Force `label` in ClsDatasample long type.

mmcls/core/data_structures/cls_data_sample.py

@@ -30,9 +30,9 @@ def format_label(value: Union[torch.Tensor, np.ndarray, Sequence, int],
         value = int(value.item())
 
     if isinstance(value, np.ndarray):
-        value = torch.from_numpy(value)
+        value = torch.from_numpy(value).to(torch.long)
     elif isinstance(value, Sequence) and not mmcv.is_str(value):
-        value = torch.tensor(value)
+        value = torch.tensor(value).to(torch.long)
     elif isinstance(value, int):
         value = torch.LongTensor([value])
     elif not isinstance(value, torch.Tensor):
@@ -44,7 +44,8 @@ def format_label(value: Union[torch.Tensor, np.ndarray, Sequence, int],
         if value.max() >= num_classes:
             raise ValueError(f'The label data ({value}) should not '
                              f'exceed num_classes ({num_classes}).')
-    label = LabelData(label=value, metainfo=metainfo)
+    label = LabelData(metainfo=metainfo)
+    label.set_field(value, 'label', torch.LongTensor)
     return label
 
 

tests/test_core/test_data_structure.py

@@ -56,13 +56,6 @@ class TestClsDataSample(TestCase):
         self.assertIsInstance(label, LabelData)
         self.assertTrue((label.label == torch.tensor([1, 2, 3])).all())
 
-        # Test Sequence with float number
-        method([0.2, 0, 0.8])
-        self.assertIn(key, data_sample)
-        label = getattr(data_sample, key)
-        self.assertIsInstance(label, LabelData)
-        self.assertTrue((label.label == torch.tensor([0.2, 0, 0.8])).all())
-
         # Test unavailable type
         with self.assertRaisesRegex(TypeError, "<class 'str'> is not"):
             method('hi')