add test

Author: pmeier

test/builtin_dataset_mocks.py

@@ -43,7 +43,8 @@ def _download(self, _):
 class DatasetMock:
     def __init__(self, name, mock_data_fn, *, configs=None):
         self.dataset = find(name)
-        self.root = TEST_HOME / self.dataset.name
+        self.home = TEST_HOME
+        self.root = self.home / self.dataset.name
         self.mock_data_fn = self._parse_mock_data(mock_data_fn)
         self.configs = configs or self.info._configs
         self._cache = {}
@@ -100,7 +101,7 @@ def wrapper(info, root, config):
 
         return wrapper
 
-    def _load_mock(self, config):
+    def make_mock_resources(self, config):
         with contextlib.suppress(KeyError):
             return self._cache[config]
 
@@ -120,7 +121,7 @@ def load(self, config, *, decoder=DEFAULT_DECODER):
         except ModuleNotFoundError as error:
             pytest.skip(str(error))
 
-        mock_resources, mock_info = self._load_mock(config)
+        mock_resources, mock_info = self.make_mock_resources(config)
         datapipe = self.dataset._make_datapipe(
             [resource.load(self.root) for resource in mock_resources],
             config=config,

test/test_prototype_builtin_datasets.py

@@ -6,7 +6,7 @@
 from torch.utils.data.datapipes.iter.grouping import ShardingFilterIterDataPipe as ShardingFilter
 from torch.utils.data.graph import traverse
 from torchdata.datapipes.iter import IterDataPipe, Shuffler
-from torchvision.prototype import transforms
+from torchvision.prototype import transforms, datasets
 from torchvision.prototype.utils._internal import sequence_to_str
 
 
@@ -85,6 +85,13 @@ def scan(graph):
         else:
             raise AssertionError(f"The dataset doesn't comprise a {annotation_dp_type.__name__}() datapipe.")
 
+    def test_loadable_through_api(self, mocker, dataset_mock, config):
+        # Make all resources that are necessary for the given config
+        dataset_mock.make_mock_resources(config)
+        mocker.patch("torchvision.prototype.datasets._api.home", return_value=str(dataset_mock.home))
+
+        datasets.load(dataset_mock.name, **config)
+
 
 class TestQMNIST:
     @parametrize_dataset_mocks([mock for mock in DATASET_MOCKS if mock.name == "qmnist"])