def __data_parser(serialized_example):
    features = tf.parse_single_example(serialized_example, features={'keywords_list': tf.FixedLenSequenceFeature([], tf.int64, allow_missing=True), 'ucdoc': tf.FixedLenFeature([], tf.int64), 'keyword': tf.FixedLenFeature([], tf.int64), 'is_click': tf.FixedLenFeature([], tf.float32), 'sl': tf.FixedLenFeature([], tf.int64), 'lr': tf.FixedLenFeature([], tf.float32)})
    keywords_list = tf.cast(features['keywords_list'], tf.int32)
    ucdoc = tf.cast(features['ucdoc'], tf.int32)
    keyword = tf.cast(features['keyword'], tf.int32)
    is_click = tf.cast(features['is_click'], tf.float32)
    sl = tf.cast(features['sl'], tf.int32)
    lr = tf.cast(features['lr'], tf.float32)
    return (ucdoc, keyword, keywords_list, is_click, sl, lr)
def __data_parser(serialized_example):
    features = tf.parse_single_example(serialized_example, features={'keywords_list': tf.FixedLenSequenceFeature([], tf.int64, allow_missing=True), 'ucdoc': tf.FixedLenFeature([], tf.int64), 'keyword': tf.FixedLenFeature([], tf.int64), 'is_click': tf.FixedLenFeature([], tf.float32), 'sl': tf.FixedLenFeature([], tf.int64), 'lr': tf.FixedLenFeature([], tf.float32)})
    keywords_list = tf.cast(features['keywords_list'], tf.int32)
    ucdoc = tf.cast(features['ucdoc'], tf.int32)
    keyword = tf.cast(features['keyword'], tf.int32)
    is_click = tf.cast(features['is_click'], tf.float32)
    sl = tf.cast(features['sl'], tf.int32)
    lr = tf.cast(features['lr'], tf.float32)
    return (ucdoc, keyword, keywords_list, is_click, sl, lr)