diff --git a/nnvm/tests/python/frontend/coreml/model_zoo/__init__.py b/nnvm/tests/python/frontend/coreml/model_zoo/__init__.py
index 99b23819ced4..d43768f1e376 100644
--- a/nnvm/tests/python/frontend/coreml/model_zoo/__init__.py
+++ b/nnvm/tests/python/frontend/coreml/model_zoo/__init__.py
@@ -1,33 +1,24 @@
-from six.moves import urllib
 import os
 from PIL import Image
 import numpy as np
-
-def download(url, path, overwrite=False):
-    if os.path.exists(path) and not overwrite:
-        return
-    print('Downloading {} to {}.'.format(url, path))
-    urllib.request.urlretrieve(url, path)
+from tvm.contrib.download import download_testdata
 
 def get_mobilenet():
     url = 'https://docs-assets.developer.apple.com/coreml/models/MobileNet.mlmodel'
     dst = 'mobilenet.mlmodel'
-    real_dst = os.path.abspath(os.path.join(os.path.dirname(__file__), dst))
-    download(url, real_dst)
-    return os.path.abspath(real_dst)
+    real_dst = download_testdata(url, dst, module='coreml')
+    return real_dst
 
 def get_resnet50():
     url = 'https://docs-assets.developer.apple.com/coreml/models/Resnet50.mlmodel'
     dst = 'resnet50.mlmodel'
-    real_dst = os.path.abspath(os.path.join(os.path.dirname(__file__), dst))
-    download(url, real_dst)
-    return os.path.abspath(real_dst)
+    real_dst = download_testdata(url, dst, module='coreml')
+    return real_dst
 
 def get_cat_image():
     url = 'https://gist.githubusercontent.com/zhreshold/bcda4716699ac97ea44f791c24310193/raw/fa7ef0e9c9a5daea686d6473a62aacd1a5885849/cat.png'
     dst = 'cat.png'
-    real_dst = os.path.abspath(os.path.join(os.path.dirname(__file__), dst))
-    download(url, real_dst)
+    real_dst = download_testdata(url, dst, module='coreml')
     img = Image.open(real_dst).resize((224, 224))
     img = np.transpose(img, (2, 0, 1))[np.newaxis, :]
     return np.asarray(img)
diff --git a/nnvm/tests/python/frontend/darknet/test_forward.py b/nnvm/tests/python/frontend/darknet/test_forward.py
index 1f5e89c6e4d5..7cd47d382d22 100644
--- a/nnvm/tests/python/frontend/darknet/test_forward.py
+++ b/nnvm/tests/python/frontend/darknet/test_forward.py
@@ -12,44 +12,16 @@
 import numpy as np
 import tvm
 from tvm.contrib import graph_runtime
+from tvm.contrib.download import download_testdata
 from nnvm import frontend
 from nnvm.testing.darknet import LAYERTYPE
 from nnvm.testing.darknet import __darknetffi__
 import nnvm.compiler
-if sys.version_info >= (3,):
-    import urllib.request as urllib2
-else:
-    import urllib2
-
-
-def _download(url, path, overwrite=False, sizecompare=False):
-    ''' Download from internet'''
-    if os.path.isfile(path) and not overwrite:
-        if sizecompare:
-            file_size = os.path.getsize(path)
-            res_head = requests.head(url)
-            res_get = requests.get(url, stream=True)
-            if 'Content-Length' not in res_head.headers:
-                res_get = urllib2.urlopen(url)
-            urlfile_size = int(res_get.headers['Content-Length'])
-            if urlfile_size != file_size:
-                print("exist file got corrupted, downloading", path, " file freshly")
-                _download(url, path, True, False)
-                return
-        print('File {} exists, skip.'.format(path))
-        return
-    print('Downloading from url {} to {}'.format(url, path))
-    try:
-        urllib.request.urlretrieve(url, path)
-        print('')
-    except:
-        urllib.urlretrieve(url, path)
 
