  
          self._model = self._load_model()
          self._sizes = self._get_io_sizes()
          self._coverage_ratio = self._model.coverage_ratio
  
          self._thread = self._launch_predictor()
 
</s> remove         self._batchsize = self._get_batchsize(queue_size)
 </s> add  </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 
        self._batchsize = self._get_batchsize(queue_size)
  
          self._model = self._load_model()
        self._batchsize = self._get_batchsize(queue_size)
          self._sizes = self._get_io_sizes()
          self._coverage_ratio = self._model.coverage_ratio
  
          self._thread = self._launch_predictor()
keep add keep keep keep keep
 model.config - Make convert batchsize a user configurable option 
scripts/convert.py