  "L|unbalanced: 128px in/out model from andenixa. The autoencoders are unbalanced so B>A swaps won't work so well. Very configurable.\n"
  "L|villain: 128px in/out model from villainguy. Very resource hungry (You will require a GPU with a fair amount of VRAM). Good for details, but more susceptible to color differences."
  msgstr ""
  
  #: lib/cli/args.py:949
  msgid "Output a summary of the model and exit. If a model folder is provided then a summary of the saved model is displayed. Otherwise a summary of the model that would be created by the chosen plugin and configuration settings is displayed."
  msgstr ""
  
  #: lib/cli/args.py:959
  msgid "Freeze the weights of the model. Freezing weights means that some of the parameters in the model will no longer continue to learn, but those that are not frozen will continue to learn. For most models, this will freeze the encoder, but some models may have configuration options for freezing other layers."
 
</s> remove #: lib/cli/args.py:959
 </s> add #: lib/cli/args.py:975 </s> remove #: lib/cli/args.py:972 lib/cli/args.py:984 lib/cli/args.py:995
#: lib/cli/args.py:1081
 </s> add #: lib/cli/args.py:988 lib/cli/args.py:1000 lib/cli/args.py:1011
#: lib/cli/args.py:1097 </s> remove #: lib/cli/args.py:1047
 </s> add #: lib/cli/args.py:1063 </s> remove     def _freeze_weights(self):
        """ If freeze has been selected in the cli arguments, then freeze those models indicated
        in the plugin's configuration. """
        if not self._args.freeze_weights:
            logger.debug("Freeze weights deselected. Not freezing")
            return

        to_freeze = self.config.get("freeze_layers")  # Standardized config for freezing weights
        to_freeze = to_freeze if to_freeze else ["encoder"]  # No plugin config
        for layer in self._get_all_sub_models(self._model):
            if layer.name in to_freeze:
                logger.info("Freezing weights for '%s' in model '%s'", layer.name, self.name)
                layer.trainable = False
                to_freeze.remove(layer.name)
        if to_freeze:
            logger.warning("The following layers were set to be frozen but do not exist in the "
                           "model: %s", to_freeze)

 </s> add 
#: lib/cli/args.py:965
  "L|unbalanced: 128px in/out model from andenixa. The autoencoders are unbalanced so B>A swaps won't work so well. Very configurable.\n"
  "L|villain: 128px in/out model from villainguy. Very resource hungry (You will require a GPU with a fair amount of VRAM). Good for details, but more susceptible to color differences."
  msgstr ""
  
#: lib/cli/args.py:965
  msgid "Output a summary of the model and exit. If a model folder is provided then a summary of the saved model is displayed. Otherwise a summary of the model that would be created by the chosen plugin and configuration settings is displayed."
  msgstr ""
  
  #: lib/cli/args.py:959
  msgid "Freeze the weights of the model. Freezing weights means that some of the parameters in the model will no longer continue to learn, but those that are not frozen will continue to learn. For most models, this will freeze the encoder, but some models may have configuration options for freezing other layers."
keep keep keep keep replace keep keep keep keep keep
 Training - Load Weights
  - Enable the loading of previously trained encoders for new models. 
locales/lib.cli.args.pot