  
          self._io = _IO(self, model_dir, self._is_predict)
          self._check_multiple_models()
  
          self._settings = _Settings(self._args, self.config["allow_growth"], self._is_predict)
          self._state = State(model_dir,
                              self.name,
                              self._config_changeable_items,
                              False if self._is_predict else self._args.no_logs,
                              training_image_size)
 
</s> remove         if get_backend() != "nvidia" or not use_mixed_precision:
 </s> add         if not use_mixed_precision: </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         use_mixed_precision = not is_predict and arguments.mixed_precision
 </s> add         use_mixed_precision = not is_predict and mixed_precision and get_backend() == "nvidia"
  
          self._io = _IO(self, model_dir, self._is_predict)
          self._check_multiple_models()
  

          self._state = State(model_dir,
                              self.name,
                              self._config_changeable_items,
                              False if self._is_predict else self._args.no_logs,
                              training_image_size)
keep keep keep keep replace keep keep keep keep keep
 Training - Move Mixed Precision to model config 
plugins/train/model/_base.py