[WIP] Add test for ImageNet (#976)

* added fake data

* fixed fake data

* renamed extract and download methods and added functionality

* added raw fake data

* refactored imagenet and added test

* flake8

* added fake devkit and mocked download_url

* reversed uncommenting

* added mock to CI

* fixed tests for imagefolder

* flake8

torchvision/datasets/mnist.py

@@ -7,7 +7,7 @@ import os.path
 import numpy as np
 import torch
 import codecs
-from .utils import download_and_extract, extract_file, makedir_exist_ok
+from .utils import download_and_extract_archive, extract_archive, makedir_exist_ok
 
 
 class MNIST(VisionDataset):
@@ -131,7 +131,7 @@ class MNIST(VisionDataset):
         # download files
         for url in self.urls:
             filename = url.rpartition('/')[2]
-            download_and_extract(url, root=self.raw_folder, filename=filename)
+            download_and_extract_archive(url, download_root=self.raw_folder, filename=filename)
 
         # process and save as torch files
         print('Processing...')
@@ -259,11 +259,12 @@ class EMNIST(MNIST):
 
         # download files
         print('Downloading and extracting zip archive')
-        download_and_extract(self.url, root=self.raw_folder, filename="emnist.zip", remove_finished=True)
+        download_and_extract_archive(self.url, download_root=self.raw_folder, filename="emnist.zip",
+                                     remove_finished=True)
         gzip_folder = os.path.join(self.raw_folder, 'gzip')
         for gzip_file in os.listdir(gzip_folder):
             if gzip_file.endswith('.gz'):
-                extract_file(os.path.join(gzip_folder, gzip_file), gzip_folder)
+                extract_archive(os.path.join(gzip_folder, gzip_file), gzip_folder)
 
         # process and save as torch files
         for split in self.splits:

torchvision/datasets/omniglot.py

@@ -3,7 +3,7 @@ from PIL import Image
 from os.path import join
 import os
 from .vision import VisionDataset
-from .utils import download_and_extract, check_integrity, list_dir, list_files
+from .utils import download_and_extract_archive, check_integrity, list_dir, list_files
 
 
 class Omniglot(VisionDataset):
@@ -88,7 +88,7 @@ class Omniglot(VisionDataset):
         filename = self._get_target_folder()
         zip_filename = filename + '.zip'
         url = self.download_url_prefix + '/' + zip_filename
-        download_and_extract(url, self.root, zip_filename, self.zips_md5[filename])
+        download_and_extract_archive(url, self.root, zip_filename, self.zips_md5[filename])
 
     def _get_target_folder(self):
         return 'images_background' if self.background else 'images_evaluation'

torchvision/datasets/stl10.py

@@ -5,7 +5,7 @@ import os.path
 import numpy as np
 
 from .vision import VisionDataset
-from .utils import check_integrity, download_and_extract
+from .utils import check_integrity, download_and_extract_archive
 
 
 class STL10(VisionDataset):
@@ -152,7 +152,7 @@ class STL10(VisionDataset):
         if self._check_integrity():
             print('Files already downloaded and verified')
             return
-        download_and_extract(self.url, self.root, self.filename, self.tgz_md5)
+        download_and_extract_archive(self.url, self.root, self.filename, self.tgz_md5)
 
     def extra_repr(self):
         return "Split: {split}".format(**self.__dict__)

torchvision/datasets/utils.py

@@ -38,7 +38,6 @@ def check_integrity(fpath, md5=None):
         return False
     if md5 is None:
         return True
-    else:
     return check_md5(fpath, md5)
 
 
@@ -74,7 +73,7 @@ def download_url(url, root, filename=None, md5=None):
     makedir_exist_ok(root)
 
     # downloads file
-    if os.path.isfile(fpath) and check_integrity(fpath, md5):
+    if check_integrity(fpath, md5):
         print('Using downloaded and verified file: ' + fpath)
     else:
         try:
@@ -211,9 +210,12 @@ def _is_zip(filename):
     return filename.endswith(".zip")
 
 
-def extract_file(from_path, to_path, remove_finished=False):
+def extract_archive(from_path, to_path=None, remove_finished=False):
+    if to_path is None:
+        to_path = os.path.dirname(from_path)
+
     if _is_tar(from_path):
-        with tarfile.open(from_path, 'r:') as tar:
+        with tarfile.open(from_path, 'r') as tar:
             tar.extractall(path=to_path)
     elif _is_targz(from_path):
         with tarfile.open(from_path, 'r:gz') as tar:
@@ -229,10 +231,19 @@ def extract_file(from_path, to_path, remove_finished=False):
         raise ValueError("Extraction of {} not supported".format(from_path))
 
     if remove_finished:
-        os.unlink(from_path)
+        os.remove(from_path)
+
+
+def download_and_extract_archive(url, download_root, extract_root=None, filename=None,
+                                 md5=None, remove_finished=False):
+    download_root = os.path.expanduser(download_root)
+    if extract_root is None:
+        extract_root = download_root
+    if not filename:
+        filename = os.path.basename(url)
 
+    download_url(url, download_root, filename, md5)
 
-def download_and_extract(url, root, filename, md5=None, remove_finished=False):
-    download_url(url, root, filename, md5)
-    print("Extracting {} to {}".format(os.path.join(root, filename), root))
-    extract_file(os.path.join(root, filename), root, remove_finished)
+    archive = os.path.join(download_root, filename)
+    print("Extracting {} to {}".format(archive, extract_root))
+    extract_archive(archive, extract_root, remove_finished)