      """
      def __init__(self, in_queue, queue_size, arguments):
          logger.debug("Initializing %s: (args: %s, queue_size: %s, in_queue: %s)",
                       self.__class__.__name__, arguments, queue_size, in_queue)
          self._batchsize = self._get_batchsize(queue_size)
          self._args = arguments
          self._in_queue = in_queue
          self._out_queue = queue_manager.get_queue("patch")
          self._serializer = get_serializer("json")
          self._faces_count = 0
 
</s> remove     @staticmethod
    def _get_batchsize(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
        :attr:`self._queue_size` and 16.

        Returns
        -------
        int
            The batch size that the model is to be fed at.
        """
        logger.debug("Getting batchsize")
        is_cpu = GPUStats().device_count == 0
        batchsize = 1 if is_cpu else 16
        batchsize = min(queue_size, batchsize)
        logger.debug("Batchsize: %s", batchsize)
        logger.debug("Got batchsize: %s", batchsize)
        return batchsize

 </s> add 
      """
      def __init__(self, in_queue, queue_size, arguments):
          logger.debug("Initializing %s: (args: %s, queue_size: %s, in_queue: %s)",
                       self.__class__.__name__, arguments, queue_size, in_queue)

          self._args = arguments
          self._in_queue = in_queue
          self._out_queue = queue_manager.get_queue("patch")
          self._serializer = get_serializer("json")
          self._faces_count = 0
keep keep keep keep replace keep keep keep keep keep
 model.config - Make convert batchsize a user configurable option 
scripts/convert.py