      def init_model(self) -> None:
          """ Initialize S3FD Model"""
          assert isinstance(self.model_path, str)
          confidence = self.config["confidence"] / 100
          model_kwargs = dict(custom_objects=dict(L2Norm=L2Norm, SliceO2K=SliceO2K))
          self.model = S3fd(self.model_path,
                            model_kwargs,
                            self.config["allow_growth"],
                            self._exclude_gpus,
                            confidence)
 
</s> remove     def model_definition(self) -> Tuple[List[Tensor], List[Tensor]]:
 </s> add     def model_definition(self) -> T.Tuple[T.List[Tensor], T.List[Tensor]]: </s> remove     file = ('{"test": "param"}')
 </s> add     file = '{"test": "param"}' </s> remove     def __init__(self, arguments: "argparse.Namespace") -> None:
 </s> add     def __init__(self, arguments: argparse.Namespace) -> None: </s> remove         batch.feed = ((np.array([cast(np.ndarray, feed.face)[..., :3]
 </s> add         batch.feed = ((np.array([T.cast(np.ndarray, feed.face)[..., :3] </s> remove     def test__add_amd_loss_labels(self,
                                  event_parser_instance: _EventParser,
                                  mocker: pytest_mock.MockerFixture) -> None:
        """ Test _add_amd_loss_labels works correctly

        Parameters
        ----------
        event_parser_instance: :class:`lib.gui.analysis.event_reader._EventParser`
            The class instance to test
        mocker: :class:`pytest_mock.MockerFixture`
            Mocker for checking Session data
        """
        event_parse = event_parser_instance

        # Already collected
        assert not event_parse._cache._loss_labels
        event_parse._cache._loss_labels.extend(["label_a", "label_b"])
        event_parse._add_amd_loss_labels(1)
        assert not event_parse._loss_labels

        # New labels
        event_parse._cache._loss_labels = []
        mock_session = mocker.patch("lib.gui.analysis.Session")
        mock_session.get_loss_keys.return_value = ["label_c", "label_d"]
        assert not event_parse._cache._loss_labels
        event_parse._add_amd_loss_labels(1)
        assert event_parse._loss_labels == ["label_c", "label_d"]

 </s> add 
        model_kwargs = {"custom_objects": {"L2Norm": L2Norm, "SliceO2K": SliceO2K}}
      def init_model(self) -> None:
          """ Initialize S3FD Model"""
          assert isinstance(self.model_path, str)
          confidence = self.config["confidence"] / 100
        model_kwargs = {"custom_objects": {"L2Norm": L2Norm, "SliceO2K": SliceO2K}}
          self.model = S3fd(self.model_path,
                            model_kwargs,
                            self.config["allow_growth"],
                            self._exclude_gpus,
                            confidence)
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/extract/detect/s3fd.py