training_q.py 文件源码

def _print_info(self, data_set, verbose):
        logger.info('Config:')
        logger.info(pprint.pformat(self.cnf))
        data_set.print_info()
        logger.info('Max epochs: %d' % self.num_epochs)
        if verbose > 0:
            util.show_vars(logger, self.trainable_scopes)

        # logger.debug("\n---Number of Regularizable vars in model:")
        # logger.debug(len(tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES)))

        if verbose > 3:
            all_ops = tf.get_default_graph().get_operations()
            logger.debug("\n---All ops in graph")
            names = map(lambda v: v.name, all_ops)
            for n in sorted(names):
                logger.debug(n)

        util.show_layer_shapes(self.training_end_points, logger)