diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index f5704473e6d43efa32e266c90b37f793bc8a6f88..d6b9d1108c5970798a99260c7d5a2024319f47f3 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -371,7 +371,7 @@ function run_test() {
     Running unit tests ...
     ========================================
 EOF
-        # ctest --output-on-failure
+        ctest --output-on-failure
         # make install should also be test when unittest
         make install -j `nproc`
         pip install ${INSTALL_PREFIX:-/paddle/build}/opt/paddle/share/wheels/*.whl
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 7e5389d49dd0f5c41210d93f72c4fb22c7c3f1fe..99f1a91119232c0bb23b45e2944e319fb6c1fed3 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -7504,11 +7504,12 @@ def hash(input, hash_size, num_hash=1, name=None):
         input (Variable): The input variable which is a one-hot word.
         hash_size (int): The space size for hash algorithm.
         num_hash (int): The times of hash, default 1.
+        name (str, default None): The name of this layer.
      Returns:
         Variable: The hash result variable which is a LoDTensor.
      Examples:
         .. code-block:: python
-             word_dict = paddle.dataset.imdb.word_dict()
+            word_dict = paddle.dataset.imdb.word_dict()
             x = fluid.layers.data(shape[1], dtype='int32', lod_level=1)
             out = fluid.layers.hash(input=x, len(word_dict))
     """