  class ModelBase():
      """ Base class that all models should inherit from """
      def __init__(self,
                   model_dir,
                   gpus,
                   configfile=None,
                   snapshot_interval=0,
                   no_logs=False,
                   warp_to_landmarks=False,
                   augment_color=True,
 
</s> remove                 logger.debug("face loss func: %s", loss_func)
                loss_funcs.append(loss_func)
 </s> add                 loss_funcs.append(loss_dict[img_loss_config])
                logger.debug("face loss func: %s", img_loss_config) </s> remove         """ Set the global options for training """
 </s> add         """
        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
        """ </s> remove         argument_list.append({"opts": ("-tia", "--timelapse-input-A"),
                              "action": DirFullPaths,
                              "dest": "timelapse_input_a",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of A "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-B parameter."})
        argument_list.append({"opts": ("-tib", "--timelapse-input-B"),
                              "action": DirFullPaths,
                              "dest": "timelapse_input_b",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of B "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-A parameter."})
        argument_list.append({"opts": ("-to", "--timelapse-output"),
                              "action": DirFullPaths,
                              "dest": "timelapse_output",
                              "default": None,
                              "help": "The output folder for the timelapse. "
                                      "If the input folders are supplied but "
                                      "no output folder, it will default to "
                                      "your model folder /timelapse/"})
 </s> add  </s> remove         if swap:
            model = self.predictors["a"]
        else:
            model = self.predictors["b"]
 </s> add         side = "a" if swap else "b"
        model = self.predictors[side]
                 gpus=1,
  class ModelBase():
      """ Base class that all models should inherit from """
      def __init__(self,
                   model_dir,
                 gpus=1,
                   configfile=None,
                   snapshot_interval=0,
                   no_logs=False,
                   warp_to_landmarks=False,
                   augment_color=True,
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/model/_base.py