  
          self._feeder = _Feeder(images, self._model, batch_size, self._config)
  
          self._tensorboard = self._set_tensorboard()
          self._samples = _Samples(self._model,
                                   self._model.coverage_ratio,
                                   self._model.command_line_arguments.preview_scale / 100)
          self._timelapse = _Timelapse(self._model,
                                       self._model.coverage_ratio,
                                       self._config.get("preview_images", 14),
                                       self._feeder,
                                       self._images)
 
</s> remove             if save_iteration or self._save_now or self._refresh_preview:
 </s> add             if self._preview.should_refresh(): </s> remove         self._toggle_preview_mask: bool = False
        self._refresh_preview: bool = False
        self._preview_buffer: Dict[str, np.ndarray] = {}
        self._lock = Lock()
 </s> add         self._preview = Preview() </s> remove         argument_list = []
 </s> add         argument_list: List[Dict[str, Any]] = []
        self._samples = _Samples(self._model, self._model.coverage_ratio)
  
          self._feeder = _Feeder(images, self._model, batch_size, self._config)
  
          self._tensorboard = self._set_tensorboard()
        self._samples = _Samples(self._model, self._model.coverage_ratio)
        self._samples = _Samples(self._model, self._model.coverage_ratio)
        self._samples = _Samples(self._model, self._model.coverage_ratio)
          self._timelapse = _Timelapse(self._model,
                                       self._model.coverage_ratio,
                                       self._config.get("preview_images", 14),
                                       self._feeder,
                                       self._images)
keep keep keep keep replace replace replace keep keep keep keep keep
 Live Preview - Replace cv2 with matplotlib viewer 
plugins/train/trainer/_base.py