          x = Conv2D(in_conv_filters, kernel_size=5, use_bias=False, padding="same")(impt)
          x = self.conv_inst_norm(in_conv_filters+32, use_instance_norm=False)(x)
          x = self.conv_inst_norm(256)(x)        
          x = self.conv_inst_norm(512)(x)
          x = self.conv_inst_norm(1024)(x)        
          
          dense_shape = self.IMAGE_SHAPE[0] // 16         
          x = Dense(self.ENCODER_DIM, kernel_initializer=_kern_init)(Flatten()(x))
          x = Dense(dense_shape * dense_shape * 768, kernel_initializer=_kern_init)(x)
          x = Reshape((dense_shape, dense_shape, 768))(x)
          x = self.upscale(512)(x)
          
 
</s> remove         
        dense_shape = self.IMAGE_SHAPE[0] // 16         
 </s> add         dense_shape = self.IMAGE_SHAPE[0] // 16 </s> remove         
        return KerasModel(impt, x, **kwargs)    
 </s> add         return KerasModel(impt, x, **kwargs) </s> remove         
        return KerasModel(impt, x, **kwargs)    
          
    
 </s> add         return KerasModel(impt, x, **kwargs)

 </s> remove     
    
    def Decoder_shaoanlu(self):       
        decoder_shape = self.IMAGE_SHAPE[0]//8        
 </s> add     def Decoder_shaoanlu(self):
        decoder_shape = self.IMAGE_SHAPE[0]//8 </s> remove         
        return KerasModel(inpt, x)    
 </s> add         return KerasModel(inpt, x)
        x = self.conv_inst_norm(1024)(x)

        dense_shape = self.IMAGE_SHAPE[0] // 16
          x = Conv2D(in_conv_filters, kernel_size=5, use_bias=False, padding="same")(impt)
          x = self.conv_inst_norm(in_conv_filters+32, use_instance_norm=False)(x)
          x = self.conv_inst_norm(256)(x)        
          x = self.conv_inst_norm(512)(x)
        x = self.conv_inst_norm(1024)(x)

        dense_shape = self.IMAGE_SHAPE[0] // 16
        x = self.conv_inst_norm(1024)(x)

        dense_shape = self.IMAGE_SHAPE[0] // 16
        x = self.conv_inst_norm(1024)(x)

        dense_shape = self.IMAGE_SHAPE[0] // 16
          x = Dense(self.ENCODER_DIM, kernel_initializer=_kern_init)(Flatten()(x))
          x = Dense(dense_shape * dense_shape * 768, kernel_initializer=_kern_init)(x)
          x = Reshape((dense_shape, dense_shape, 768))(x)
          x = self.upscale(512)(x)
          
keep keep keep keep replace replace replace keep keep keep keep keep
 Logging (#541)

* Convert prints to logger. Further logging improvements. Tidy  up

* Fix system verbosity. Allow SystemExit

* Fix reload extract bug

* Child Traceback handling

* Safer shutdown procedure

* Add shutdown event to queue manager

* landmarks_as_xy > property. GUI notes + linting. Aligner bugfix

* fix FaceFilter. Enable nFilter when no Filter is supplied

* Fix blurry face filter

* Continue on IO error. Better error handling

* Explicitly print stack trace tocrash log

* Windows Multiprocessing bugfix

* Add git info and conda version to crash log

* Windows/Anaconda mp bugfix

* Logging fixes for training 
plugins/model/Model_OriginalHighRes/Model.py