              datatype=bool,
              default=True,
              group="loss",
              info="Image loss function is weighted by mask presence. For areas of "
                   "the image without the facial mask, reconstuction errors will be "
                   "ignored while the masked face area is prioritized. May increase "
                   "overall quality by focusing attention on the core face area.")
          self.add_item(
              section=section,
              title="mask_type",
 
</s> remove                  "\n\t rms-prop - Root Mean Square Propogation. Maintains a moving (discounted) "
 </s> add                  "\n\t rms-prop - Root Mean Square Propagation. Maintains a moving (discounted) " </s> remove                  "suspectible to outliers and typically produces slightly blurrier results."
                 "\n\t LogCosh - log(cosh(x)) acts similiar to MSE for small errors and to "
 </s> add                  "susceptible to outliers and typically produces slightly blurrier results."
                 "\n\t LogCosh - log(cosh(x)) acts similar to MSE for small errors and to " </s> remove                  "towards its average value in the training dataset. As an avg, it will be "
                 "suspectible to outliers and typically produces slightly blurrier results.")
 </s> add                  "towards its average value in the training dataset. As an average, it will be "
                 "susceptible to outliers and typically produces slightly blurrier results.") </s> remove                  "between two images. Allows for large color shifts,but maintains the structure "
 </s> add                  "between two images. Allows for large color shifts, but maintains the structure "
                 "the image without the facial mask, reconstruction errors will be "
              datatype=bool,
              default=True,
              group="loss",
              info="Image loss function is weighted by mask presence. For areas of "
                 "the image without the facial mask, reconstruction errors will be "
                   "ignored while the masked face area is prioritized. May increase "
                   "overall quality by focusing attention on the core face area.")
          self.add_item(
              section=section,
              title="mask_type",
keep keep keep keep replace keep keep keep keep keep
 Training updates:
  - Expose optimizer epsilon param
  - Add NaN protection
GUI - slider - add support for discreet values 
plugins/train/_config.py