  
          images = {"a": get_image_paths(input_a), "b": get_image_paths(input_b)}
          batchsize = min(len(images["a"]),
                          len(images["b"]),
                          self.model.training_opts.get("preview_images", 14))
          for side, image_files in images.items():
              self.batchers[side].set_timelapse_feed(image_files, batchsize)
          logger.debug("Set up timelapse")
  
      def output_timelapse(self):
 
</s> remove         batchsize = min(len(self.images), self.model.training_opts.get("preview_images", 14))
 </s> add         preview_images = self.config.get("preview_images", 14)
        preview_images = min(max(preview_images, 2), 16)
        batchsize = min(len(self.images), preview_images) </s> remove         num_images = self.model.training_opts.get("preview_images", 14)
 </s> add         num_images = self.config.get("preview_images", 14) </s> remove     def __init__(self, side, images, model, use_mask, batch_size):
        logger.debug("Initializing %s: side: '%s', num_images: %s, batch_size: %s)",
                     self.__class__.__name__, side, len(images), batch_size)
 </s> add     def __init__(self, side, images, model, use_mask, batch_size, config):
        logger.debug("Initializing %s: side: '%s', num_images: %s, batch_size: %s, config: %s)",
                     self.__class__.__name__, side, len(images), batch_size, config) </s> remove         preview_images = self.config.get("preview_images", 14)
        preview_images = min(max(preview_images, 2), 16)
        self.training_opts["preview_images"] = preview_images
 </s> add 
                        self.preview_images)
  
          images = {"a": get_image_paths(input_a), "b": get_image_paths(input_b)}
          batchsize = min(len(images["a"]),
                          len(images["b"]),
                        self.preview_images)
          for side, image_files in images.items():
              self.batchers[side].set_timelapse_feed(image_files, batchsize)
          logger.debug("Set up timelapse")
  
      def output_timelapse(self):
keep keep keep keep replace keep keep keep keep keep
 Expose Augmentation Options to config 
plugins/train/trainer/_base.py