tune_mnist_ray.py 文件源码

def train(config={'activation': 'relu'}, reporter=None):
    global FLAGS, status_reporter, activation_fn
    status_reporter = reporter
    activation_fn = getattr(tf.nn, config['activation'])
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--data_dir', type=str, default='/tmp/tensorflow/mnist/input_data',
        help='Directory for storing input data')
    FLAGS, unparsed = parser.parse_known_args()
    tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)


# !!! Example of using the ray.tune Python API !!!