deeppavlov/core/models/keras_model.py
def process_event(self, event_name: str, data: dict):
        """
        Process event after epoch
        Args:
            event_name: whether event is send after epoch or batch.
                    Set of values: ``"after_epoch", "after_batch"``
            data: event data (dictionary)

        Returns:
            None
        """
        if (isinstance(self.opt.get("learning_rate", None), float) and
                isinstance(self.opt.get("learning_rate_decay", None), float)):
            pass
        else:
            if event_name == 'after_train_log':
                if (self.get_learning_rate_variable() is not None) and ('learning_rate' not in data):
                    data['learning_rate'] = float(K.get_value(self.get_learning_rate_variable()))
                    # data['learning_rate'] = self._lr
                if (self.get_momentum_variable() is not None) and ('momentum' not in data):
                    data['momentum'] = float(K.get_value(self.get_momentum_variable()))
                    # data['momentum'] = self._mom
            else:
                super().process_event(event_name, data)
def process_event(self, event_name: str, data: dict):
        """
        Process event after epoch
        Args:
            event_name: whether event is send after epoch or batch.
                    Set of values: ``"after_epoch", "after_batch"``
            data: event data (dictionary)

        Returns:
            None
        """
        if (isinstance(self.opt.get("learning_rate", None), float) and
                isinstance(self.opt.get("learning_rate_decay", None), float)):
            pass
        else:
            if event_name == 'after_train_log':
                if (self.get_learning_rate_variable() is not None) and ('learning_rate' not in data):
                    data['learning_rate'] = float(K.get_value(self.get_learning_rate_variable()))
                    # data['learning_rate'] = self._lr
                if (self.get_momentum_variable() is not None) and ('momentum' not in data):
                    data['momentum'] = float(K.get_value(self.get_momentum_variable()))
                    # data['momentum'] = self._mom
            else:
                super().process_event(event_name, data)
def process_event ( self , event_name : str , data : dict ) : if ( isinstance ( self . opt . get ( "learning_rate" , None ) , float ) and isinstance ( self . opt . get ( "learning_rate_decay" , None ) , float ) ) : pass else : if event_name == 'after_train_log' : if ( self . get_learning_rate_variable ( ) is not None ) and ( 'learning_rate' not in data ) : data [ 'learning_rate' ] = float ( K . get_value ( self . get_learning_rate_variable ( ) ) ) # data['learning_rate'] = self._lr if ( self . get_momentum_variable ( ) is not None ) and ( 'momentum' not in data ) : data [ 'momentum' ] = float ( K . get_value ( self . get_momentum_variable ( ) ) ) # data['momentum'] = self._mom else : super ( ) . process_event ( event_name , data )
Process event after epoch
        Args:
            event_name: whether event is send after epoch or batch.
                    Set of values: ``"after_epoch", "after_batch"``
            data: event data (dictionary)

        Returns:
            None
Process event after epoch Args : event_name : whether event is send after epoch or batch . Set of values : after_epoch after_batch data : event data ( dictionary )