      is_predict: bool, optional
          ``True`` if the model is being loaded for inference, ``False`` if the model is being loaded
          for training. Default: ``False``
      """
      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)
          self._set_tf_settings(allow_growth, arguments.exclude_gpus)
  
          use_mixed_precision = not is_predict and arguments.mixed_precision
          if use_mixed_precision:
              self._mixed_precision = tf.keras.mixed_precision.experimental
 
</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" </s> remove         if get_backend() != "nvidia" or not use_mixed_precision:
 </s> add         if not use_mixed_precision: </s> remove         self._settings = _Settings(self._args, self.config["allow_growth"], self._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)
      is_predict: bool, optional
          ``True`` if the model is being loaded for inference, ``False`` if the model is being loaded
          for training. Default: ``False``
      """
    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)
    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)
    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)
          self._set_tf_settings(allow_growth, arguments.exclude_gpus)
  
          use_mixed_precision = not is_predict and arguments.mixed_precision
          if use_mixed_precision:
              self._mixed_precision = tf.keras.mixed_precision.experimental
keep keep keep keep replace replace replace keep keep keep keep keep
 Training - Move Mixed Precision to model config 
plugins/train/model/_base.py