 DARKNET_LIB = 'libdarknet2.0.so'
 DARKNETLIB_URL = 'https://github.com/siju-samuel/darknet/blob/master/lib/' \
                                     + DARKNET_LIB + '?raw=true'
-_download(DARKNETLIB_URL, DARKNET_LIB)
-LIB = __darknetffi__.dlopen('./' + DARKNET_LIB)
+LIB = __darknetffi__.dlopen(download_testdata(DARKNETLIB_URL, DARKNET_LIB, module='darknet'))
 
 def _read_memory_buffer(shape, data, dtype='float32'):
     length = 1
@@ -82,6 +54,12 @@ def _get_tvm_output(net, data, build_dtype='float32'):
         tvm_out.append(m.get_output(i).asnumpy())
     return tvm_out
 
+def _load_net(cfg_url, cfg_name, weights_url, weights_name):
+    cfg_path = download_testdata(cfg_url, cfg_name, module='darknet')
+    weights_path = download_testdata(weights_url, weights_name, module='darknet')
+    net = LIB.load_network(cfg_path.encode('utf-8'), weights_path.encode('utf-8'), 0)
+    return net
+
 def test_forward(net, build_dtype='float32'):
     '''Test network with given input image on both darknet and tvm'''
     def get_darknet_output(net, img):
@@ -125,8 +103,8 @@ def get_darknet_output(net, img):
 
     test_image = 'dog.jpg'
     img_url = 'https://github.com/siju-samuel/darknet/blob/master/data/' + test_image   +'?raw=true'
-    _download(img_url, test_image)
-    img = LIB.letterbox_image(LIB.load_image_color(test_image.encode('utf-8'), 0, 0), net.w, net.h)
+    img_path = download_testdata(img_url, test_image, module='darknet')
+    img = LIB.letterbox_image(LIB.load_image_color(img_path.encode('utf-8'), 0, 0), net.w, net.h)
     darknet_output = get_darknet_output(net, img)
     batch_size = 1
     data = np.empty([batch_size, img.c, img.h, img.w], dtype)
@@ -167,9 +145,7 @@ def test_forward_extraction():
     weights_name = model_name + '.weights'
     cfg_url = 'https://github.com/pjreddie/darknet/blob/master/cfg/' + cfg_name + '?raw=true'
     weights_url = 'http://pjreddie.com/media/files/' + weights_name + '?raw=true'
-    _download(cfg_url, cfg_name)
-    _download(weights_url, weights_name)
-    net = LIB.load_network(cfg_name.encode('utf-8'), weights_name.encode('utf-8'), 0)
+    net = _load_net(cfg_url, cfg_name, weights_url, weights_name)
     test_forward(net)
     LIB.free_network(net)
 
@@ -180,9 +156,7 @@ def test_forward_alexnet():
     weights_name = model_name + '.weights'
     cfg_url = 'https://github.com/pjreddie/darknet/blob/master/cfg/' + cfg_name + '?raw=true'
     weights_url = 'http://pjreddie.com/media/files/' + weights_name + '?raw=true'
-    _download(cfg_url, cfg_name)
-    _download(weights_url, weights_name)
-    net = LIB.load_network(cfg_name.encode('utf-8'), weights_name.encode('utf-8'), 0)
+    net = _load_net(cfg_url, cfg_name, weights_url, weights_name)
     test_forward(net)
     LIB.free_network(net)
 
@@ -193,9 +167,7 @@ def test_forward_resnet50():
     weights_name = model_name + '.weights'
     cfg_url = 'https://github.com/pjreddie/darknet/blob/master/cfg/' + cfg_name + '?raw=true'
     weights_url = 'http://pjreddie.com/media/files/' + weights_name + '?raw=true'
-    _download(cfg_url, cfg_name)
-    _download(weights_url, weights_name)
-    net = LIB.load_network(cfg_name.encode('utf-8'), weights_name.encode('utf-8'), 0)
+    net = _load_net(cfg_url, cfg_name, weights_url, weights_name)
     test_forward(net)
     LIB.free_network(net)
 
