Fix: typo in dict processing

Summary:
David had his code crashed when using frame_annot["meta"] dictionary. Turns out we had a typo.
The tests were passing by chance since all the keys were single-character strings.

Reviewed By: bottler

Differential Revision: D37503987

fbshipit-source-id: c12b0df21116cfbbc4675a0182b9b9e6d62bad2e

pytorch3d/implicitron/dataset/types.py

@@ -226,7 +226,7 @@ def _dataclass_list_from_dict_list(dlist, typeannot):
 
         keys = np.split(list(all_keys_res), indices[:-1])
         vals = np.split(list(all_vals_res), indices[:-1])
-        return [cls(zip(*k, v)) for k, v in zip(keys, vals)]
+        return [cls(zip(k, v)) for k, v in zip(keys, vals)]
     elif not dataclasses.is_dataclass(typeannot):
         return dlist
 

tests/implicitron/test_types.py

@@ -73,8 +73,8 @@ def test_parsing(self):
         )
 
         # dict
-        parsed = types._dataclass_from_dict({"k": dct}, Dict[str, FrameAnnotation])
-        self.assertEqual(parsed, {"k": self.entry})
+        parsed = types._dataclass_from_dict({"key": dct}, Dict[str, FrameAnnotation])
+        self.assertEqual(parsed, {"key": self.entry})
 
     def test_parsing_vectorized(self):
         dct = dataclasses.asdict(self.entry)
@@ -83,10 +83,10 @@ def test_parsing_vectorized(self):
         self._compare_with_scalar(_NT(dct), _NT)
         self._compare_with_scalar((dct,), Tuple[FrameAnnotation])
         self._compare_with_scalar([dct], List[FrameAnnotation])
-        self._compare_with_scalar({"k": dct}, Dict[str, FrameAnnotation])
+        self._compare_with_scalar({"key": dct}, Dict[str, FrameAnnotation])
 
         dct2 = dct.copy()
-        dct2["meta"] = {"d": 76}
+        dct2["meta"] = {"aux": 76}
         self._compare_with_scalar(dct2, FrameAnnotation)
 
     def _compare_with_scalar(self, obj, typeannot, repeat=3):