diff --git a/fluid/text_matching_on_quora/configs/__init__.py b/fluid/text_matching_on_quora/configs/__init__.py
index de786797273bdc1fe12691d9373db14bed10bf64..a8c3e13b8a203a199572c1bc0df3214bc69ee3df 100755
--- a/fluid/text_matching_on_quora/configs/__init__.py
+++ b/fluid/text_matching_on_quora/configs/__init__.py
@@ -1,6 +1,6 @@
 
-from cdssm import cdssm_base
-from dec_att import decatt_glove
-from sse import sse_base
-from infer_sent import infer_sent_v1
-from infer_sent import infer_sent_v2
+from .cdssm import cdssm_base
+from .dec_att import decatt_glove
+from .sse import sse_base
+from .infer_sent import infer_sent_v1
+from .infer_sent import infer_sent_v2
diff --git a/fluid/text_matching_on_quora/configs/cdssm.py b/fluid/text_matching_on_quora/configs/cdssm.py
index 275c6f89ae143936a9a44e679337fa9a6e308eab..d6433e4f93118cf50e7c5d84e1c78735911897c8 100755
--- a/fluid/text_matching_on_quora/configs/cdssm.py
+++ b/fluid/text_matching_on_quora/configs/cdssm.py
@@ -1,5 +1,5 @@
 
-import basic_config
+from . import basic_config
 
 def cdssm_base():
     """
diff --git a/fluid/text_matching_on_quora/configs/dec_att.py b/fluid/text_matching_on_quora/configs/dec_att.py
index a8994097c95990fd8c39391709639d088db0a5b5..9b8b192ae026a65a525aff5876b99c2388449da5 100755
--- a/fluid/text_matching_on_quora/configs/dec_att.py
+++ b/fluid/text_matching_on_quora/configs/dec_att.py
@@ -1,5 +1,5 @@
 
-import basic_config
+from . import basic_config
 
 def decatt_glove():
     """
diff --git a/fluid/text_matching_on_quora/configs/infer_sent.py b/fluid/text_matching_on_quora/configs/infer_sent.py
index ac549c01b894934a7d3cb9c3d0ba4f1984512450..0bc91d49e87c64d02ca51e074331d1aa02abb5eb 100755
--- a/fluid/text_matching_on_quora/configs/infer_sent.py
+++ b/fluid/text_matching_on_quora/configs/infer_sent.py
@@ -1,5 +1,5 @@
 
-import basic_config
+from . import basic_config
 
 def infer_sent_v1():
     """
diff --git a/fluid/text_matching_on_quora/configs/sse.py b/fluid/text_matching_on_quora/configs/sse.py
index f30e04953df07606308ac8d1a515e6a467b5e152..ea3c77319b0870130690f4f89bf6173b806ff14d 100755
--- a/fluid/text_matching_on_quora/configs/sse.py
+++ b/fluid/text_matching_on_quora/configs/sse.py
@@ -1,5 +1,5 @@
 
-import basic_config
+from . import basic_config
 
 def sse_base():
     """
diff --git a/fluid/text_matching_on_quora/models/__init__.py b/fluid/text_matching_on_quora/models/__init__.py
index 08b661b3f46fbe34c2b69aef1ced38d4e63a9350..ecee5791ab3bdd277d35321d5d608683c22e5d01 100755
--- a/fluid/text_matching_on_quora/models/__init__.py
+++ b/fluid/text_matching_on_quora/models/__init__.py
@@ -1,4 +1,4 @@
-from cdssm import cdssmNet
-from dec_att import DecAttNet
-from sse import SSENet
-from infer_sent import InferSentNet
+from .cdssm import cdssmNet
+from .dec_att import DecAttNet
+from .sse import SSENet
+from .infer_sent import InferSentNet
diff --git a/fluid/text_matching_on_quora/models/infer_sent.py b/fluid/text_matching_on_quora/models/infer_sent.py
index 1367cb75fd3684f165b7c5ca88b2dc2943906db3..45a4c3d122c12e9442c0adf849abae1d9d476a5c 100644
--- a/fluid/text_matching_on_quora/models/infer_sent.py
+++ b/fluid/text_matching_on_quora/models/infer_sent.py
@@ -1,6 +1,7 @@
+
 import paddle.fluid as fluid
-from my_layers import bi_lstm_layer
-from match_layers import ElementwiseMatching
+from .my_layers import bi_lstm_layer
+from .match_layers import ElementwiseMatching
 
