diff --git a/demo/recommendation/api_train_v2.py b/demo/recommendation/api_train_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..64dff9ae4328582bbe1922de218bd1c3f07a6302
--- /dev/null
+++ b/demo/recommendation/api_train_v2.py
@@ -0,0 +1,12 @@
+import paddle.v2 as paddle
+
+
+def main():
+    movie_title_dict = paddle.dataset.movielens.get_movie_title_dict()
+    title_word_count = len(movie_title_dict)
+
+    paddle.layer.mixed
+
+
+if __name__ == '__main__':
+    main()
diff --git a/python/paddle/v2/dataset/__init__.py b/python/paddle/v2/dataset/__init__.py
index 9647e9850332b795f6480d26e4f9c736129782ae..a947edd2cce649b74649cabc32321c62f5a1bd64 100644
--- a/python/paddle/v2/dataset/__init__.py
+++ b/python/paddle/v2/dataset/__init__.py
@@ -1,3 +1,5 @@
 import mnist
+import cifar
+import movielens
 
-__all__ = ['mnist']
+__all__ = ['mnist', 'cifar', 'movielens']
diff --git a/python/paddle/v2/dataset/movielens.py b/python/paddle/v2/dataset/movielens.py
index dcffcff2f58c63d451761d37f14127d730faf621..b66448fafe42168e100037dd4ac807a571f152e6 100644
--- a/python/paddle/v2/dataset/movielens.py
+++ b/python/paddle/v2/dataset/movielens.py
@@ -4,7 +4,7 @@ import re
 import random
 import functools
 
-__all__ = ['train_creator', 'test_creator']
+__all__ = ['train_creator', 'test_creator', 'get_movie_title_dict']
 
 
 class MovieInfo(object):
@@ -40,7 +40,8 @@ USER_INFO = None
 def __initialize_meta_info__():
     fn = download(
         url='http://files.grouplens.org/datasets/movielens/ml-1m.zip',
-        md5='c4d9eecfca2ab87c1945afe126590906')
+        module_name='movielens',
+        md5sum='c4d9eecfca2ab87c1945afe126590906')
     global MOVIE_INFO
     if MOVIE_INFO is None:
         pattern = re.compile(r'^(.*)\((\d+)\)$')
@@ -107,6 +108,11 @@ train_creator = functools.partial(__reader_creator__, is_test=False)
 test_creator = functools.partial(__reader_creator__, is_test=True)
 
 
+def get_movie_title_dict():
+    __initialize_meta_info__()
+    return MOVIE_TITLE_DICT
+
+
 def unittest():
     for train_count, _ in enumerate(train_creator()()):
         pass