deepy/trainers/trainers.py
def optimization_updates(self, params, gradients):
        """
        Return updates from optimization.
        """
        updates, free_parameters = optimize_updates(params, gradients, self.config)
        self.network.free_parameters.extend(free_parameters)
        logging.info("Added %d free parameters for optimization" % len(free_parameters))
        return updates
def optimization_updates(self, params, gradients):
        updates, free_parameters = optimize_updates(params, gradients, self.config)
        self.network.free_parameters.extend(free_parameters)
        logging.info("Added %d free parameters for optimization" % len(free_parameters))
        return updates
def optimization_updates ( self , params , gradients ) : updates , free_parameters = optimize_updates ( params , gradients , self . config ) self . network . free_parameters . extend ( free_parameters ) logging . info ( "Added %d free parameters for optimization" % len ( free_parameters ) ) return updates
Return updates from optimization.
Return updates from optimization .