| 657 | |
| 658 | |
| 659 | def eval(sess_config, input_hooks, model, data_init_op, steps, checkpoint_dir): |
| 660 | model.is_training = False |
| 661 | hooks = [] |
| 662 | hooks.extend(input_hooks) |
| 663 | |
| 664 | scaffold = tf.train.Scaffold( |
| 665 | local_init_op=tf.group(tf.local_variables_initializer(), data_init_op)) |
| 666 | session_creator = tf.train.ChiefSessionCreator( |
| 667 | scaffold=scaffold, checkpoint_dir=checkpoint_dir, config=sess_config) |
| 668 | writer = tf.summary.FileWriter(os.path.join(checkpoint_dir, 'eval')) |
| 669 | merged = tf.summary.merge_all() |
| 670 | |
| 671 | with tf.train.MonitoredSession(session_creator=session_creator, |
| 672 | hooks=hooks) as sess: |
| 673 | for _in in range(1, steps + 1): |
| 674 | if (_in != steps): |
| 675 | sess.run([model.acc_op, model.auc_op]) |
| 676 | if (_in % 1000 == 0): |
| 677 | print("Evaluation complete:[{}/{}]".format(_in, steps)) |
| 678 | else: |
| 679 | eval_acc, eval_auc, events = sess.run( |
| 680 | [model.acc_op, model.auc_op, merged]) |
| 681 | writer.add_summary(events, _in) |
| 682 | print("Evaluation complete:[{}/{}]".format(_in, steps)) |
| 683 | print("ACC = {}\nAUC = {}".format(eval_acc, eval_auc)) |
| 684 | |
| 685 | |
| 686 | def main(tf_config=None, server=None): |