[WIP] Add tests for datasets (#966)

* WIP

* WIP: minor improvements

* Add tests

* Fix typo

* Use download_and_extract on caltech, cifar and omniglot

* Add a print message during extraction

* Remove EMNIST from test

test/test_datasets.py

+import PIL
+import shutil
+import tempfile
+import unittest
+
+import torchvision
+
+
+class Tester(unittest.TestCase):
+
+    def test_mnist(self):
+        tmp_dir = tempfile.mkdtemp()
+        dataset = torchvision.datasets.MNIST(tmp_dir, download=True)
+        self.assertEqual(len(dataset), 60000)
+        img, target = dataset[0]
+        self.assertTrue(isinstance(img, PIL.Image.Image))
+        self.assertTrue(isinstance(target, int))
+        shutil.rmtree(tmp_dir)
+
+    def test_kmnist(self):
+        tmp_dir = tempfile.mkdtemp()
+        dataset = torchvision.datasets.KMNIST(tmp_dir, download=True)
+        img, target = dataset[0]
+        self.assertTrue(isinstance(img, PIL.Image.Image))
+        self.assertTrue(isinstance(target, int))
+        shutil.rmtree(tmp_dir)
+
+    def test_fashionmnist(self):
+        tmp_dir = tempfile.mkdtemp()
+        dataset = torchvision.datasets.FashionMNIST(tmp_dir, download=True)
+        img, target = dataset[0]
+        self.assertTrue(isinstance(img, PIL.Image.Image))
+        self.assertTrue(isinstance(target, int))
+        shutil.rmtree(tmp_dir)
+
+
+if __name__ == '__main__':
+    unittest.main()

test/test_datasets_utils.py

@@ -3,6 +3,9 @@ import shutil
 import tempfile
 import torchvision.datasets.utils as utils
 import unittest
+import zipfile
+import tarfile
+import gzip
 
 TEST_FILE = os.path.join(os.path.dirname(os.path.abspath(__file__)),
                          'assets', 'grace_hopper_517x606.jpg')
@@ -41,6 +44,47 @@ class Tester(unittest.TestCase):
         assert not len(os.listdir(temp_dir)) == 0, 'The downloaded root directory is empty after download.'
         shutil.rmtree(temp_dir)
 
+    def test_extract_zip(self):
+        temp_dir = tempfile.mkdtemp()
+        with tempfile.NamedTemporaryFile(suffix='.zip') as f:
+            with zipfile.ZipFile(f, 'w') as zf:
+                zf.writestr('file.tst', 'this is the content')
+            utils.extract_file(f.name, temp_dir)
+            assert os.path.exists(os.path.join(temp_dir, 'file.tst'))
+            with open(os.path.join(temp_dir, 'file.tst'), 'r') as nf:
+                data = nf.read()
+            assert data == 'this is the content'
+        shutil.rmtree(temp_dir)
+
+    def test_extract_tar(self):
+        for ext, mode in zip(['.tar', '.tar.gz'], ['w', 'w:gz']):
+            temp_dir = tempfile.mkdtemp()
+            with tempfile.NamedTemporaryFile() as bf:
+                bf.write("this is the content".encode())
+                bf.seek(0)
+                with tempfile.NamedTemporaryFile(suffix=ext) as f:
+                    with tarfile.open(f.name, mode=mode) as zf:
+                        zf.add(bf.name, arcname='file.tst')
+                    utils.extract_file(f.name, temp_dir)
+                    assert os.path.exists(os.path.join(temp_dir, 'file.tst'))
+                    with open(os.path.join(temp_dir, 'file.tst'), 'r') as nf:
+                        data = nf.read()
+                    assert data == 'this is the content', data
+            shutil.rmtree(temp_dir)
+
+    def test_extract_gzip(self):
+        temp_dir = tempfile.mkdtemp()
+        with tempfile.NamedTemporaryFile(suffix='.gz') as f:
+            with gzip.GzipFile(f.name, 'wb') as zf:
+                zf.write('this is the content'.encode())
+            utils.extract_file(f.name, temp_dir)
+            f_name = os.path.join(temp_dir, os.path.splitext(os.path.basename(f.name))[0])
+            assert os.path.exists(f_name)
+            with open(os.path.join(f_name), 'r') as nf:
+                data = nf.read()
+            assert data == 'this is the content', data
+        shutil.rmtree(temp_dir)
+
 
