          logger.debug("Initializing %s: (model_input_size: %s, model_output_shapes: %s, "
                       "coverage_ratio: %s, augment_color: %s, no_flip: %s, warp_to_landmarks: %s, "
                       "alignments: %s, config: %s)",
                       self.__class__.__name__, model_input_size, model_output_shapes,
                       coverage_ratio, augment_color, no_flip, warp_to_landmarks,
                       list(alignments.keys()), config)
          self._config = config
          self._model_input_size = model_input_size
          self._model_output_shapes = model_output_shapes
          self._coverage_ratio = coverage_ratio
 
</s> remove                      "coverage_ratio: %s, augment_color: %s, no_flip: %s, warp_to_landmarks: %s, "
                     "alignments: %s, config: %s)",
 </s> add                      "coverage_ratio: %s, augment_color: %s, no_flip: %s, no_warp: %s, "
                     "warp_to_landmarks: %s, alignments: %s, config: %s)", </s> remove                  no_flip, warp_to_landmarks, alignments, config):
 </s> add                  no_flip, no_warp, warp_to_landmarks, alignments, config): </s> remove         else:
            processed["feed"] = [self._processing.skip_warp(batch[..., :3])]
 </s> add  </s> remove     disable_warp=dict(
        default=False,
        info="Disable warp augmentation. Warping is integral to the Neural Network training. If "
             "you decide to disable warping, you should only do so towards the end of a model's "
             "training session.",
        datatype=bool,
        group="image augmentation",
        fixed=False),
 </s> add 
                     coverage_ratio, augment_color, no_flip, no_warp, warp_to_landmarks,
          logger.debug("Initializing %s: (model_input_size: %s, model_output_shapes: %s, "
                       "coverage_ratio: %s, augment_color: %s, no_flip: %s, warp_to_landmarks: %s, "
                       "alignments: %s, config: %s)",
                       self.__class__.__name__, model_input_size, model_output_shapes,
                     coverage_ratio, augment_color, no_flip, no_warp, warp_to_landmarks,
                       list(alignments.keys()), config)
          self._config = config
          self._model_input_size = model_input_size
          self._model_output_shapes = model_output_shapes
          self._coverage_ratio = coverage_ratio
keep keep keep keep replace keep keep keep keep keep
 Training - Move disable warp option out of config 
lib/training_data.py