  
      @property
      def use_mask(self):
          """ Return True if a mask has been set else false """
          return self.config.get("mask_type", None) is not None
  
      @property
      def ae_dims(self):
          """ Set the Autoencoder Dimensions or set to default """
          retval = self.config["autoencoder_dims"]
 
</s> remove         retval = bool(opts.get("mask_type", None) or opts["warp_to_landmarks"])
 </s> add         retval = opts["warp_to_landmarks"] </s> remove         retval = bool(self.model.training_opts.get("mask_type", None))
 </s> add         retval = (self.model.training_opts.get("replicate_input_mask", False) or
                  self.model.training_opts.get("penalized_mask_loss", True)) </s> remove         qname = "extract_align_out" if self.final_pass else "extract_align_in"
 </s> add         qname_dict = dict(detect="extract_align_in",
                          align="extract_mask_in",
                          mask="extract_mask_out")
        qname = "extract_mask_out" if self.final_pass else qname_dict[self.phase] </s> remove         """ Set whether to run detect and align together or separately """
        if self._detector.vram == 0 or self._aligner.vram == 0:
            logger.debug("At least one of aligner or detector have no VRAM requirement. "
                         "Enabling parallel processing.")
            return True
 </s> add         """ Set whether to run detect, align, and mask together or separately """
        return self.config.get("replicate_input_mask", False)
  
      @property
      def use_mask(self):
          """ Return True if a mask has been set else false """
        return self.config.get("replicate_input_mask", False)
  
      @property
      def ae_dims(self):
          """ Set the Autoencoder Dimensions or set to default """
          retval = self.config["autoencoder_dims"]
keep keep keep keep replace keep keep keep keep keep
 Smart Mask Exposure for Extraction & Training (#831)

Smart Masks - Initial Commit 
plugins/train/model/dfl_sae.py