          """ input_size: Size of the face input into the model
              output_size: Size of the face that comes out of the modell
              coverage_ratio: Coverage ratio of full image. Eg: 256 * 0.625 = 160
          """
          logger.debug("Initializing %s: (input_size: %s, output_size: %s, coverage_ratio: %s, "
                       "config: %s)", self.__class__.__name__, input_size, output_size,
                       coverage_ratio, config)
          self.config = config
          # Transform and Warp args
          self.input_size = input_size
          self.output_size = output_size
 
</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     def __init__(self, input_size, output_size, coverage_ratio, config):
 </s> add     def __init__(self, input_size, output_shapes, coverage_ratio, config): </s> remove         self.output_size = output_size
 </s> add         self.output_sizes = [shape[1] for shape in output_shapes if shape[2] == 3]
        logger.debug("Output sizes: %s", self.output_sizes) </s> remove         output_size = self.model.output_shape[0]
        logger.debug("input_size: %s, output_size: %s", input_size, output_size)
 </s> add         output_shapes = self.model.output_shapes
        logger.debug("input_size: %s, output_shapes: %s", input_size, output_shapes) </s> remove                                           output_size,
 </s> add                                           output_shapes,
        logger.debug("Initializing %s: (input_size: %s, output_shapes: %s, coverage_ratio: %s, "
                     "config: %s)", self.__class__.__name__, input_size, output_shapes,
          """ input_size: Size of the face input into the model
              output_size: Size of the face that comes out of the modell
              coverage_ratio: Coverage ratio of full image. Eg: 256 * 0.625 = 160
          """
        logger.debug("Initializing %s: (input_size: %s, output_shapes: %s, coverage_ratio: %s, "
                     "config: %s)", self.__class__.__name__, input_size, output_shapes,
        logger.debug("Initializing %s: (input_size: %s, output_shapes: %s, coverage_ratio: %s, "
                     "config: %s)", self.__class__.__name__, input_size, output_shapes,
                       coverage_ratio, config)
          self.config = config
          # Transform and Warp args
          self.input_size = input_size
          self.output_size = output_size
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 
lib/training_data.py