 if __name__ == '__main__':
     unittest.main()

torchvision/datasets/caltech.py

@@ -4,7 +4,7 @@ import os
 import os.path
 
 from .vision import VisionDataset
-from .utils import download_url, makedir_exist_ok
+from .utils import download_and_extract, makedir_exist_ok
 
 
 class Caltech101(VisionDataset):
@@ -109,28 +109,21 @@ class Caltech101(VisionDataset):
         return len(self.index)
 
     def download(self):
-        import tarfile
-
         if self._check_integrity():
             print('Files already downloaded and verified')
             return
 
-        download_url("http://www.vision.caltech.edu/Image_Datasets/Caltech101/101_ObjectCategories.tar.gz",
+        download_and_extract(
+            "http://www.vision.caltech.edu/Image_Datasets/Caltech101/101_ObjectCategories.tar.gz",
             self.root,
             "101_ObjectCategories.tar.gz",
             "b224c7392d521a49829488ab0f1120d9")
-        download_url("http://www.vision.caltech.edu/Image_Datasets/Caltech101/Annotations.tar",
+        download_and_extract(
+            "http://www.vision.caltech.edu/Image_Datasets/Caltech101/Annotations.tar",
             self.root,
             "101_Annotations.tar",
             "6f83eeb1f24d99cab4eb377263132c91")
 
-        # extract file
-        with tarfile.open(os.path.join(self.root, "101_ObjectCategories.tar.gz"), "r:gz") as tar:
-            tar.extractall(path=self.root)
-
-        with tarfile.open(os.path.join(self.root, "101_Annotations.tar"), "r:") as tar:
-            tar.extractall(path=self.root)
-
     def extra_repr(self):
         return "Target type: {target_type}".format(**self.__dict__)
 
@@ -204,17 +197,12 @@ class Caltech256(VisionDataset):
         return len(self.index)
 
     def download(self):
-        import tarfile
-
         if self._check_integrity():
             print('Files already downloaded and verified')
             return
 
-        download_url("http://www.vision.caltech.edu/Image_Datasets/Caltech256/256_ObjectCategories.tar",
+        download_and_extract(
+            "http://www.vision.caltech.edu/Image_Datasets/Caltech256/256_ObjectCategories.tar",
             self.root,
             "256_ObjectCategories.tar",
             "67b4f42ca05d46448c6bb8ecd2220f6d")
-
-        # extract file
-        with tarfile.open(os.path.join(self.root, "256_ObjectCategories.tar"), "r:") as tar:
-            tar.extractall(path=self.root)

torchvision/datasets/cifar.py

@@ -11,7 +11,7 @@ else:
     import pickle
 
 from .vision import VisionDataset
-from .utils import download_url, check_integrity
+from .utils import check_integrity, download_and_extract
 
 
 class CIFAR10(VisionDataset):
@@ -144,17 +144,10 @@ class CIFAR10(VisionDataset):
         return True
 
     def download(self):
-        import tarfile
-
         if self._check_integrity():
             print('Files already downloaded and verified')
             return
-
-        download_url(self.url, self.root, self.filename, self.tgz_md5)
-
-        # extract file
-        with tarfile.open(os.path.join(self.root, self.filename), "r:gz") as tar:
-            tar.extractall(path=self.root)
+        download_and_extract(self.url, self.root, self.filename, self.tgz_md5)
 
     def extra_repr(self):
         return "Split: {}".format("Train" if self.train is True else "Test")

torchvision/datasets/mnist.py

@@ -4,11 +4,10 @@ import warnings
 from PIL import Image
 import os
 import os.path
-import gzip
 import numpy as np
 import torch
 import codecs
-from .utils import download_url, makedir_exist_ok
+from .utils import download_and_extract, extract_file, makedir_exist_ok
 
 
 class MNIST(VisionDataset):
@@ -120,15 +119,6 @@ class MNIST(VisionDataset):
                 os.path.exists(os.path.join(self.processed_folder,
                                             self.test_file)))
 
-    @staticmethod
-    def extract_gzip(gzip_path, remove_finished=False):
-        print('Extracting {}'.format(gzip_path))
-        with open(gzip_path.replace('.gz', ''), 'wb') as out_f, \
-                gzip.GzipFile(gzip_path) as zip_f:
-            out_f.write(zip_f.read())
-        if remove_finished:
-            os.unlink(gzip_path)
-
     def download(self):
         """Download the MNIST data if it doesn't exist in processed_folder already."""
 
