d97188ee62bc0627235578485c5df7d3245fa1ed,example6.py,,,#,14

Before Change

        316, 245, 232, 175, 149, 263, 387, 283, 391, 211, 396, 352, 345, 258, 253, 163, 140, 293, 194, 342, 161, 358,
        271, 156, 260, 384, 153, 277, 214]

laws_str = [str(x) for x in laws]


def get_encodes(x):

After Change

tf.logging.set_verbosity(tf.logging.INFO)

with open("README.md") as fp:
    data = [v for v in fp if v.strip()]
    bc = BertClient()
    list_vec = bc.encode(data)
    list_label = [0 for _ in data]  // a dummy list of all-zero labels

// write tfrecords

with tf.python_io.TFRecordWriter("tmp.tfrecord") as writer:
    def create_float_feature(values):
        return tf.train.Feature(float_list=tf.train.FloatList(value=values))


    def create_int_feature(values):
        return tf.train.Feature(int64_list=tf.train.Int64List(value=list(values)))


    for (vec, label) in zip(list_vec, list_label):
        features = {"features": create_float_feature(vec), "labels": create_int_feature([label])}
        tf_example = tf.train.Example(features=tf.train.Features(feature=features))
        writer.write(tf_example.SerializeToString())

// read tfrecords and build dataset from it

num_hidden_unit = 768


def _decode_record(record):

Instances