          self._update_legacy_models()
          is_summary = hasattr(self._args, "summary") and self._args.summary
          with self._settings.strategy_scope():
              if self._io.model_exists:
                  model = self._io._load()  # pylint:disable=protected-access
                  if self._is_predict:
                      inference = _Inference(model, self._args.swap_model)
                      self._model = inference.model
                  else:
                      self._model = model
 
</s> remove             model = self._io._load()  # pylint:disable=protected-access
 </s> add             model = self.io.load() </s> remove         filename = self._io._filename  # pylint:disable=protected-access
 </s> add         filename = self._io.filename </s> remove             retval = KModel(model_inputs, model, name=f"{saved_model.name}_inference")
 </s> add             retval = keras.models.Model(model_inputs, model, name=f"{saved_model.name}_inference") </s> remove             self._backup.backup_model(self._filename)
            # pylint:disable=protected-access
            self._backup.backup_model(self._plugin.state._filename)
 </s> add             self._backup.backup_model(self.filename)
            self._backup.backup_model(self._plugin.state.filename)
                model = self.io.load()
          self._update_legacy_models()
          is_summary = hasattr(self._args, "summary") and self._args.summary
          with self._settings.strategy_scope():
              if self._io.model_exists:
                model = self.io.load()
                  if self._is_predict:
                      inference = _Inference(model, self._args.swap_model)
                      self._model = inference.model
                  else:
                      self._model = model
keep keep keep keep replace keep keep keep keep keep
 Learning Rate finder (#1341)

* Add LR Finder support structure

* Move trainer.Feeder to lib.training.generator

* Expose model.io

* Add lr_finder

* Update docs and locales

* Pre-PR fixups
  - Fix training graph not displaying
  - CI fixes
  - Switch lr finder progress to tqdm
  - Exit lr finder early on NaN
  - Display lr finder progress in GUI 
plugins/train/model/_base/model.py