                                        minimalist=self._config["mobilenet_minimalistic"],
                                        include_preprocessing=False))
  
      @property
      def _selected_model(self) -> Tuple[_EncoderInfo, dict]:
          """ tuple(dict, :class:`_EncoderInfo`): The selected encoder model and it's associated
          keyword arguments """
          arch = self._config["enc_architecture"]
          model = _MODEL_MAPPING[arch]
          kwargs = self._model_kwargs.get(arch, {})
 
</s> remove         return dict(mobilenet=dict(alpha=self._config["mobilenet_width"],
                                   depth_multiplier=self._config["mobilenet_depth"],
                                   dropout=self._config["mobilenet_dropout"]),
                    mobilenet_v2=dict(alpha=self._config["mobilenet_width"]),
                    mobilenet_v3=dict(alpha=self._config["mobilenet_width"],
                                      minimalist=self._config["mobilenet_minimalistic"],
                                      include_preprocessing=False))
 </s> add         return {"mobilenet": {"alpha": self._config["mobilenet_width"],
                              "depth_multiplier": self._config["mobilenet_depth"],
                              "dropout": self._config["mobilenet_dropout"]},
                "mobilenet_v2": {"alpha": self._config["mobilenet_width"]},
                "mobilenet_v3": {"alpha": self._config["mobilenet_width"],
                                 "minimalist": self._config["mobilenet_minimalistic"],
                                 "include_preprocessing": False}} </s> remove         model_inputs: List[List[np.ndarray]] = []
        model_targets: List[List[np.ndarray]] = []
 </s> add         model_inputs: T.List[T.List[np.ndarray]] = []
        model_targets: T.List[T.List[np.ndarray]] = [] </s> remove     kwargs: Dict[str, Any] = field(default_factory=dict)
 </s> add     kwargs: T.Dict[str, T.Any] = field(default_factory=dict) </s> remove     def _select_freeze_layers(self) -> List[str]:
 </s> add     def _select_freeze_layers(self) -> T.List[str]: </s> remove     def command_line_arguments(self) -> "argparse.Namespace":
 </s> add     def command_line_arguments(self) -> argparse.Namespace:
    def _selected_model(self) -> T.Tuple[_EncoderInfo, dict]:
                                        minimalist=self._config["mobilenet_minimalistic"],
                                        include_preprocessing=False))
  
      @property
    def _selected_model(self) -> T.Tuple[_EncoderInfo, dict]:
          """ tuple(dict, :class:`_EncoderInfo`): The selected encoder model and it's associated
          keyword arguments """
          arch = self._config["enc_architecture"]
          model = _MODEL_MAPPING[arch]
          kwargs = self._model_kwargs.get(arch, {})
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/phaze_a.py