          model.build()
          logger.debug("Loaded Model")
          return model
  
      def _get_batchsize(self, queue_size):
          """ Get the batch size for feeding the model.
  
          Sets the batch size to 1 if inference is being run on CPU, otherwise the minimum of the
          input queue size and the model's `convert_batchsize` configuration option.
  
 
</s> remove     def output_size(self):
 </s> add     def output_size(self) -> int: </s> remove     def _get_io_sizes(self):
 </s> add     def _get_io_sizes(self) -> Dict[str, int]: </s> remove     in_queue: :class:`queue.Queue`
 </s> add     in_queue: :class:`~lib.queue_manager.EventQueue` </s> remove     def set_display_dimensions(self, dimensions):
 </s> add     def set_display_dimensions(self, dimensions: Tuple[int, int]) -> None: </s> remove     def in_queue(self):
        """ :class:`queue.Queue`: The input queue to the predictor. """
 </s> add     def in_queue(self) -> "EventQueue":
        """ :class:`~lib.queue_manager.EventQueue`: The input queue to the predictor. """
    def _get_batchsize(self, queue_size: int) -> int:
          model.build()
          logger.debug("Loaded Model")
          return model
  
    def _get_batchsize(self, queue_size: int) -> int:
          """ Get the batch size for feeding the model.
  
          Sets the batch size to 1 if inference is being run on CPU, otherwise the minimum of the
          input queue size and the model's `convert_batchsize` configuration option.
  
keep keep keep keep replace keep keep keep keep keep
 Bugfix: convert - Gif Writer
  - Fix non-launch error on Gif Writer
  - convert plugins - linting
  - convert/fs_media/preview/queue_manager - typing
  - Change convert items from dict to Dataclass 
scripts/convert.py