viddesc_model.py 文件源码

def setOptimizer(self, **kwargs):

        """
        Sets a new optimizer for the Translation_Model.
        :param **kwargs:
        """

        # compile differently depending if our model is 'Sequential' or 'Graph'
        if self.verbose > 0:
            logging.info("Preparing optimizer and compiling.")
        if self.params['OPTIMIZER'].lower() == 'adam':
            optimizer = Adam(lr=self.params['LR'], clipnorm=self.params['CLIP_C'])
        elif self.params['OPTIMIZER'].lower() == 'rmsprop':
            optimizer = RMSprop(lr=self.params['LR'], clipnorm=self.params['CLIP_C'])
        elif self.params['OPTIMIZER'].lower() == 'nadam':
            optimizer = Nadam(lr=self.params['LR'], clipnorm=self.params['CLIP_C'])
        elif self.params['OPTIMIZER'].lower() == 'adadelta':
            optimizer = Adadelta(lr=self.params['LR'], clipnorm=self.params['CLIP_C'])
        elif self.params['OPTIMIZER'].lower() == 'sgd':
            optimizer = SGD(lr=self.params['LR'], clipnorm=self.params['CLIP_C'])
        else:
            logging.info('\tWARNING: The modification of the LR is not implemented for the chosen optimizer.')
            optimizer = eval(self.params['OPTIMIZER'])
        self.model.compile(optimizer=optimizer, loss=self.params['LOSS'],
                           sample_weight_mode='temporal' if self.params['SAMPLE_WEIGHTS'] else None)