import tensorflow as tf

                saver.save(sess, FLAGS.checkpoint_path + 'model.ckpt', global_step=global_step)

            if step % FLAGS.save_summary_steps == 0:
                _, tl, summary_str = sess.run([train_op, total_loss, summary_op], feed_dict={input_images: images,
                                                                                             input_score_maps: score_maps,
                                                                                             input_geo_maps: geo_maps,
                                                                                             input_training_masks: training_masks})
                summary_writer.add_summary(summary_str, global_step=step)
    print("Final Train Accuracy", tl)
    E2Etime = time.time() - start1
    print("E2E Training Duration sec", E2Etime)
    print("avg time per step", avg_time_per_step1)
    print("FPS {:.2f}".format(sum(performs)/len(performs)))

if __name__ == '__main__':
    tf.app.run()
