diff --git a/python/paddle/dataset/common.py b/python/paddle/dataset/common.py
index 68660601c161d2332b17b448fae089506238ba78..424c121e82eccf5319295ac9a718592ce4fccd61 100644
--- a/python/paddle/dataset/common.py
+++ b/python/paddle/dataset/common.py
@@ -17,6 +17,7 @@ import hashlib
 import os
 import errno
 import shutil
+import six
 import sys
 import importlib
 import paddle.dataset
@@ -93,6 +94,8 @@ def download(url, module_name, md5sum, save_name=None):
                 dl = 0
                 total_length = int(total_length)
                 for data in r.iter_content(chunk_size=4096):
+		    if six.PY2:
+			data = six.b(data)
                     dl += len(data)
                     f.write(data)
                     done = int(50 * dl / total_length)
diff --git a/python/paddle/dataset/flowers.py b/python/paddle/dataset/flowers.py
index 527044b415533cc640e3cfc5837c08ab0f8b74b1..fee127dfb35956bd582f25e2ead913cb7ebf0e03 100644
--- a/python/paddle/dataset/flowers.py
+++ b/python/paddle/dataset/flowers.py
@@ -28,11 +28,12 @@ Graphics and Image Processing (2008)
 http://www.robots.ox.ac.uk/~vgg/publications/papers/nilsback08.{pdf,ps.gz}.
 
 """
-import cPickle
 import itertools
 import functools
 from common import download
 import tarfile
+import six
+from six.moves import cPickle as pickle
 import scipy.io as scio
 from paddle.dataset.image import *
 from paddle.reader import *
@@ -41,6 +42,7 @@ import numpy as np
 from multiprocessing import cpu_count
 __all__ = ['train', 'test', 'valid']
 
+
 DATA_URL = 'http://www.robots.ox.ac.uk/~vgg/data/flowers/102/102flowers.tgz'
 LABEL_URL = 'http://www.robots.ox.ac.uk/~vgg/data/flowers/102/imagelabels.mat'
 SETID_URL = 'http://www.robots.ox.ac.uk/~vgg/data/flowers/102/setid.mat'
@@ -111,8 +113,11 @@ def reader_creator(data_file,
         for file in open(file_list):
             file = file.strip()
             batch = None
-            with open(file, 'r') as f:
-                batch = cPickle.load(f)
+            with open(file, 'rb') as f:
+                if six.PY2:
+                    batch = pickle.load(f)
+                else:
+                    batch = pickle.load(f, encoding='bytes')
             data = batch['data']
             labels = batch['label']
             for sample, label in itertools.izip(data, batch['label']):