feature_column_test.py 文件源码

def testWeightedSparseColumnDtypes(self):
    ids = tf.contrib.layers.sparse_column_with_keys(
        "ids", ["marlo", "omar", "stringer"])
    weighted_ids = tf.contrib.layers.weighted_sparse_column(ids, "weights")
    self.assertDictEqual(
        {"ids": tf.VarLenFeature(tf.string),
         "weights": tf.VarLenFeature(tf.float32)},
        weighted_ids.config)

    weighted_ids = tf.contrib.layers.weighted_sparse_column(ids, "weights",
                                                            dtype=tf.int32)
    self.assertDictEqual(
        {"ids": tf.VarLenFeature(tf.string),
         "weights": tf.VarLenFeature(tf.int32)},
        weighted_ids.config)

    with self.assertRaisesRegexp(ValueError,
                                 "dtype is not convertible to float"):
      weighted_ids = tf.contrib.layers.weighted_sparse_column(ids, "weights",
                                                              dtype=tf.string)