                     f"model (.h5) file.")
  
          if msg:
              msg += " Please check and try again."
              raise FaceswapError(msg)
  
          logger.verbose("Using weights file: %s", weights_file)
          return weights_file
  
      def freeze(self):
 
</s> remove             msg = (f"Load weights selected, but the path '{weights_file}' is not a valid Keras "
                   f"model (.h5) file.")
 </s> add             msg = "Load weights selected, but the path '%s' is not a valid Keras model (.h5) file." </s> remove             msg = f"Load weights selected, but the path '{weights_file}' does not exist."
 </s> add             msg = "Load weights selected, but the path '%s' does not exist." </s> remove     def _patch_weights_management(self, arguments):
        """ Patch in the correct encoder name into the config dictionary for freezing and loading
        weights based on architecture.

        Because of variable model name based on architecture, configfile needs to be loaded
        prior to initializing parent

        Parameters
        ----------
        arguments: :class:`argparse.Namespace`
            The arguments that were passed to the train or convert process as generated from
            Faceswap's command line arguments

        """
        self._configfile = arguments.configfile if hasattr(arguments, "configfile") else None
        self.architecture = self.config["architecture"].lower()
        self.config["freeze_layers"] = [f"encoder_{self.architecture}"]
        self.config["load_layers"] = [f"encoder_{self.architecture}"]
        logger.debug("Patched encoder layers to config: %s", self.config)

 </s> add  </s> remove     @property
    def name(self):
        """ str: The name of this model based on the plugin name. Overridden as DFL-SAE is
        named differently depending on the architecture selected. """
        basename = super().name
        name = f"{basename}_{self.architecture}"
        return name

 </s> add  </s> remove                                  name=self.name)
 </s> add                                  name="{}_{}".format(self.name, self.architecture))
            logger.error(msg)
                     f"model (.h5) file.")
  
          if msg:
              msg += " Please check and try again."
            logger.error(msg)
  
          logger.verbose("Using weights file: %s", weights_file)
          return weights_file
  
      def freeze(self):
keep keep keep keep replace keep keep keep keep keep
 Revert "Bugfix -Weights freezing/loading for dfl-sae"

This reverts commit 086933d97dbd50bb9291026c1cf90fe94f463ce1. 
plugins/train/model/_base.py