          self.name = self.set_name()
          self.network = network
          self.network.name = self.name
          self.config = network.get_config()  # For pingpong restore
          self.weights = network.get_weights()  # For pingpong restore
          logger.debug("Initialized %s", self.__class__.__name__)
  
 
</s> remove                      "network: %s", self.__class__.__name__, filename, network_type,
                     side, network)
 </s> add                      "network: %s, is_output: %s", self.__class__.__name__, filename,
                     network_type, side, network, is_output) </s> remove     @staticmethod
    def update_kwargs(kwargs):
        """ Set the default kernel initializer to he_uniform() """
        kwargs["kernel_initializer"] = kwargs.get("kernel_initializer", he_uniform())
 </s> add     def update_kwargs(self, kwargs):
        """ Update Kwargs for conv2D and Seperable conv2D layers.
            Set the default kernel initializer to conv_aware or he_uniform()
            if a specific initializer has not been passed in """
        if self.use_convaware_init:
            default = ConvolutionAware()
            if self.first_run:
                # Indicate the Convolutional Aware should be calculated on first run
                default._init = True  # pylint:disable=protected-access
        else:
            default = he_uniform()
        kwargs["kernel_initializer"] = kwargs.get("kernel_initializer", default)
        logger.debug("Set default kernel_initializer to: %s", kwargs["kernel_initializer"]) </s> remove     def __init__(self, use_subpixel=False, use_icnr_init=False, use_reflect_padding=False):
        logger.debug("Initializing %s: (use_subpixel: %s, use_icnr_init: %s, use_reflect_padding: %s)",
                     self.__class__.__name__, use_subpixel, use_icnr_init, use_reflect_padding)
 </s> add     def __init__(self, use_subpixel=False, use_icnr_init=False, use_convaware_init=False,
                 use_reflect_padding=False, first_run=True):
        logger.debug("Initializing %s: (use_subpixel: %s, use_icnr_init: %s, use_convaware_init: "
                     "%s, use_reflect_padding: %s, first_run: %s)",
                     self.__class__.__name__, use_subpixel, use_icnr_init, use_convaware_init,
                     use_reflect_padding, first_run)
        self.first_run = first_run
        self.is_output = is_output
          self.name = self.set_name()
          self.network = network
        self.is_output = is_output
          self.network.name = self.name
          self.config = network.get_config()  # For pingpong restore
          self.weights = network.get_weights()  # For pingpong restore
          logger.debug("Initialized %s", self.__class__.__name__)
  
keep add keep keep keep keep keep
 Add Convolutional Aware Initialization (#795)

* Training: Add Convolutional Aware Initialization config option

* Centralize Conv2D layer for handling initializer

* Add 'is-output' to NNMeta to indicate that network is an output to the Model 
plugins/train/model/_base.py