@@ -206,9 +178,7 @@ def test_forward_yolov2():
     weights_name = model_name + '.weights'
     cfg_url = 'https://github.com/pjreddie/darknet/blob/master/cfg/' + cfg_name + '?raw=true'
     weights_url = 'http://pjreddie.com/media/files/' + weights_name + '?raw=true'
-    _download(cfg_url, cfg_name)
-    _download(weights_url, weights_name)
-    net = LIB.load_network(cfg_name.encode('utf-8'), weights_name.encode('utf-8'), 0)
+    net = _load_net(cfg_url, cfg_name, weights_url, weights_name)
     build_dtype = {}
     test_forward(net, build_dtype)
     LIB.free_network(net)
@@ -220,9 +190,7 @@ def test_forward_yolov3():
     weights_name = model_name + '.weights'
     cfg_url = 'https://github.com/pjreddie/darknet/blob/master/cfg/' + cfg_name + '?raw=true'
     weights_url = 'http://pjreddie.com/media/files/' + weights_name + '?raw=true'
-    _download(cfg_url, cfg_name)
-    _download(weights_url, weights_name)
-    net = LIB.load_network(cfg_name.encode('utf-8'), weights_name.encode('utf-8'), 0)
+    net = _load_net(cfg_url, cfg_name, weights_url, weights_name)
     build_dtype = {}
     test_forward(net, build_dtype)
     LIB.free_network(net)
diff --git a/nnvm/tests/python/frontend/onnx/model_zoo/__init__.py b/nnvm/tests/python/frontend/onnx/model_zoo/__init__.py
index ee5093e07a97..ffd39f5b9976 100644
--- a/nnvm/tests/python/frontend/onnx/model_zoo/__init__.py
+++ b/nnvm/tests/python/frontend/onnx/model_zoo/__init__.py
@@ -3,22 +3,7 @@
 import os
 import logging
 from .super_resolution import get_super_resolution
-
-def _download(url, filename, overwrite=False):
-    if os.path.isfile(filename) and not overwrite:
-        logging.debug('File %s existed, skip.', filename)
-        return
-    logging.debug('Downloading from url %s to %s', url, filename)
-    try:
-        import urllib.request
-        urllib.request.urlretrieve(url, filename)
-    except:
-        import urllib
-        urllib.urlretrieve(url, filename)
-
-def _as_abs_path(fname):
-    cur_dir = os.path.abspath(os.path.dirname(__file__))
-    return os.path.join(cur_dir, fname)
+from tvm.contrib.download import download_testdata
 
 
 URLS = {
@@ -30,9 +15,9 @@ def _as_abs_path(fname):
 # download and add paths
 for k, v  in URLS.items():
     name = k.split('.')[0]
-    path = _as_abs_path(k)
-    _download(v, path, False)
-    locals()[name] = path
+    relpath = os.path.join('onnx', k)
+    abspath = download_testdata(v, relpath, module='onnx')
+    locals()[name] = abspath
 
 # symbol for graph comparison
 super_resolution_sym = get_super_resolution()
diff --git a/python/tvm/contrib/download.py b/python/tvm/contrib/download.py
index 0dcbb56ad663..26f285a0b29a 100644
--- a/python/tvm/contrib/download.py
+++ b/python/tvm/contrib/download.py
@@ -5,8 +5,10 @@
 import os
 import sys
 import time
+import uuid
+import shutil
 
-def download(url, path, overwrite=False, size_compare=False, verbose=1):
+def download(url, path, overwrite=False, size_compare=False, verbose=1, retries=3):
     """Downloads the file from the internet.
     Set the input options correctly to overwrite or do the size comparison
 
@@ -53,6 +55,11 @@ def download(url, path, overwrite=False, size_compare=False, verbose=1):
 
