  
              super() this method for defaults otherwise be sure to add """
          logger.debug("Setting training data")
          # Force number of preview images to between 2 and 16
          preview_images = self.config.get("preview_images", 14)
          preview_images = min(max(preview_images, 2), 16)
          self.training_opts["preview_images"] = preview_images
          self.training_opts["training_size"] = self.state.training_size
          self.training_opts["no_logs"] = self.state.current_session["no_logs"]
          self.training_opts["mask_type"] = self.config.get("mask_type", None)
          self.training_opts["coverage_ratio"] = self.calculate_coverage_ratio()
          logger.debug("Set training data: %s", self.training_opts)
 
</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         logger.debug("Initializing %s: (input_size: %s, output_size: %s, coverage_ratio: %s)",
                     self.__class__.__name__, input_size, output_size, coverage_ratio)
        # Transform args
        self.rotation_range = 10  # Range to randomly rotate the image by
        self.zoom_range = 0.05  # Range to randomly zoom the image by
        self.shift_range = 0.05  # Range to randomly translate the image by
        self.random_flip = 0.5  # Chance to flip the image horizontally
 </s> add         logger.debug("Initializing %s: (input_size: %s, output_size: %s, coverage_ratio: %s, "
                     "config: %s)", self.__class__.__name__, input_size, output_size,
                     coverage_ratio, config)
        self.config = config </s> remove                                             training_opts.get("coverage_ratio", 0.625))
 </s> add                                             training_opts.get("coverage_ratio", 0.625),
                                            config) </s> remove         self.add_item(
            section=section, title="preview_images", datatype=int, default=14, min_max=(2, 16),
            rounding=2, fixed=False,
            info="Number of sample faces to display for each side in the preview when training.")
 </s> add 
  
              super() this method for defaults otherwise be sure to add """
          logger.debug("Setting training data")
          # Force number of preview images to between 2 and 16



          self.training_opts["training_size"] = self.state.training_size
          self.training_opts["no_logs"] = self.state.current_session["no_logs"]
          self.training_opts["mask_type"] = self.config.get("mask_type", None)
          self.training_opts["coverage_ratio"] = self.calculate_coverage_ratio()
          logger.debug("Set training data: %s", self.training_opts)
keep keep keep keep replace replace replace keep keep keep keep keep
 Expose Augmentation Options to config 
plugins/train/model/_base.py