          mask_type:          Type of mask to use. See lib.model.masks for valid mask names.
                              Set to None for not used
          no_logs:            Disable tensorboard logging
          warp_to_landmarks:  Use random_warp_landmarks instead of random_warp
          augment_color:      Perform random shifting of LAB colors
          no_flip:            Don't perform a random flip on the image
          pingpong:           Train each side seperately per save iteration rather than together
  """
  
  import logging
 
</s> remove                                             training_opts.get("coverage_ratio", 0.625))
 </s> add                                             training_opts.get("coverage_ratio", 0.625),
                                            config) </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     def __init__(self, input_size, output_size, coverage_ratio):
 </s> add     def __init__(self, input_size, output_size, coverage_ratio, 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  </s> remove         if np.random.random() < self.random_flip:
 </s> add         random_flip = self.config.get("random_flip", 50) / 100
        if np.random.random() < random_flip:
        augment_color:      Perform random shifting of L*a*b* colors
          mask_type:          Type of mask to use. See lib.model.masks for valid mask names.
                              Set to None for not used
          no_logs:            Disable tensorboard logging
          warp_to_landmarks:  Use random_warp_landmarks instead of random_warp
        augment_color:      Perform random shifting of L*a*b* colors
          no_flip:            Don't perform a random flip on the image
          pingpong:           Train each side seperately per save iteration rather than together
  """
  
  import logging
keep keep keep keep replace keep keep keep keep keep
 Expose Augmentation Options to config 
plugins/train/trainer/_base.py