     # Stateful start time
     start_time = time.time()
+    dirpath = os.path.dirname(path)
+    if not os.path.isdir(dirpath):
+        os.makedirs(dirpath)
+    random_uuid = str(uuid.uuid4())
+    tempfile = os.path.join(dirpath, random_uuid)
 
     def _download_progress(count, block_size, total_size):
         #pylint: disable=unused-argument
@@ -68,11 +75,62 @@ def _download_progress(count, block_size, total_size):
                          (percent, progress_size / (1024.0 * 1024), speed, duration))
         sys.stdout.flush()
 
-    if sys.version_info >= (3,):
-        urllib2.urlretrieve(url, path, reporthook=_download_progress)
-        print("")
+    while retries >= 0:
+        # Disable pyling too broad Exception
+        # pylint: disable=W0703
+        try:
+            if sys.version_info >= (3,):
+                urllib2.urlretrieve(url, tempfile, reporthook=_download_progress)
+                print("")
+            else:
+                f = urllib2.urlopen(url)
+                data = f.read()
+                with open(tempfile, "wb") as code:
+                    code.write(data)
+            shutil.move(tempfile, path)
+            break
+        except Exception as err:
+            retries -= 1
+            if retries == 0:
+                os.remove(tempfile)
+                raise err
+            else:
+                print("download failed due to {}, retrying, {} attempt{} left"
+                      .format(repr(err), retries, 's' if retries > 1 else ''))
+
+
+TEST_DATA_ROOT_PATH = os.path.join(os.path.expanduser('~'), '.tvm_test_data')
+if not os.path.exists(TEST_DATA_ROOT_PATH):
+    os.mkdir(TEST_DATA_ROOT_PATH)
+
+def download_testdata(url, relpath, module=None):
+    """Downloads the test data from the internet.
+
+    Parameters
+    ----------
+    url : str
+        Download url.
+
+    relpath : str
+        Relative file path.
+
+    module : Union[str, list, tuple], optional
+        Subdirectory paths under test data folder.
+
+    Returns
+    -------
+    abspath : str
+        Absolute file path of downloaded file
+    """
+    global TEST_DATA_ROOT_PATH
+    if module is None:
+        module_path = ''
+    elif isinstance(module, str):
+        module_path = module
+    elif isinstance(module, (list, tuple)):
+        module_path = os.path.join(*module)
     else:
-        f = urllib2.urlopen(url)
-        data = f.read()
-        with open(path, "wb") as code:
-            code.write(data)
+        raise ValueError("Unsupported module: " + module)
+    abspath = os.path.join(TEST_DATA_ROOT_PATH, module_path, relpath)
+    download(url, abspath, overwrite=False, size_compare=True)
+    return abspath
diff --git a/python/tvm/relay/testing/tf.py b/python/tvm/relay/testing/tf.py
index effe19808a59..0f22939768c5 100644
--- a/python/tvm/relay/testing/tf.py
+++ b/python/tvm/relay/testing/tf.py
@@ -13,7 +13,7 @@
 import tensorflow as tf
 from tensorflow.core.framework import graph_pb2
 
-from tvm.contrib import util
+from tvm.contrib.download import download_testdata
 
 ######################################################################
 # Some helper functions
@@ -136,7 +136,7 @@ def id_to_string(self, node_id):
             return ''
         return self.node_lookup[node_id]
 
-def get_workload_official(model_url, model_sub_path, temp_dir):
+def get_workload_official(model_url, model_sub_path):
     """ Import workload from tensorflow official
 
