eval.py

from hparams import hyperparams as hp
import tensorflow as tf
from model import Graph
import os

def main(self):
    mode = 'eval'
    g = Graph(mode=mode)
    print('{} graph loaded.'.format(mode))
    saver = tf.train.Saver()
    gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.5)
    with tf.Session(config=tf.ConfigProto(
            gpu_options=gpu_options, log_device_placement=False, allow_soft_placement=True)) as sess:
        writer = tf.summary.FileWriter(hp.log_dir, sess.graph)
        loaded = False
        try:
            try:
                print('try to load trained model in {} ...'.format(hp.model_dir))
                saver.restore(sess, tf.train.latest_checkpoint(hp.model_dir))
                loaded = True
            finally:
                if loaded is False:
                    print('load trained model failed in eval, please check ...')
                    exit(0)
                while 1:
                    _, loss, summary, steps, y_hat = sess.run([g.train_op, g.loss, g.merged, g.global_step, g.y_hat])
                    writer.add_summary(summary, steps)
                    saver.save(sess, os.path.join(hp.model_dir, 'eval_model_{}'.format(steps)))
                    print('eval mode \t steps  : {}, loss : {}'.format(steps, loss))
        except:
            print('eval over.')

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