didineuralmodel.py 文件源码

def run_graph(self):
        logging.debug("computeGraph")
        with tf.Session(graph=self.graph) as sess:
            tf.initialize_all_variables().run()
            logging.debug("Initialized")
            for step in range(1, self.num_steps + 1):
                summary, _ , train_loss, train_metrics= sess.run([self.merged, self.train_step, self.loss, self.accuracy], feed_dict=self.feed_dict("train"))
                self.train_writer.add_summary(summary, step)

                if step % 100 == 0:
                    summary, validation_loss, validation_metrics = sess.run([self.merged, self.loss, self.accuracy], feed_dict=self.feed_dict("validation"))
                    self.test_writer.add_summary(summary, step)
#                     loss_train = sess.run(self.loss, feed_dict=self.feed_dict("validation_wholetrain"))
                    logging.info("Step {}/{}, train/test: {:.3f}/{:.3f}, train/test loss: {:.3f}/{:.3f}".format(step, self.num_steps, train_metrics, validation_metrics,\
                                                                                                                train_loss, validation_loss))
                    if self.get_stop_decisision(step, -validation_metrics):
                        logging.info("stop here due to early stopping")
                        return 

#                     y_pred = sess.run(self.y_pred, feed_dict=self.feed_dict("validation"))
#                     logging.info("validation mape :{:.3f}".format(mean_absolute_percentage_error(self.y_validation.reshape(-1), y_pred.reshape(-1))))
        return