[fbsync] Added Type Check for cocodetection dataset (#8227)

Reviewed By: vmoens

Differential Revision: D55062775

fbshipit-source-id: 3bfbb2e607b31373bece42ef449bebb863057b34

Co-authored-by: RazaProdigy <[email protected]>
Co-authored-by: Nicolas Hug <[email protected]>

Author: 2 people

test/test_datasets.py

@@ -827,6 +827,11 @@ def test_transforms_v2_wrapper_spawn(self):
         with self.create_dataset(transform=v2.Resize(size=expected_size)) as (dataset, _):
             datasets_utils.check_transforms_v2_wrapper_spawn(dataset, expected_size=expected_size)
 
+    def test_slice_error(self):
+        with self.create_dataset() as (dataset, _):
+            with pytest.raises(ValueError, match="Index must be of type integer"):
+                dataset[:2]
+
 
 class CocoCaptionsTestCase(CocoDetectionTestCase):
     DATASET_CLASS = datasets.CocoCaptions

torchvision/datasets/coco.py

@@ -44,6 +44,10 @@ def _load_target(self, id: int) -> List[Any]:
         return self.coco.loadAnns(self.coco.getAnnIds(id))
 
     def __getitem__(self, index: int) -> Tuple[Any, Any]:
+
+        if not isinstance(index, int):
+            raise ValueError(f"Index must be of type integer, got {type(index)} instead.")
+
         id = self.ids[index]
         image = self._load_image(id)
         target = self._load_target(id)