              for filename in default_files:
                  self.load_module(filename, import_path, plugin_type)
  
      def set_globals(self):
          """ Set the global options for training """
          logger.debug("Setting global config")
          section = "global"
          self.add_section(title=section,
                           info="Options that apply to all models" + ADDITIONAL_INFO)
          self.add_item(section=section, title="mask_type", datatype=str, default="none",
 
</s> remove                       choices=get_available_masks(), gui_radio=True,
 </s> add                       choices=get_available_masks(), </s> remove             section=section, title="dssim_loss", datatype=bool, default=True,
            info="Use DSSIM for Loss rather than Mean Absolute Error\n"
                 "May increase overall quality.")
        self.add_item(
            section=section, title="penalized_mask_loss", datatype=bool, default=True,
            info="If using a mask, This penalizes the loss for the masked area, to give higher "
                 "priority to the face area. \nShould increase overall quality and speed up "
                 "training. This should probably be left at True")
        logger.debug("Set global config")
 </s> add             section=section, title="coverage", datatype=float, default=68.75,
            min_max=(62.5, 100.0), rounding=2, fixed=True,
            info="How much of the extracted image to train on. A lower coverage will limit the model's "
                 "scope to a zoomed-in central area while higher amounts can include the entire face. "
                 "A trade-off exists between lower amounts given a bit more detail versus higher amounts "
                 "avoiding noticeable swap transitions. Sensible values to use are:"
                 "\n\t62.5%% spans from eyebrow to eyebrow."
                 "\n\t75.0%% spans from temple to temple."
                 "\n\t87.5%% spans from ear to ear."
                 "\n\t100.0%% is a mugshot.") </s> remove         radius = max(1, round(mask_diameter * radius_ratio / 100))
        kernel_size = int((radius * 2) + 1)
 </s> add         radius = round(max(1., mask_diameter * radius_ratio / 100.))
        kernel_size = radius * 2 + 1 </s> remove                  gpus,
 </s> add                  gpus=1, </s> remove 
        if self.config.get("dssim_loss", False):
            if not predict and side.lower() == "a":
                logger.verbose("Using DSSIM Loss")
            loss_func = DSSIMObjective()
        else:
            loss_func = losses.mean_absolute_error
            if not predict and side.lower() == "a":
                logger.verbose("Using Mean Absolute Error Loss")
 </s> add         loss_dict = {'mae':                     losses.mean_absolute_error,
                     'mse':                     losses.mean_squared_error,
                     'logcosh':                 losses.logcosh,
                     'smooth_l1':               generalized_loss,
                     'l_inf_norm':              l_inf_norm,
                     'ssim':                    DSSIMObjective(),
                     'gmsd':                    gmsd_loss,
                     'pixel_gradient_diff':     gradient_loss}
        img_loss_config = self.config.get("loss_function", "mae")
        mask_loss_config = "mse"
        """
        Set the global options for training

        Loss Documentation
        MAE https://heartbeat.fritz.ai/5-regression-loss-functions-all-machine
            -learners-should-know-4fb140e9d4b0
        MSE https://heartbeat.fritz.ai/5-regression-loss-functions-all-machine
            -learners-should-know-4fb140e9d4b0
        LogCosh https://heartbeat.fritz.ai/5-regression-loss-functions-all-machine
                -learners-should-know-4fb140e9d4b0
        Smooth L1 https://arxiv.org/pdf/1701.03077.pdf
        L_inf_norm https://medium.com/@montjoile/l0-norm-l1-norm-l2-norm-l-infinity
                   -norm-7a7d18a4f40c
        SSIM http://www.cns.nyu.edu/pub/eero/wang03-reprint.pdf
        GMSD https://arxiv.org/ftp/arxiv/papers/1308/1308.3052.pdf
        """
              for filename in default_files:
                  self.load_module(filename, import_path, plugin_type)
  
      def set_globals(self):
        """
        Set the global options for training

        Loss Documentation
        MAE https://heartbeat.fritz.ai/5-regression-loss-functions-all-machine
            -learners-should-know-4fb140e9d4b0
        MSE https://heartbeat.fritz.ai/5-regression-loss-functions-all-machine
            -learners-should-know-4fb140e9d4b0
        LogCosh https://heartbeat.fritz.ai/5-regression-loss-functions-all-machine
                -learners-should-know-4fb140e9d4b0
        Smooth L1 https://arxiv.org/pdf/1701.03077.pdf
        L_inf_norm https://medium.com/@montjoile/l0-norm-l1-norm-l2-norm-l-infinity
                   -norm-7a7d18a4f40c
        SSIM http://www.cns.nyu.edu/pub/eero/wang03-reprint.pdf
        GMSD https://arxiv.org/ftp/arxiv/papers/1308/1308.3052.pdf
        """
          logger.debug("Setting global config")
          section = "global"
          self.add_section(title=section,
                           info="Options that apply to all models" + ADDITIONAL_INFO)
          self.add_item(section=section, title="mask_type", datatype=str, default="none",
keep keep keep keep replace keep keep keep keep keep
 documentation, pep8, style, clarity updates  - Prep for Segmentation (#812)

* documentation, pep8, style, clarity updates

* Update cli.py

* Update _config.py

remove extra mask and coverage

mask type as dropdown

* Update training_data.py

move coverage / LR to global
cut down on loss description

style change
losses working in PR

* simpler logging

* legacy update 
plugins/train/_config.py