 class InferSentNet():
     """
diff --git a/fluid/text_matching_on_quora/models/match_layers.py b/fluid/text_matching_on_quora/models/match_layers.py
index ee2d469181589a7e7d1f29916fd9b6c0b8362ca7..6c6105a1fa9bee3bf940e0a783c5622220637787 100755
--- a/fluid/text_matching_on_quora/models/match_layers.py
+++ b/fluid/text_matching_on_quora/models/match_layers.py
@@ -3,7 +3,6 @@ This Module provide different kinds of Match layers
 """
 
 import paddle.fluid as fluid
-import paddle.v2 as paddle
 
 
 def MultiPerspectiveMatching(vec1, vec2, perspective_num):
@@ -44,18 +43,3 @@ def ElementwiseMatching(vec1, vec2):
     return fluid.layers.concat(input=[vec1, vec2, elementwise_mul, elementwise_abs_sub], axis=1)
 
 
-def MultiPerspectiveFullMatching(seq1, seq2, perspective_num):
-    """
-    seq1: Lod tensor with shape [-1, feature_dim] (lod level == 1) is a representation of a sentence.
-    seq2: Another Lod tensor with shape [-1, feature_dim] (lod level == 1) is a representation of a sentence.
-    use seq1 to match seq2
-    return match seq with same shape as seq1.
-    """
-    print seq2
-    seq2_last = fluid.layers.sequence_pool(input=seq2, pool_type="last")
-    print seq2_last
-    seq2 = fluid.layers.sequence_expand(seq2_last, seq1)
-    print seq2
-    #seq2 = fluid.layers.lod_reset(x=seq2, y=seq1)
-    seq2.set_lod(seq1)
-    print seq2
diff --git a/fluid/text_matching_on_quora/models/sse.py b/fluid/text_matching_on_quora/models/sse.py
index dea6535e0454d90ba35033e0d2e595593dc8aeae..445032a2efb41213a0fef6b4e375acbc0eccf2ee 100644
--- a/fluid/text_matching_on_quora/models/sse.py
+++ b/fluid/text_matching_on_quora/models/sse.py
@@ -1,6 +1,7 @@
+
 import paddle.fluid as fluid
-from my_layers import bi_lstm_layer
-from match_layers import ElementwiseMatching
+from .my_layers import bi_lstm_layer
+from .match_layers import ElementwiseMatching
 
 class SSENet():
     """
diff --git a/fluid/text_matching_on_quora/pretrained_word2vec.py b/fluid/text_matching_on_quora/pretrained_word2vec.py
index eda9e80a7b58fd03e8a845f691d496997344113c..d49b4740a506a22fbf1cd6b43a002a135ee21ef9 100755
--- a/fluid/text_matching_on_quora/pretrained_word2vec.py
+++ b/fluid/text_matching_on_quora/pretrained_word2vec.py
@@ -2,27 +2,29 @@
 This Module provide pretrained word-embeddings 
 """
 
-from __future__ import print_function 
+from __future__ import print_function, unicode_literals 
 import numpy as np
 import time, datetime
+import os, sys
+
 
