          self.multiscale_count = 3 if self.config["multiscale_decoder"] else 1
          self.encoder_dim = self.config["encoder_dims"]
          self.decoder_dim = self.config["decoder_dims"]
  
      @property
      def ae_dims(self):
          """ Set the Autoencoder Dimensions or set to default """
          retval = self.config["autoencoder_dims"]
          if retval == 0:
              retval = 256 if self.architecture == "liae" else 512
 
</s> remove         autoencoder = KerasModel(inputs, outputs, name=self.name)
 </s> add         autoencoder = KerasModel(inputs, outputs, name=self.model_name) </s> remove         autoencoder = KerasModel(inputs, outputs, name=self.name)
 </s> add         autoencoder = KerasModel(inputs, outputs, name=self.model_name) </s> remove             msg = "Load weights selected, but the path '%s' does not exist."
 </s> add             msg = f"Load weights selected, but the path '{weights_file}' does not exist." </s> remove             msg = "Load weights selected, but the path '%s' is not a valid Keras model (.h5) file."
 </s> add             msg = (f"Load weights selected, but the path '{weights_file}' is not a valid Keras "
                   f"model (.h5) file.")
        self._patch_weights_management()

    @property
    def model_name(self):
        """ str: The name of the keras model. Varies depending on selected architecture. """
        return f"{self.name}_{self.architecture}"

          self.multiscale_count = 3 if self.config["multiscale_decoder"] else 1
          self.encoder_dim = self.config["encoder_dims"]
          self.decoder_dim = self.config["decoder_dims"]
  
        self._patch_weights_management()

    @property
    def model_name(self):
        """ str: The name of the keras model. Varies depending on selected architecture. """
        return f"{self.name}_{self.architecture}"

      @property
      def ae_dims(self):
          """ Set the Autoencoder Dimensions or set to default """
          retval = self.config["autoencoder_dims"]
          if retval == 0:
              retval = 256 if self.architecture == "liae" else 512
keep keep keep add keep keep keep keep keep keep
 Bugfix -Weights freezing/loading for dfl-sae 
plugins/train/model/dfl_sae.py