          -------
          dict
              Dictionary of source frame names with a list of associated face indices to be skipped
          """
          retval: Dict[str, List[int]] = {}
          input_aligned_dir = self._args.input_aligned_dir
  
          if input_aligned_dir is None:
              logger.verbose("Aligned directory not specified. All faces listed in "  # type:ignore
                             "the alignments file will be converted")
 
</s> remove     def _get_face_metadata(self) -> Dict[str, List[int]]:
 </s> add     def _get_face_metadata(self) -> T.Dict[str, T.List[int]]: </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()} </s> remove         if backend == "amd":
            return  # No settings for AMD
 </s> add  </s> remove         masks3: Union[List[np.ndarray], np.ndarray] = []
 </s> add         masks3: T.Union[T.List[np.ndarray], np.ndarray] = [] </s> remove         datatype:  [required] A python type class. This limits the type of data that can be
                   provided in the .ini file and ensures that the value is returned in the
                   correct type to faceswap. Valid data types are: <class 'int'>, <class 'float'>,
                   <class 'str'>, <class 'bool'>.
        default:   [required] The default value for this option.
        info:      [required] A string describing what this option does.
        choices:   [optional] If this option's datatype is of <class 'str'> then valid
                   selections can be defined here. This validates the option and also enables
                   a combobox / radio option in the GUI.
        gui_radio: [optional] If <choices> are defined, this indicates that the GUI should use
                   radio buttons rather than a combobox to display this option.
        min_max:   [partial] For <class 'int'> and <class 'float'> data types this is required
                   otherwise it is ignored. Should be a tuple of min and max accepted values.
                   This is used for controlling the GUI slider range. Values are not enforced.
        rounding:  [partial] For <class 'int'> and <class 'float'> data types this is
                   required otherwise it is ignored. Used for the GUI slider. For floats, this
                   is the number of decimal places to display. For ints this is the step size.
        fixed:     [optional] [train only]. Training configurations are fixed when the model is
                   created, and then reloaded from the state file. Marking an item as fixed=False
                   indicates that this value can be changed for existing models, and will override
                   the value saved in the state file with the updated value in config. If not
                   provided this will default to True.
 </s> add         "datatype:  [required] A python type class. This limits the type of data that can be
               "   provided in the .ini file and ensures that the value is returned in the
               "   correct type to faceswap. Valid data types are: <class 'int'>, <class 'float'>,
               "   <class 'str'>, <class 'bool'>.
        "default:   [required] The default value for this option.
        "info:      [required] A string describing what this option does.
        "choices:   [optional] If this option's datatype is of <class 'str'> then valid
               "   selections can be defined here. This validates the option and also enables
               "   a combobox / radio option in the GUI.
        "gui_radio: [optional] If <choices> are defined, this indicates that the GUI should use
               "   radio buttons rather than a combobox to display this option.
        "min_max:   [partial] For <class 'int'> and <class 'float'> data types this is required
               "   otherwise it is ignored. Should be a tuple of min and max accepted values.
               "   This is used for controlling the GUI slider range. Values are not enforced.
        "rounding:  [partial] For <class 'int'> and <class 'float'> data types this is
               "   required otherwise it is ignored. Used for the GUI slider. For floats, this
               "   is the number of decimal places to display. For ints this is the step size.
        "fixed:     [optional] [train only]. Training configurations are fixed when the model is
               "   created, and then reloaded from the state file. Marking an item as fixed=False
               "   indicates that this value can be changed for existing models, and will override
               "   the value saved in the state file with the updated value in config. If not
               "   provided this will default to True.
        retval: T.Dict[str, T.List[int]] = {}
          -------
          dict
              Dictionary of source frame names with a list of associated face indices to be skipped
          """
        retval: T.Dict[str, T.List[int]] = {}
          input_aligned_dir = self._args.input_aligned_dir
  
          if input_aligned_dir is None:
              logger.verbose("Aligned directory not specified. All faces listed in "  # type:ignore
                             "the alignments file will be converted")
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 
scripts/convert.py