diff --git a/python/paddle/v2/data_set/config.py b/python/paddle/v2/data_set/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..69e96d65ef1ef868aff5d46ddf3af250ca11e641
--- /dev/null
+++ b/python/paddle/v2/data_set/config.py
@@ -0,0 +1,8 @@
+import os
+
+__all__ = ['DATA_HOME']
+
+DATA_HOME = os.path.expanduser('~/.cache/paddle_data_set')
+
+if not os.path.exists(DATA_HOME):
+    os.makedirs(DATA_HOME)
diff --git a/python/paddle/v2/data_set/mnist.py b/python/paddle/v2/data_set/mnist.py
index 34f61bb9f632eaa8daacafc67ff5a7f05c20cf7f..6f35acf683686e3030e4c89784486ea0a3c0317f 100644
--- a/python/paddle/v2/data_set/mnist.py
+++ b/python/paddle/v2/data_set/mnist.py
@@ -1,61 +1,53 @@
 import sklearn.datasets.mldata
 import sklearn.model_selection
 import numpy
+from config import DATA_HOME
 
-__all__ = ['MNISTReader', 'train_reader_creator', 'test_reader_creator']
+__all__ = ['MNIST', 'train_creator', 'test_creator']
 
-DATA_HOME = None
 
+def __mnist_reader_creator__(data, target):
+    def reader():
+        n_samples = data.shape[0]
+        for i in xrange(n_samples):
+            yield (data[i] / 255.0).astype(numpy.float32), int(target[i])
 
-def __mnist_reader__(data, target):
-    n_samples = data.shape[0]
-    for i in xrange(n_samples):
-        yield data[i].astype(numpy.float32), int(target[i])
+    return reader
 
 
-class MNISTReader(object):
+class MNIST(object):
     """
     mnist dataset reader. The `train_reader` and `test_reader` method returns
     a iterator of each sample. Each sample is combined by 784-dim float and a
     one-dim label
     """
 
-    def __init__(self, random_state):
+    def __init__(self, random_state=0, test_size=10000, **options):
         data = sklearn.datasets.mldata.fetch_mldata(
             "MNIST original", data_home=DATA_HOME)
-        n_train = 60000
         self.X_train, self.X_test, self.y_train, self.y_test = sklearn.model_selection.train_test_split(
-            data.data / 255.0,
-            data.target.astype("int"),
-            train_size=n_train,
-            random_state=random_state)
+            data.data,
+            data.target,
+            test_size=test_size,
+            random_state=random_state,
+            **options)
 
-    def train_reader(self):
-        return __mnist_reader__(self.X_train, self.y_train)
+    def train_creator(self):
+        return __mnist_reader_creator__(self.X_train, self.y_train)
 
-    def test_reader(self):
-        return __mnist_reader__(self.X_test, self.y_test)
+    def test_creator(self):
+        return __mnist_reader_creator__(self.X_test, self.y_test)
 
 
-__default_instance__ = MNISTReader(0)
-
-
-def train_reader_creator():
-    """
-    Default train set reader creator.
-    """
-    return __default_instance__.train_reader
-
-
-def test_reader_creator():
-    """
-    Default test set reader creator.
-    """
-    return __default_instance__.test_reader
+__default_instance__ = MNIST()
+train_creator = __default_instance__.train_creator
+test_creator = __default_instance__.test_creator
 
 
 def unittest():
-    assert len(list(train_reader_creator()())) == 60000
+    size = 12045
+    mnist = MNIST(test_size=size)
+    assert len(list(mnist.test_creator()())) == size
 
 
 if __name__ == '__main__':