 def Glove840B_300D(filepath, keys=None):
     """
     input: the "glove.840B.300d.txt" file path
     return: a dict, key: word (unicode), value: a numpy array with shape [300]
     """
-    if keys is not None: 
+    if keys is not None:
         assert(isinstance(keys, set))
     print("loading word2vec from ", filepath)
     print("please wait for a minute.")
     start = time.time()
     word2vec = {}
-
     with open(filepath, "r") as f:
         for line in f:
-            info = line.strip().split()
-            # TODO: test python3
-            word = info[0].decode('utf-8')
+            if sys.version_info <= (3, 0): # for python2
+                line = line.decode('utf-8')
+            info = line.strip("\n").split(" ")
+            word = info[0]
             if (keys is not None) and (word not in keys):
                 continue
             vector = info[1:]
@@ -32,6 +34,9 @@ def Glove840B_300D(filepath, keys=None):
     end = time.time()
     print("Spent ", str(datetime.timedelta(seconds=end-start)), " on loading word2vec.")
     return word2vec
- 
+
 if __name__ == '__main__':
-    embed_dict = Glove840B_300D("data/glove.840B.300d.txt")
+    from os.path import expanduser
+    home = expanduser("~")
+    embed_dict = Glove840B_300D(os.path.join(home, "./.cache/paddle/dataset/glove.840B.300d.txt"))
+    exit(0)
diff --git a/fluid/text_matching_on_quora/quora_question_pairs.py b/fluid/text_matching_on_quora/quora_question_pairs.py
index 76b24c20bf4158153406a2f2744f3245efe18e92..2d97a89f540bd39b794d698c35e0bbafc4617380 100755
--- a/fluid/text_matching_on_quora/quora_question_pairs.py
+++ b/fluid/text_matching_on_quora/quora_question_pairs.py
@@ -20,7 +20,7 @@ import tarfile
 import re
 import string
 import random
-import os
+import os, sys
 import nltk
 from os.path import expanduser
 
@@ -43,7 +43,8 @@ COLUMN_COUNT = 4
 
 
 def tokenize(s):
-    s = s.decode('utf-8')
+    if sys.version_info <= (3, 0): # for python2
+        s = s.decode('utf-8')
     if TOKENIZE_METHOD == "nltk":
         return nltk.tokenize.word_tokenize(s)
     elif TOKENIZE_METHOD == "punctuation":
@@ -116,7 +117,7 @@ def build_dict(file_name, cutoff):
 
     dictionary = sorted(word_freq, key=lambda x: (-x[1], x[0]))
     words, _ = list(zip(*dictionary))
-    word_idx = dict(zip(words, xrange(len(words))))
+    word_idx = dict(zip(words, range(len(words))))
     word_idx['<unk>'] = len(words)
     word_idx['<pad>'] = len(words) + 1
     return word_idx
diff --git a/fluid/text_matching_on_quora/train_and_evaluate.py b/fluid/text_matching_on_quora/train_and_evaluate.py
index 333fe8698b19e76f6b8fb85082d4d4f72d866227..ad87a8ef4a967c42280c596d4639f5baec9d19ea 100755
--- a/fluid/text_matching_on_quora/train_and_evaluate.py
+++ b/fluid/text_matching_on_quora/train_and_evaluate.py
@@ -9,7 +9,6 @@ import contextlib
 import numpy as np
 
 import paddle.fluid as fluid
-import paddle.v2 as paddle
 
 import utils, metric, configs
 import models
@@ -155,7 +154,7 @@ def train_and_evaluate(train_reader,
 
     # start training
     print("[%s] Start Training" % time.asctime(time.localtime(time.time())))
-    for epoch_id in xrange(global_config.epoch_num):
+    for epoch_id in range(global_config.epoch_num):
         data_size, data_count, total_acc, total_cost = 0, 0, 0.0, 0.0
         batch_id = 0
         for data in train_reader():
diff --git a/fluid/text_matching_on_quora/utils.py b/fluid/text_matching_on_quora/utils.py
index 604a0eea361d826296cf57b5904ed98e0952d8a4..25ffe9024f2f874c19eb65fcd484d6bd2d5e8a63 100755
--- a/fluid/text_matching_on_quora/utils.py
+++ b/fluid/text_matching_on_quora/utils.py
@@ -7,7 +7,7 @@ import time
 import numpy as np
 
 import paddle.fluid as fluid
-import paddle.v2 as paddle
+import paddle
 import quora_question_pairs