diff --git a/paddle/fluid/inference/tests/api/full_ILSVRC2012_val_preprocess.py b/paddle/fluid/inference/tests/api/full_ILSVRC2012_val_preprocess.py
index 9f3a389ea344e7e827c5864dff70a1b0eec10f08..f25ce8be9eeb7db3f2ac897235e9fd280936d9d4 100644
--- a/paddle/fluid/inference/tests/api/full_ILSVRC2012_val_preprocess.py
+++ b/paddle/fluid/inference/tests/api/full_ILSVRC2012_val_preprocess.py
@@ -13,6 +13,7 @@
 import hashlib
 import unittest
 import os
+import io
 import numpy as np
 import time
 import sys
@@ -23,10 +24,9 @@ from PIL import Image
 import math
 from paddle.dataset.common import download
 import tarfile
-from six.moves import StringIO
 import argparse
+import shutil
 
-random.seed(0)
 np.random.seed(0)
 
 DATA_DIM = 224
@@ -34,7 +34,7 @@ SIZE_FLOAT32 = 4
 SIZE_INT64 = 8
 FULL_SIZE_BYTES = 30106000008
 FULL_IMAGES = 50000
-TARGET_HASH = '22d2e0008dca693916d9595a5ea3ded8'
+TARGET_HASH = '0be07c2c23296b97dad83c626682c66a'
 FOLDER_NAME = "ILSVRC2012/"
 VALLIST_TAR_NAME = "ILSVRC2012/val_list.txt"
 CHUNK_SIZE = 8192
@@ -55,8 +55,8 @@ def crop_image(img, target_size, center):
     width, height = img.size
     size = target_size
     if center == True:
-        w_start = (width - size) / 2
-        h_start = (height - size) / 2
+        w_start = (width - size) // 2
+        h_start = (height - size) // 2
     else:
         w_start = np.random.randint(0, width - size + 1)
         h_start = np.random.randint(0, height - size + 1)
@@ -95,11 +95,9 @@ def download_concat(cache_folder, zip_path):
         file_name = os.path.join(cache_folder, data_urls[i].split('/')[-1])
         file_names.append(file_name)
         print("Downloaded part {0}\n".format(file_name))
-    if not os.path.exists(zip_path):
-        with open(zip_path, "w+") as outfile:
-            for fname in file_names:
-                with open(fname) as infile:
-                    outfile.write(infile.read())
+    with open(zip_path, "wb") as outfile:
+        for fname in file_names:
+            shutil.copyfileobj(open(fname, 'rb'), outfile)
 
 
 def print_processbar(done_percentage):
@@ -114,12 +112,12 @@ def check_integrity(filename, target_hash):
     print('\nThe binary file exists. Checking file integrity...\n')
     md = hashlib.md5()
     count = 0
-    onepart = FULL_SIZE_BYTES / CHUNK_SIZE / 100
-    with open(filename) as ifs:
+    onepart = FULL_SIZE_BYTES // CHUNK_SIZE // 100
+    with open(filename, 'rb') as ifs:
         while True:
             buf = ifs.read(CHUNK_SIZE)
             if count % onepart == 0:
-                done = count / onepart
+                done = count // onepart
                 print_processbar(done)
             count = count + 1
             if not buf:
@@ -142,28 +140,26 @@ def convert_Imagenet_tar2bin(tar_file, output_file):
     for tarInfo in tar:
         if tarInfo.isfile() and tarInfo.name != VALLIST_TAR_NAME:
             dataset[tarInfo.name] = tar.extractfile(tarInfo).read()
-
     with open(output_file, "w+b") as ofs:
         ofs.seek(0)
         num = np.array(int(FULL_IMAGES)).astype('int64')
         ofs.write(num.tobytes())
 
-        per_percentage = FULL_IMAGES / 100
+        per_percentage = FULL_IMAGES // 100
 
+        val_info = tar.getmember(VALLIST_TAR_NAME)
+        val_list = tar.extractfile(val_info).read().decode("utf-8")
+        lines = val_list.splitlines()
         idx = 0
         for imagedata in dataset.values():
-            img = Image.open(StringIO(imagedata))
+            img = Image.open(io.BytesIO(imagedata))
             img = process_image(img)
             np_img = np.array(img)
             ofs.write(np_img.astype('float32').tobytes())
             if idx % per_percentage == 0:
-                print_processbar(idx / per_percentage)
+                print_processbar(idx // per_percentage)
             idx = idx + 1
 
-        val_info = tar.getmember(VALLIST_TAR_NAME)
-        val_list = tar.extractfile(val_info).read()
-
-        lines = val_list.split('\n')
         val_dict = {}
         for line_idx, line in enumerate(lines):
             if line_idx == FULL_IMAGES: