Model Save and Load

tensorflow_save_model.py

def save_model(sess, saver, checkpoint_dir, model_name, step):
    if not os.path.exists(checkpoint_dir):
        os.makedirs(checkpoint_dir)
    saver.save(sess, os.path.join(checkpoint_dir, model_name), global_step=step)
    
def load_model(sess, saver, checkpoint_dir):
    print("[*] Reading checkpoints...")
    ckpt = tf.train.get_checkpoint_state(checkpoint_dir)
    if ckpt and ckpt.model_checkpoint_path:
        ckpt_name = os.path.basename(ckpt.model_checkpoint_path)
        saver.restore(sess, os.path.join(checkpoint_dir, ckpt_name))
        return True
    return False