          if not self._args.freeze:
              logger.debug("Freeze weights deselected. Not freezing")
              return
  
          # Standardized config for freezing weights of other layers in model is `freeze-layers`
          to_freeze = self.config.get("freeze_layers")
          to_freeze = to_freeze if to_freeze else ["encoder"]
          for layer in self._model.layers:
              if isinstance(layer, KModel) and 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 "
 
</s> remove         if not self._args.freeze:
 </s> add         if not self._args.freeze_weights: </s> remove             dest="freeze",
 </s> add             dest="freeze_weights", </s> remove         self._model.summary(print_fn=print_fn)
        for layer in self._model.layers:
            if isinstance(layer, KModel):
                layer.summary(print_fn=print_fn)
 </s> add         for model in self._get_all_sub_models(self._model):
            model.summary(print_fn=print_fn) </s> remove             opts=("-f", "--freeze"),
 </s> add             opts=("-f", "--freeze-weights"), </s> remove matplotlib==3.0.3
 </s> add matplotlib>3.0.3,<3.3.0
        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:
          if not self._args.freeze:
              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:
        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:
        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:
        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:
        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 "
keep keep keep keep replace replace replace replace replace keep keep keep keep keep
 Fixups
  - Documentation - Update sphinx_requirements.txt
  - plugins.train.model - Add recursive keras model scanning
  - Change "freeze" option to "freeze-weights" 
plugins/train/model/_base.py