Args:
        features: [N, N, FEATURE_DIM] nparray of uint8
        pi: [N * N + 1] nparray of float32
        value: float

def make_tf_example(features, pi, value):
    """
    Args:
        features: [N, N, FEATURE_DIM] nparray of uint8
        pi: [N * N + 1] nparray of float32
        value: float
    """
    return tf.train.Example(features=tf.train.Features(feature={
        'x': tf.train.Feature(
            bytes_list=tf.train.BytesList(
                value=[features.tostring()])),
        'pi': tf.train.Feature(
            bytes_list=tf.train.BytesList(
                value=[pi.tostring()])),
        'outcome': tf.train.Feature(
            float_list=tf.train.FloatList(
                value=[value]))}))