          logger.debug("Load model: (swapped: %s)", swapped)
          model_mapping = self.map_models(swapped)
          for network in self.networks.values():
              if not network.side:
                  is_loaded = network.load(predict=self.predict)
              else:
                  is_loaded = network.load(fullpath=model_mapping[network.side][network.type],
                                           predict=self.predict)
              if not is_loaded:
                  break
 
</s> remove                 is_loaded = network.load(fullpath=model_mapping[network.side][network.type],
                                         predict=self.predict)
 </s> add                 is_loaded = network.load(fullpath=model_mapping[network.side][network.type]) </s> remove     def load(self, fullpath=None, predict=False):
 </s> add     def load(self, fullpath=None): </s> remove         #else:
 </s> add         # else: </s> remove         ## PlaidML has a bug regarding the clipnorm parameter
        ## See: https://github.com/plaidml/plaidml/issues/228
        ## Workaround by simply removing it.
        ## TODO: Remove this as soon it is fixed in PlaidML.
        #if keras.backend.backend() == "plaidml.keras.backend":
 </s> add         # # PlaidML has a bug regarding the clipnorm parameter
        # # See: https://github.com/plaidml/plaidml/issues/228
        # # Workaround by simply removing it.
        # # TODO: Remove this as soon it is fixed in PlaidML.
        # if keras.backend.backend() == "plaidml.keras.backend":
                is_loaded = network.load()
          logger.debug("Load model: (swapped: %s)", swapped)
          model_mapping = self.map_models(swapped)
          for network in self.networks.values():
              if not network.side:
                is_loaded = network.load()
              else:
                  is_loaded = network.load(fullpath=model_mapping[network.side][network.type],
                                           predict=self.predict)
              if not is_loaded:
                  break
keep keep keep keep replace keep keep keep keep keep
 Fix VRAM issue with reloading models 
plugins/train/model/_base.py