     Parameters
@@ -158,21 +158,17 @@ def get_workload_official(model_url, model_sub_path, temp_dir):
     """
 
     model_tar_name = os.path.basename(model_url)
-
-    from mxnet.gluon.utils import download
-    temp_path = temp_dir.relpath("./")
-    path_model = temp_path + model_tar_name
-
-    download(model_url, path_model)
+    model_path = download_testdata(model_url, model_tar_name, module=['tf', 'official'])
+    dir_path = os.path.dirname(model_path)
 
     import tarfile
-    if path_model.endswith("tgz") or path_model.endswith("gz"):
-        tar = tarfile.open(path_model)
-        tar.extractall(path=temp_path)
+    if model_path.endswith("tgz") or model_path.endswith("gz"):
+        tar = tarfile.open(model_path)
+        tar.extractall(path=dir_path)
         tar.close()
     else:
-        raise RuntimeError('Could not decompress the file: ' + path_model)
-    return temp_path + model_sub_path
+        raise RuntimeError('Could not decompress the file: ' + model_path)
+    return os.path.join(dir_path, model_sub_path)
 
 def get_workload(model_path, model_sub_path=None):
     """ Import workload from frozen protobuf
@@ -192,24 +188,18 @@ def get_workload(model_path, model_sub_path=None):
 
     """
 
-    temp = util.tempdir()
     if model_sub_path:
-        path_model = get_workload_official(model_path, model_sub_path, temp)
+        path_model = get_workload_official(model_path, model_sub_path)
     else:
         repo_base = 'https://github.com/dmlc/web-data/raw/master/tensorflow/models/'
-        model_name = os.path.basename(model_path)
         model_url = os.path.join(repo_base, model_path)
-
-        from mxnet.gluon.utils import download
-        path_model = temp.relpath(model_name)
-        download(model_url, path_model)
+        path_model = download_testdata(model_url, model_path, module='tf')
 
     # Creates graph from saved graph_def.pb.
     with tf.gfile.FastGFile(path_model, 'rb') as f:
         graph_def = tf.GraphDef()
         graph_def.ParseFromString(f.read())
         graph = tf.import_graph_def(graph_def, name='')
-        temp.remove()
         return graph_def
 
 #######################################################################
@@ -292,7 +282,7 @@ def _get_feed_dict(input_name, input_data):
 
 def _create_ptb_vocabulary(data_dir):
     """Read the PTB sample data input to create vocabulary"""
-    data_path = data_dir+'simple-examples/data/'
+    data_path = os.path.join(data_dir, 'simple-examples/data/')
     file_name = 'ptb.train.txt'
     def _read_words(filename):
         """Read the data for creating vocabulary"""
@@ -341,13 +331,10 @@ def get_workload_ptb():
     ptb_model_file = 'RNN/ptb/ptb_model_with_lstmblockcell.pb'
 
     import tarfile
-    from tvm.contrib.download import download
-    DATA_DIR = './ptb_data/'
-    if not os.path.exists(DATA_DIR):
-        os.mkdir(DATA_DIR)
-    download(sample_url, DATA_DIR+sample_data_file)
-    t = tarfile.open(DATA_DIR+sample_data_file, 'r')
-    t.extractall(DATA_DIR)
-
-    word_to_id, id_to_word = _create_ptb_vocabulary(DATA_DIR)
+    file_path = download_testdata(sample_url, sample_data_file, module=['tf', 'ptb_data'])
+    dir_path = os.path.dirname(file_path)
+    t = tarfile.open(file_path, 'r')
+    t.extractall(dir_path)
+
+    word_to_id, id_to_word = _create_ptb_vocabulary(dir_path)
     return word_to_id, id_to_word, get_workload(ptb_model_file)
diff --git a/tests/python/frontend/coreml/model_zoo/__init__.py b/tests/python/frontend/coreml/model_zoo/__init__.py
index 9e075bba073f..ca10a96ff649 100644
--- a/tests/python/frontend/coreml/model_zoo/__init__.py
+++ b/tests/python/frontend/coreml/model_zoo/__init__.py
@@ -1,33 +1,24 @@
-from six.moves import urllib
 import os
 from PIL import Image
 import numpy as np
-
-def download(url, path, overwrite=False):
-    if os.path.exists(path) and not overwrite:
-        return
-    print('Downloading {} to {}.'.format(url, path))
-    urllib.request.urlretrieve(url, path)
+from tvm.contrib.download import download_testdata
 
