          if self._mask_inputs is None:
              return None
          return [K.int_shape(mask_input) for mask_input in self._mask_inputs]
  
      def configure(self, model: keras.models.Model) -> None:
          """ Configure the loss functions for the given inputs and outputs.
  
          Parameters
          ----------
          model: :class:`keras.models.Model`
 
</s> remove     def _mask_shapes(self) -> Optional[List[tuple]]:
 </s> add     def _mask_shapes(self) -> T.Optional[T.List[tuple]]: </s> remove     def _make_inference_model(self, saved_model: keras.models.Model) -> keras.models.Model:
 </s> add     def _make_inference_model(self, saved_model: tf.keras.models.Model) -> tf.keras.models.Model: </s> remove                  model: "ModelBase",
 </s> add                  model: ModelBase, </s> remove     def _mask_inputs(self) -> Optional[list]:
 </s> add     def _mask_inputs(self) -> T.Optional[list]: </s> remove         if get_backend() == "amd":
            # We can't log the graph in Tensorboard logs for AMD so need to obtain from state file
            loss_keys = {int(sess_id): [name for name in session["loss_names"] if name != "total"]
                         for sess_id, session in self._state["sessions"].items()}
        else:
            assert self._tb_logs is not None
            loss_keys = {sess_id: list(logs.keys())
                         for sess_id, logs
                         in self._tb_logs.get_loss(session_id=session_id).items()}
 </s> add         assert self._tb_logs is not None
        loss_keys = {sess_id: list(logs.keys())
                     for sess_id, logs
                     in self._tb_logs.get_loss(session_id=session_id).items()}
    def configure(self, model: tf.keras.models.Model) -> None:
          if self._mask_inputs is None:
              return None
          return [K.int_shape(mask_input) for mask_input in self._mask_inputs]
  
    def configure(self, model: tf.keras.models.Model) -> None:
          """ Configure the loss functions for the given inputs and outputs.
  
          Parameters
          ----------
          model: :class:`keras.models.Model`
keep keep keep keep replace keep keep keep keep keep
 Remove plaidML support (#1325)

* Remove PlaidML reference from readme files

* Remove AMD option from installers

* remove amd requirements and update setup.py

* remove plaidml test from CI workflow

* gpustats: remove plaidml backend

* plaid removals:
  - faceswap.py - python version check
  - setup.cfg - plaidml typing ignore
  - lib.keras_utils - All plaid code
  - lib.launcher.py - All plaidml checks and configuration

* remove tf2.2 specific code from GUI event reader

* lib.model - remove all plaidml implementations

* plugins.extract - remove plaidml code

* plugins.train remove plaidml code

* lib.convert - remove plaidml code

* tools.model: remove plaidml code

* Remove plaidML tests from unit tests

* remove plaidml_utils and docsting cleanups

* Remove plaidML refs from configs

* fix keras imports 
plugins/train/model/_base/settings.py