      def load_generator(self):
          """ Pass arguments to TrainingDataGenerator and return object """
          logger.debug("Loading generator: %s", self.side)
          input_size = self.model.input_shape[0]
          output_size = self.model.output_shape[0]
          logger.debug("input_size: %s, output_size: %s", input_size, output_size)
          generator = TrainingDataGenerator(input_size,
                                            output_size,
                                            self.model.training_opts,
                                            self.config)
          return generator
 
</s> remove                                           output_size,
 </s> add                                           output_shapes, </s> remove         logger.debug("Initializing %s: (input_size: %s, output_size: %s, coverage_ratio: %s, "
                     "config: %s)", self.__class__.__name__, input_size, output_size,
 </s> add         logger.debug("Initializing %s: (input_size: %s, output_shapes: %s, coverage_ratio: %s, "
                     "config: %s)", self.__class__.__name__, input_size, output_shapes, </s> remove     def __init__(self, input_size, output_size, coverage_ratio, config):
 </s> add     def __init__(self, input_size, output_shapes, coverage_ratio, config): </s> remove             output_size: Size of the face that comes out of the modell
 </s> add             output_shapes: Shapes that come out of the model </s> remove         batch = batch[1:]   # Remove full size samples from batch
 </s> add         feed = batch[1]
        batch = batch[2:]   # Remove full size samples and feed from batch
        output_shapes = self.model.output_shapes
        logger.debug("input_size: %s, output_shapes: %s", input_size, output_shapes)
      def load_generator(self):
          """ Pass arguments to TrainingDataGenerator and return object """
          logger.debug("Loading generator: %s", self.side)
          input_size = self.model.input_shape[0]
        output_shapes = self.model.output_shapes
        logger.debug("input_size: %s, output_shapes: %s", input_size, output_shapes)
        output_shapes = self.model.output_shapes
        logger.debug("input_size: %s, output_shapes: %s", input_size, output_shapes)
          generator = TrainingDataGenerator(input_size,
                                            output_size,
                                            self.model.training_opts,
                                            self.config)
          return generator
keep keep keep keep replace replace keep keep keep keep keep
 Training: Add Multi-Output Support

- Name output nodes of models
- Add support for multiple outputs in models and in training
- Update loss output format for cli and gui
- Sort graphs tabs on training
- Fix analysis graph for new loss names
- Multi output support in convert 
plugins/train/trainer/_base.py