wide_deep_evaluate_predict.py 文件源码

def evaluate_and_prdict(model_dir):
    """
    Method evaluate validation dataset and predict target class for test dataset
    :param model_dir:
    :return:
    """
    m=build_estimator(model_dir=model_dir)
    results = m.evaluate(input_fn=lambda: input_fn(5000,test_data), steps=2000)
    for key in sorted(results):
        print("%s: %s" % (key, results[key]))
    y = m.predict(input_fn=lambda :input_fn_eval(5000,test_data),as_iterable=True)
    file_test= open("prediction_final.txt", "w")
    for x in y:
        file_test.write('%s' % x+"\n")
    with tf.Session() as sess:
        init = tf.group(tf.initialize_all_variables(), tf.initialize_local_variables())
        sess = tf.Session(config=tf.ConfigProto())
        sess.run(init)
        coord = tf.train.Coordinator()
        threads = tf.train.start_queue_runners(sess=sess,coord=coord)
        coord.request_stop()
        coord.join(threads)
        sess.close()