Optimized type-changing of features from numpy to torch

- Bugfix: `torch` throws warnings when copying a tensor via initialization
- Added lambda to `.clone()` those tensors instead

openfold/data/feature_pipeline.py

@@ -41,8 +41,9 @@ def np_to_tensor_dict(
         A dictionary of features mapping feature names to features. Only the given
         features are returned, all other ones are filtered out.
     """
+    to_tensor = lambda t: torch.tensor(t) if type(t) != torch.Tensor else t.clone().detach()
     tensor_dict = {
-        k: torch.tensor(v) for k, v in np_example.items() if k in features
+        k: to_tensor(v) for k, v in np_example.items() if k in features
     }
 
     return tensor_dict