                              self._config_changeable_items,
                              False if self._is_predict else self._args.no_logs,
                              training_image_size)
  
          logger.debug("Initialized ModelBase (%s)", self.__class__.__name__)
  
      @property
      def model(self):
 
</s> remove         self._settings = _Settings(self._args, self.config["allow_growth"], self._is_predict)
 </s> add  </s> remove     def __init__(self, arguments, allow_growth, is_predict):
        logger.debug("Initializing %s: (arguments: %s, allow_growth: %s, is_predict: %s)",
                     self.__class__.__name__, arguments, allow_growth, is_predict)
 </s> add     def __init__(self, arguments, mixed_precision, allow_growth, is_predict):
        logger.debug("Initializing %s: (arguments: %s, mixed_precision: %s, allow_growth: %s, "
                     "is_predict: %s)", self.__class__.__name__, arguments, mixed_precision,
                     allow_growth, is_predict) </s> remove         if get_backend() != "nvidia" or not use_mixed_precision:
 </s> add         if not use_mixed_precision:
        self._settings = _Settings(self._args,
                                   self.config["mixed_precision"],
                                   self.config["allow_growth"],
                                   self._is_predict)
                              self._config_changeable_items,
                              False if self._is_predict else self._args.no_logs,
                              training_image_size)
        self._settings = _Settings(self._args,
                                   self.config["mixed_precision"],
                                   self.config["allow_growth"],
                                   self._is_predict)
  
          logger.debug("Initialized ModelBase (%s)", self.__class__.__name__)
  
      @property
      def model(self):
keep keep add keep keep keep keep keep
 Training - Move Mixed Precision to model config 
plugins/train/model/_base.py