          retval = dict(input=input_shape[0][1], output=output_shape[-1][1])
          logger.debug(retval)
          return retval
  
      @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
  
      def _load_model(self):
          """ Load the Faceswap model.
  
          Returns
          -------
 
</s> remove         self._batchsize = self._get_batchsize(queue_size)
 </s> add 
          retval = dict(input=input_shape[0][1], output=output_shape[-1][1])
          logger.debug(retval)
          return retval
  




















      def _load_model(self):
          """ Load the Faceswap model.
  
          Returns
          -------
keep keep keep keep replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace keep keep keep keep keep
 model.config - Make convert batchsize a user configurable option 
scripts/convert.py