feature_column_ops_test.py 文件源码

def testOneHotColumnFromWeightedSparseColumnFails(self):
    ids_column = tf.contrib.layers.sparse_column_with_keys(
        "ids", ["a", "b", "c", "unseen"])
    ids_tensor = tf.SparseTensor(
        values=["c", "b", "a", "c"],
        indices=[[0, 0], [1, 0], [2, 0], [2, 1]],
        shape=[3, 2])
    weighted_ids_column = tf.contrib.layers.weighted_sparse_column(ids_column,
                                                                   "weights")
    weights_tensor = tf.SparseTensor(
        values=[10.0, 20.0, 30.0, 40.0],
        indices=[[0, 0], [1, 0], [2, 0], [2, 1]],
        shape=[3, 2])
    features = {"ids": ids_tensor, "weights": weights_tensor}
    one_hot_column = tf.contrib.layers.one_hot_column(weighted_ids_column)
    with self.test_session():
      tf.initialize_all_variables().run()
      tf.initialize_all_tables().run()
      with self.assertRaisesRegexp(
          ValueError,
          "one_hot_column does not yet support weighted_sparse_column"):
        _ = tf.contrib.layers.input_from_feature_columns(features,
                                                         [one_hot_column])