      """
  
      def __init__(self, filename, network_type, side, network):
          logger.debug("Initializing %s: (filename: '%s', network_type: '%s', side: '%s', "
                       "network: %s", self.__class__.__name__, filename, network_type,
                       side, network)
          self.filename = filename
          self.type = network_type.lower()
          self.side = side
          self.name = self.set_name()
          self.network = network
 
</s> remove     def __init__(self, filename, network_type, side, network):
 </s> add     def __init__(self, filename, network_type, side, network, is_output): </s> remove         logger.debug("network_type: '%s', side: '%s', network: '%s'", network_type, side, network)
 </s> add         logger.debug("network_type: '%s', side: '%s', network: '%s', is_output: %s",
                     network_type, side, network, is_output) </s> remove     network:      Define network to this.
 </s> add     network:    Define network to this.
    is_output:  Set to True to indicate that this network is an output to the Autoencoder </s> remove     def add_network(self, network_type, side, network):
 </s> add     def add_network(self, network_type, side, network, is_output=False): </s> remove         self.networks[name] = NNMeta(str(self.model_dir / filename), network_type, side, network)
 </s> add         self.networks[name] = NNMeta(str(self.model_dir / filename),
                                     network_type,
                                     side,
                                     network,
                                     is_output)
                     "network: %s, is_output: %s", self.__class__.__name__, filename,
                     network_type, side, network, is_output)
      """
  
      def __init__(self, filename, network_type, side, network):
          logger.debug("Initializing %s: (filename: '%s', network_type: '%s', side: '%s', "
                     "network: %s, is_output: %s", self.__class__.__name__, filename,
                     network_type, side, network, is_output)
                     "network: %s, is_output: %s", self.__class__.__name__, filename,
                     network_type, side, network, is_output)
          self.filename = filename
          self.type = network_type.lower()
          self.side = side
          self.name = self.set_name()
          self.network = network
keep keep keep keep replace replace 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