@@ -141,9 +131,7 @@ class MNIST(VisionDataset):
         # download files
         for url in self.urls:
             filename = url.rpartition('/')[2]
-            file_path = os.path.join(self.raw_folder, filename)
-            download_url(url, root=self.raw_folder, filename=filename, md5=None)
-            self.extract_gzip(gzip_path=file_path, remove_finished=True)
+            download_and_extract(url, root=self.raw_folder, filename=filename)
 
         # process and save as torch files
         print('Processing...')
@@ -262,7 +250,6 @@ class EMNIST(MNIST):
     def download(self):
         """Download the EMNIST data if it doesn't exist in processed_folder already."""
         import shutil
-        import zipfile
 
         if self._check_exists():
             return
@@ -271,18 +258,12 @@ class EMNIST(MNIST):
         makedir_exist_ok(self.processed_folder)
 
         # download files
-        filename = self.url.rpartition('/')[2]
-        file_path = os.path.join(self.raw_folder, filename)
-        download_url(self.url, root=self.raw_folder, filename=filename, md5=None)
-
-        print('Extracting zip archive')
-        with zipfile.ZipFile(file_path) as zip_f:
-            zip_f.extractall(self.raw_folder)
-        os.unlink(file_path)
+        print('Downloading and extracting zip archive')
+        download_and_extract(self.url, 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'):
-                self.extract_gzip(gzip_path=os.path.join(gzip_folder, gzip_file))
+                extract_file(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_url, check_integrity, list_dir, list_files
+from .utils import download_and_extract, check_integrity, list_dir, list_files
 
 
 class Omniglot(VisionDataset):
@@ -81,8 +81,6 @@ class Omniglot(VisionDataset):
         return True
 
     def download(self):
-        import zipfile
-
         if self._check_integrity():
             print('Files already downloaded and verified')
             return
@@ -90,10 +88,7 @@ class Omniglot(VisionDataset):
         filename = self._get_target_folder()
         zip_filename = filename + '.zip'
         url = self.download_url_prefix + '/' + zip_filename
-        download_url(url, self.root, zip_filename, self.zips_md5[filename])
-        print('Extracting downloaded file: ' + join(self.root, zip_filename))
-        with zipfile.ZipFile(join(self.root, zip_filename), 'r') as zip_file:
-            zip_file.extractall(self.root)
+        download_and_extract(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/utils.py

 import os
 import os.path
 import hashlib
+import gzip
 import errno
+import tarfile
+import zipfile
+
 from torch.utils.model_zoo import tqdm
 
 
@@ -189,3 +193,46 @@ def _save_response_content(response, destination, chunk_size=32768):
                 progress += len(chunk)
                 pbar.update(progress - pbar.n)
         pbar.close()
+
+
+def _is_tar(filename):
+    return filename.endswith(".tar")
+
+
+def _is_targz(filename):
+    return filename.endswith(".tar.gz")
+
+
+def _is_gzip(filename):
+    return filename.endswith(".gz") and not filename.endswith(".tar.gz")
+
+
+def _is_zip(filename):
+    return filename.endswith(".zip")
+
+
+def extract_file(from_path, to_path, remove_finished=False):
+    if _is_tar(from_path):
+        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:
+            tar.extractall(path=to_path)
+    elif _is_gzip(from_path):
+        to_path = os.path.join(to_path, os.path.splitext(os.path.basename(from_path))[0])
+        with open(to_path, "wb") as out_f, gzip.GzipFile(from_path) as zip_f:
+            out_f.write(zip_f.read())
+    elif _is_zip(from_path):
+        with zipfile.ZipFile(from_path, 'r') as z:
+            z.extractall(to_path)
+    else:
+        raise ValueError("Extraction of {} not supported".format(from_path))
+
+    if remove_finished:
+        os.unlink(from_path)
+
+
+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)