              already been performed. This is likely to cause some issues, but not as many as
              guaranteed failure when limiting GPU devices
          """
          logger.debug("use_mixed_precision: %s, skip_check: %s", use_mixed_precision, skip_check)
          if get_backend() != "nvidia" or not use_mixed_precision:
              logger.debug("Not enabling 'mixed_precision' (backend: %s, use_mixed_precision: %s)",
                           get_backend(), use_mixed_precision)
              return False
          logger.info("Enabling Mixed Precision Training.")
  
 
</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     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)
        if not use_mixed_precision:
              already been performed. This is likely to cause some issues, but not as many as
              guaranteed failure when limiting GPU devices
          """
          logger.debug("use_mixed_precision: %s, skip_check: %s", use_mixed_precision, skip_check)
        if not use_mixed_precision:
              logger.debug("Not enabling 'mixed_precision' (backend: %s, use_mixed_precision: %s)",
                           get_backend(), use_mixed_precision)
              return False
          logger.info("Enabling Mixed Precision Training.")
  
keep keep keep keep replace keep keep keep keep keep
 Training - Move Mixed Precision to model config 
plugins/train/model/_base.py