remove compability for sys.version < 3.5 (#2037)

test/test_datasets_utils.py

@@ -8,14 +8,10 @@ import tarfile
 import gzip
 import warnings
 from torch._utils_internal import get_file_path_2
+from urllib.error import URLError
 
 from common_utils import get_tmp_dir
 
-if sys.version_info < (3,):
-    from urllib2 import URLError
-else:
-    from urllib.error import URLError
-
 
 TEST_FILE = get_file_path_2(
     os.path.dirname(os.path.abspath(__file__)), 'assets', 'grace_hopper_517x606.jpg')
@@ -62,7 +58,6 @@ class Tester(unittest.TestCase):
                 warnings.warn(msg, RuntimeWarning)
                 raise unittest.SkipTest(msg)
 
-    @unittest.skipIf(sys.version_info < (3,), "Python2 doesn't raise error")
     def test_download_url_dont_exist(self):
         with get_tmp_dir() as temp_dir:
             url = "http://github.com/pytorch/vision/archive/this_doesnt_exist.zip"
@@ -98,7 +93,6 @@ class Tester(unittest.TestCase):
                         self.assertEqual(data, 'this is the content')
 
     @unittest.skipIf('win' in sys.platform, 'temporarily disabled on Windows')
-    @unittest.skipIf(sys.version_info < (3,), "Extracting .tar.xz files is not supported under Python 2.x")
     def test_extract_tar_xz(self):
         for ext, mode in zip(['.tar.xz'], ['w:xz']):
             with get_tmp_dir() as temp_dir:

test/test_io.py

@@ -6,15 +6,11 @@ import torchvision.datasets.utils as utils
 import torchvision.io as io
 from torchvision import get_video_backend
 import unittest
-import sys
 import warnings
+from urllib.error import URLError
 
 from common_utils import get_tmp_dir
 
-if sys.version_info < (3,):
-    from urllib2 import URLError
-else:
-    from urllib.error import URLError
 
 try:
     import av

torchvision/datasets/folder.py

@@ -4,7 +4,6 @@ from PIL import Image
 
 import os
 import os.path
-import sys
 
 
 def has_file_allowed_extension(filename, extensions):
@@ -119,11 +118,7 @@ class DatasetFolder(VisionDataset):
         Ensures:
             No class is a subdirectory of another.
         """
-        if sys.version_info >= (3, 5):
-            # Faster and available in Python 3.5 and above
-            classes = [d.name for d in os.scandir(dir) if d.is_dir()]
-        else:
-            classes = [d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d))]
+        classes = [d.name for d in os.scandir(dir) if d.is_dir()]
         classes.sort()
         class_to_idx = {classes[i]: i for i in range(len(classes))}
         return classes, class_to_idx

torchvision/datasets/lsun.py

@@ -4,13 +4,7 @@ import os
 import os.path
 import io
 import string
-import sys
-
-if sys.version_info < (3, 3):
-    from collections import Iterable
-else:
-    from collections.abc import Iterable
-
+from collections.abc import Iterable
 import pickle
 from .utils import verify_str_arg, iterable_to_str
 

torchvision/transforms/functional.py

 import torch
-import sys
 import math
 from PIL import Image, ImageOps, ImageEnhance, __version__ as PILLOW_VERSION
 try:
@@ -9,16 +8,9 @@ except ImportError:
 import numpy as np
 from numpy import sin, cos, tan
 import numbers
-import collections
+from collections.abc import Sequence, Iterable
 import warnings
 
-if sys.version_info < (3, 3):
-    Sequence = collections.Sequence
-    Iterable = collections.Iterable
-else:
-    Sequence = collections.abc.Sequence
-    Iterable = collections.abc.Iterable
-
 
 def _is_pil_image(img):
     if accimage is not None:

torchvision/transforms/transforms.py

 import torch
 import math
-import sys
 import random
 from PIL import Image
 try:
@@ -10,18 +9,11 @@ except ImportError:
 import numpy as np
 import numbers
 import types
-import collections
+from collections.abc import Sequence, Iterable
 import warnings
 
 from . import functional as F
 
-if sys.version_info < (3, 3):
-    Sequence = collections.Sequence
-    Iterable = collections.Iterable
-else:
-    Sequence = collections.abc.Sequence
-    Iterable = collections.abc.Iterable
-
 
 __all__ = ["Compose", "ToTensor", "ToPILImage", "Normalize", "Resize", "Scale", "CenterCrop", "Pad",
            "Lambda", "RandomApply", "RandomChoice", "RandomOrder", "RandomCrop", "RandomHorizontalFlip",