diff --git a/.github/workflows/tests-schedule.yml b/.github/workflows/tests-schedule.yml
index f0c54b6a40b..aede262fafe 100644
--- a/.github/workflows/tests-schedule.yml
+++ b/.github/workflows/tests-schedule.yml
@@ -31,6 +31,9 @@ jobs:
           pip install numpy
           pip install --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
 
+      - name: Install all optional dataset requirements
+        run: pip install scipy pandas pycocotools lmdb requests
+
       - name: Install tests requirements
         run: pip install pytest
 
diff --git a/test/test_datasets_download.py b/test/test_datasets_download.py
index c6e95ffe064..0a49752fe12 100644
--- a/test/test_datasets_download.py
+++ b/test/test_datasets_download.py
@@ -49,17 +49,22 @@ def inner_wrapper(request, *args, **kwargs):
 def log_download_attempts(
     urls_and_md5s=None,
     patch=True,
-    download_url_target="torchvision.datasets.utils.download_url",
+    download_url_location=".utils",
     patch_auxiliaries=None,
 ):
     if urls_and_md5s is None:
         urls_and_md5s = set()
+    if download_url_location.startswith("."):
+        download_url_location = f"torchvision.datasets{download_url_location}"
     if patch_auxiliaries is None:
         patch_auxiliaries = patch
 
     with contextlib.ExitStack() as stack:
         download_url_mock = stack.enter_context(
-            unittest.mock.patch(download_url_target, wraps=None if patch else download_url)
+            unittest.mock.patch(
+                f"{download_url_location}.download_url",
+                wraps=None if patch else download_url,
+            )
         )
         if patch_auxiliaries:
             # download_and_extract_archive
@@ -132,9 +137,17 @@ def make_download_configs(urls_and_md5s, name=None):
     ]
 
 
-def collect_download_configs(dataset_loader, name, **kwargs):
-    with contextlib.suppress(Exception), log_download_attempts(**kwargs) as urls_and_md5s:
-        dataset_loader()
+def collect_download_configs(dataset_loader, name=None, **kwargs):
+    urls_and_md5s = set()
+    try:
+        with log_download_attempts(urls_and_md5s=urls_and_md5s, **kwargs):
+            dataset = dataset_loader()
+    except Exception:
+        dataset = None
+
+    if name is None and dataset is not None:
+        name = type(dataset).__name__
+
     return make_download_configs(urls_and_md5s, name)
 
 
@@ -146,34 +159,40 @@ def places365():
 
                 datasets.Places365(root, split=split, small=small, download=True)
 
-    return make_download_configs(urls_and_md5s, "Places365")
+    return make_download_configs(urls_and_md5s, name="Places365")
 
 
 def caltech101():
-    return collect_download_configs(lambda: datasets.Caltech101(".", download=True), "Caltech101")
+    return collect_download_configs(lambda: datasets.Caltech101(".", download=True), name="Caltech101")
 
 
 def caltech256():
-    return collect_download_configs(lambda: datasets.Caltech256(".", download=True), "Caltech256")
+    return collect_download_configs(lambda: datasets.Caltech256(".", download=True), name="Caltech256")
 
 
 def cifar10():
-    return collect_download_configs(lambda: datasets.CIFAR10(".", download=True), "CIFAR10")
+    return collect_download_configs(lambda: datasets.CIFAR10(".", download=True), name="CIFAR10")
 
 
 def cifar100():
-    return collect_download_configs(lambda: datasets.CIFAR10(".", download=True), "CIFAR100")
+    return collect_download_configs(lambda: datasets.CIFAR10(".", download=True), name="CIFAR100")
 
 
 def voc():
-    download_configs = []
-    for year in ("2007", "2007-test", "2008", "2009", "2010", "2011", "2012"):
-        with contextlib.suppress(Exception), log_download_attempts(
-            download_url_target="torchvision.datasets.voc.download_url"
-        ) as urls_and_md5s:
-            datasets.VOCSegmentation(".", year=year, download=True)
-        download_configs.extend(make_download_configs(urls_and_md5s, f"VOC, {year}"))
-    return download_configs
+    return itertools.chain(
+        *[
+            collect_download_configs(
+                lambda: datasets.VOCSegmentation(".", year=year, download=True),
+                name=f"VOC, {year}",
+                download_url_location=".voc",
+            )
+            for year in ("2007", "2007-test", "2008", "2009", "2010", "2011", "2012")
+        ]
+    )
+
+
+def mnist():
+    return collect_download_configs(lambda: datasets.MNIST(".", download=True), name="MNIST")
 
 
 def make_parametrize_kwargs(download_configs):
@@ -196,6 +215,7 @@ def make_parametrize_kwargs(download_configs):
             cifar100(),
             # The VOC download server is unstable. See https://github.com/pytorch/vision/issues/2953 for details.
             # voc(),
+            mnist(),
         )
     )
 )