add test for svhn

Author: Philip Meier

test/fakedata_generation.py

@@ -168,3 +168,20 @@ def _make_devkit_archive(root):
         _make_devkit_archive(root)
 
         yield root
+
+
+@contextlib.contextmanager
+def svhn_root():
+    import scipy.io as sio
+
+    def _make_mat(file):
+        images = np.zeros((32, 32, 3, 2), dtype=np.uint8)
+        targets = np.zeros((2,), dtype=np.uint8)
+        sio.savemat(file, {'X': images, 'y': targets})
+
+    with get_tmp_dir() as root:
+        _make_mat(os.path.join(root, "train_32x32.mat"))
+        _make_mat(os.path.join(root, "test_32x32.mat"))
+        _make_mat(os.path.join(root, "extra_32x32.mat"))
+
+        yield root

test/test_datasets.py

@@ -6,7 +6,7 @@
 from torch._utils_internal import get_file_path_2
 import torchvision
 from common_utils import get_tmp_dir
-from fakedata_generation import mnist_root, cifar_root, imagenet_root
+from fakedata_generation import mnist_root, cifar_root, imagenet_root, svhn_root
 
 
 class Tester(unittest.TestCase):
@@ -133,6 +133,13 @@ def test_cifar100(self, mock_ext_check, mock_int_check):
             img, target = dataset[0]
             self.assertEqual(dataset.class_to_idx[dataset.classes[0]], target)
 
+    @mock.patch('torchvision.datasets.SVHN._check_integrity')
+    def test_svhn(self, mock_check):
+        mock_check.return_value = True
+        with svhn_root() as root:
+            dataset = torchvision.datasets.SVHN(root, split="train")
+            self.generic_classification_dataset_test(dataset, num_images=2)
+
 
 if __name__ == '__main__':
     unittest.main()