  
      @classmethod
      def _configure_tensorflow(cls) -> None:
          """ Disable eager execution and force Tensorflow into CPU mode. """
          if get_backend() == "amd":
              return
          tf.config.set_visible_devices([], device_type="GPU")
          tf.compat.v1.disable_eager_execution()
  
      @classmethod
      def _get_job(cls, arguments: "argparse.Namespace") -> Any:
 
</s> remove     def _get_job(cls, arguments: "argparse.Namespace") -> Any:
 </s> add     def _get_job(cls, arguments: argparse.Namespace) -> T.Any: </s> remove     def __init__(self, arguments: "argparse.Namespace") -> None:
 </s> add     def __init__(self, arguments: argparse.Namespace) -> None: </s> remove     def _set_tf_settings(cls, allow_growth: bool, exclude_devices: List[int]) -> None:
 </s> add     def _set_tf_settings(cls, allow_growth: bool, exclude_devices: T.List[int]) -> None: </s> remove 
        if get_backend() == "amd" and not self._setup_amd(arguments):
            safe_shutdown(got_error=True)

    @classmethod
    def _setup_amd(cls, arguments: "argparse.Namespace") -> bool:
        """ Test for plaidml and perform setup for AMD.

        Parameters
        ----------
        arguments: :class:`argparse.Namespace`
            The command line arguments passed to Faceswap.

        Returns
        -------
        bool
            ``True`` if AMD was set up succesfully otherwise ``False``
        """
        logger.debug("Setting up for AMD")
        if platform.system() == "Windows":
            deprecation_warning("The AMD backend",
                                additional_info="Please consider re-installing using the "
                                                "'DirectML' backend")
        try:
            import plaidml  # noqa pylint:disable=unused-import,import-outside-toplevel
        except ImportError:
            logger.error("PlaidML not found. Run `pip install plaidml-keras` for AMD support")
            return False
        from lib.gpu_stats import setup_plaidml  # pylint:disable=import-outside-toplevel
        setup_plaidml(arguments.loglevel, arguments.exclude_gpus)
        logger.debug("setup up for PlaidML")
        return True
 </s> add  </s> remove         return mixedprecision.LossScaleOptimizer(optimizer)
 </s> add         return mixedprecision.LossScaleOptimizer(optimizer)  # pylint:disable=no-member
  
      @classmethod
      def _configure_tensorflow(cls) -> None:
          """ Disable eager execution and force Tensorflow into CPU mode. """


          tf.config.set_visible_devices([], device_type="GPU")
          tf.compat.v1.disable_eager_execution()
  
      @classmethod
      def _get_job(cls, arguments: "argparse.Namespace") -> Any:
keep keep keep keep replace 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 
tools/model/model.py