IMAGE_SHAPE[0]//8        
          inpt = Input(shape=(decoder_shape, decoder_shape, 512))
 
</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             x = SeparableConv2D(filters * 4, kernel_size=3, padding='same')(x)
 </s> add             x = Conv2D(filters*4, kernel_size=3, use_bias=False, kernel_initializer=RandomNormal(0, 0.02), padding='same', **kwargs)(x)
            if use_instance_norm:
                x = inst_norm()(x) </s> remove         x = Dense(4 * 4 * 1024)(x)
        x = Reshape((4, 4, 1024))(x)
        out = self.upscale(512)(x)
        return KerasModel(retina, out)
    
 </s> add         x = Dense(dense_shape * dense_shape * 768)(x)
        x = Reshape((dense_shape, dense_shape, 768))(x)
        x = self.upscale(512)(x)
        
        return KerasModel(impt, x, **kwargs)     </s> remove     def Encoder_v2(self):
        """Old algorithm; pretty good but slow"""
        retina = Input(shape=self.IMAGE_SHAPE)
        x = self.conv(128)(retina)         
        x = self.conv(144)(x)              
        x = self.conv_sep(256)(x)
        x = self.conv(448)(x)        
        x = self.conv_sep(512)(x)        
        x = self.conv(768)(x)
        x = self.conv_sep(1024)(x)
 </s> add     def Encoder_shaoanlu(self, **kwargs):
        impt = Input(shape=self.IMAGE_SHAPE)
                
        in_conv_filters = self.IMAGE_SHAPE[0] if self.IMAGE_SHAPE[0] <= 128 else 128 + (self.IMAGE_SHAPE[0]-128)//4
        
        x = Conv2D(in_conv_filters, kernel_size=5, kernel_initializer=conv_init, use_bias=False, padding="same")(impt)
        x = self.conv_sep3(in_conv_filters+32, use_instance_norm=False)(x)
        x = self.conv_sep3(256)(x)        
        x = self.conv_sep3(512)(x)
        x = self.conv_sep3(1024)(x)        
        
        dense_shape = self.IMAGE_SHAPE[0] // 16         
        x = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
        
        return KerasModel(inpt, x)
    
          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)
          
        x = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
        
        return KerasModel(inpt, x)
    
      
      def Decoder_shaoanlu(self):       
          decoder_shape = self.IMAGE_SHAPE[0]//8        
          inpt = Input(shape=(decoder_shape, decoder_shape, 512))
keep keep keep add keep keep keep keep
 model update (#417)

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