train.py 文件源码

def dev_step(x_dev, pos_dev, neg_dev):
            """
            Evaluates model on a dev set
            """
            batches = data_helpers.batch_iter(
                list(zip(x_dev, pos_dev, neg_dev)), FLAGS.batch_size, 1)
            loss_sum = 0
            accuracy_sum = 0
            count = 0
            for batch in batches:
                x_batch, pos_batch, neg_batch = zip(*batch)
                feed_dict = {
                  rnn.input_x: x_batch,
                  rnn.input_xpos: pos_batch,
                  rnn.input_xneg: neg_batch,
                  rnn.real_len_x: real_len(x_batch),
                  rnn.real_len_xpos: real_len(pos_batch),
                  rnn.real_len_xneg: real_len(neg_batch),
                  rnn.dropout_keep_prob: 1.0,
                  rnn.batch_size: len(x_batch),
                }
                step, summaries, loss, accuracy = sess.run(
                    [global_step, dev_summary_op, rnn.loss, rnn.accuracy],
                    feed_dict)
                loss_sum = loss_sum + loss
                accuracy_sum = accuracy_sum + loss
                count = count + 1
            loss = loss_sum / count
            accuracy = accuracy_sum / count
            time_str = datetime.datetime.now().isoformat()
            logger.info("{}: step {}, loss {:g}, acc {:g}".format(time_str, step, loss, accuracy))
            dev_summary_writer.add_summary(summaries, step)

        # Generate batches