          logger.debug("Starting Training Process")
          logger.info("Training data directory: %s", self.args.model_dir)
  
          # TODO Move these args to config and remove these deprecation warnings
          if hasattr(self.args, "warp_to_landmarks") and self.args.warp_to_landmarks:
              deprecation_warning("`-wl`, ``--warp-to-landmarks``",
                                  additional_info="This option will be available within training "
                                                  "config settings (/config/train.ini).")
          if hasattr(self.args, "no_augment_color") and self.args.no_flip:
              deprecation_warning("`-nac`, ``--no-augment-color``",
 
</s> remove         logger.info("Training data directory: %s", self.args.model_dir)
 </s> add         logger.info("Training data directory: %s", self._args.model_dir) </s> remove         if hasattr(self.args, "no_augment_color") and self.args.no_flip:
 </s> add         if hasattr(self._args, "no_augment_color") and self._args.no_flip: </s> remove         """ Call the training process object """
 </s> add         """ The entry point for triggering the Training Process.

        Should only be called from  :class:`lib.cli.ScriptExecutor`
        """ </s> remove         set_system_verbosity(self.args.loglevel)
        thread = self.start_thread()
        # queue_manager.debug_monitor(1)
 </s> add         set_system_verbosity(self._args.loglevel)
        thread = self._start_thread()
        # from lib.queue_manager import queue_manager; queue_manager.debug_monitor(1) </s> remove         if self.pingpong.active:
 </s> add         if self._pingpong.active:
        if hasattr(self._args, "warp_to_landmarks") and self._args.warp_to_landmarks:
          logger.debug("Starting Training Process")
          logger.info("Training data directory: %s", self.args.model_dir)
  
          # TODO Move these args to config and remove these deprecation warnings
        if hasattr(self._args, "warp_to_landmarks") and self._args.warp_to_landmarks:
              deprecation_warning("`-wl`, ``--warp-to-landmarks``",
                                  additional_info="This option will be available within training "
                                                  "config settings (/config/train.ini).")
          if hasattr(self.args, "no_augment_color") and self.args.no_flip:
              deprecation_warning("`-nac`, ``--no-augment-color``",
keep keep keep keep replace keep keep keep keep keep
 Smart Masks - Training Implementation (#914)

* Smart Masks - Training

- Reinstate smart mask training code
- Reinstate mask_type back to model.config
- change 'replicate_input_mask to 'learn_mask'
- Add learn mask option
- Add mask loading from alignments to plugins.train.trainer
- Add mask_blur and mask threshold options
- _base.py - Pass mask options through training_opts dict
- plugins.train.model - check for mask_type not None for learn_mask and penalized_mask_loss
- Limit alignments loading to just those faces that appear in the training folder
- Raise error if not all training images have an alignment, and alignment file is required
- lib.training_data - Mask generation code
- lib.faces_detect - cv2 dimension stripping bugfix
- Remove cv2 linting code

* Update mask helptext in cli.py

* Fix Warp to Landmarks
Remove SHA1 hashing from training data

* Update mask training config

* Capture missing masks at training init

* lib.image.read_image_batch - Return filenames with batch for ordering

* scripts.train - Documentation

* plugins.train.trainer - documentation

* Ensure backward compatibility.
Fix convert for new predicted masks

* Update removed masks to components for legacy models. 
scripts/train.py