 def get_mobilenet():
     url = 'https://docs-assets.developer.apple.com/coreml/models/MobileNet.mlmodel'
     dst = 'mobilenet.mlmodel'
-    real_dst = os.path.abspath(os.path.join(os.path.dirname(__file__), dst))
-    download(url, real_dst)
+    real_dst = download_testdata(url, dst, module='coreml')
     return os.path.abspath(real_dst)
 
 def get_resnet50():
     url = 'https://docs-assets.developer.apple.com/coreml/models/Resnet50.mlmodel'
     dst = 'resnet50.mlmodel'
-    real_dst = os.path.abspath(os.path.join(os.path.dirname(__file__), dst))
-    download(url, real_dst)
+    real_dst = download_testdata(url, dst, module='coreml')
     return os.path.abspath(real_dst)
 
 def get_cat_image():
     url = 'https://gist.githubusercontent.com/zhreshold/bcda4716699ac97ea44f791c24310193/raw/fa7ef0e9c9a5daea686d6473a62aacd1a5885849/cat.png'
     dst = 'cat.png'
-    real_dst = os.path.abspath(os.path.join(os.path.dirname(__file__), dst))
-    download(url, real_dst)
+    real_dst = download_testdata(url, dst, module='coreml')
     img = Image.open(real_dst).resize((224, 224))
     img = np.transpose(img, (2, 0, 1))[np.newaxis, :]
     return np.asarray(img)
\ No newline at end of file
diff --git a/tests/python/frontend/tflite/test_forward.py b/tests/python/frontend/tflite/test_forward.py
index 3ccc895dc60e..3c41792ae903 100644
--- a/tests/python/frontend/tflite/test_forward.py
+++ b/tests/python/frontend/tflite/test_forward.py
@@ -391,10 +391,9 @@ def test_forward_softmax():
 def test_forward_mobilenet():
     '''test mobilenet v1 tflite model'''
     # MobilenetV1
-    temp = util.tempdir()
     tflite_model_file = tf_testing.get_workload_official(
         "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz",
-        "mobilenet_v1_1.0_224.tflite", temp)
+        "mobilenet_v1_1.0_224.tflite")
     with open(tflite_model_file, "rb") as f:
         tflite_model_buf = f.read()
     data = np.random.uniform(size=(1, 224, 224, 3)).astype('float32')
@@ -403,7 +402,6 @@ def test_forward_mobilenet():
     tvm_output = run_tvm_graph(tflite_model_buf, tvm_data, 'input')
     tvm.testing.assert_allclose(np.squeeze(tvm_output[0]), np.squeeze(tflite_output[0]),
                                 rtol=1e-5, atol=1e-5)
-    temp.remove()
 
 #######################################################################
 # Inception V3
@@ -412,10 +410,9 @@ def test_forward_mobilenet():
 def test_forward_inception_v3_net():
     '''test inception v3 tflite model'''
     # InceptionV3
-    temp = util.tempdir()
     tflite_model_file = tf_testing.get_workload_official(
         "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_v3_2018_04_27.tgz",
-        "inception_v3.tflite", temp)
+        "inception_v3.tflite")
     with open(tflite_model_file, "rb") as f:
         tflite_model_buf = f.read()
     data = np.random.uniform(size=(1, 299, 299, 3)).astype('float32')
@@ -424,7 +421,6 @@ def test_forward_inception_v3_net():
     tvm_output = run_tvm_graph(tflite_model_buf, tvm_data, 'input')
     tvm.testing.assert_allclose(np.squeeze(tvm_output[0]), np.squeeze(tflite_output[0]),
                                 rtol=1e-5, atol=1e-5)
-    temp.remove()
 
 #######################################################################
 # Main