models.py 文件源码

def print_training_params(self, cgs, training_params):

        enc_dec_param_dict = merge(self.encoder.get_params(),
                                   self.decoder.get_params())

        # Print which parameters are excluded
        for k, v in cgs.iteritems():
            excluded_all = list(set(v.parameters) - set(training_params[k]))
            for p in excluded_all:
                logger.info(
                    'Excluding from training of CG[{}]: {}'
                    .format(k, [key for key, val in
                                enc_dec_param_dict.iteritems()
                                if val == p][0]))
            logger.info(
                'Total number of excluded parameters for CG[{}]: [{}]'
                .format(k, len(excluded_all)))

        for k, v in training_params.iteritems():
            for p in v:
                logger.info('Training parameter from CG[{}]: {}'
                            .format(k, p.name))
            logger.info(
                'Total number of parameters will be trained for CG[{}]: [{}]'
                .format(k, len(v)))