util.py

import time, sys, os, random
import numpy as np
import tensorflow as tf

def load_weights(sess,path,scope=None):
    if os.path.exists(path):
        # Restore saved weights
        print('Restoring saved model ... ')
        # Find out from which epoch we are restoring weights
        epoch = int(path.split('/')[-1].replace('epoch=',''))
        # Create model saver
        if scope is None:
            saver = tf.train.Saver()
        else:
            saver = tf.train.Saver(var_list=tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=scope))
        #end
        saver.restore(sess, "%s/model.ckpt" % path)
        return epoch
    else:
        raise Exception('Path does not exist!')
    #end if
#end

def save_weights(sess,path,scope=None):
    # Create /tmp/ directory to save weights
    if not os.path.exists(path):
        os.makedirs(path)
    #end if
    # Create model saver
    if scope is None:
        saver = tf.train.Saver()
    else:
        saver = tf.train.Saver(var_list=tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=scope))
    #end
    saver.save(sess, "%s/model.ckpt" % path)
    print('Model saved in path: {path}\n'.format(path=path))
#end