chore: appease warnings

optree/integration/jax.py

@@ -201,7 +201,7 @@ def _ravel_leaves(
     leaves: list[ArrayLike],
 ) -> tuple[Array, Callable[[Array], list[ArrayLike]]]:
     if not leaves:
-        return (jnp.array([]), _unravel_empty)
+        return (jnp.zeros(0), _unravel_empty)
 
     from_dtypes = tuple(dtypes.dtype(leaf) for leaf in leaves)
     to_dtype = dtypes.result_type(*from_dtypes)

optree/integration/numpy.py

@@ -130,7 +130,7 @@ def _ravel_leaves(
     leaves: list[np.ndarray],
 ) -> tuple[np.ndarray, Callable[[np.ndarray], list[np.ndarray]]]:
     if not leaves:
-        return (np.array([]), _unravel_empty)
+        return (np.zeros(0), _unravel_empty)
 
     from_dtypes = tuple(np.result_type(leaf) for leaf in leaves)
     to_dtype = np.result_type(*leaves)

optree/integration/torch.py

@@ -127,7 +127,7 @@ def _ravel_leaves(
     leaves: list[torch.Tensor],
 ) -> tuple[torch.Tensor, Callable[[torch.Tensor], list[torch.Tensor]]]:
     if not leaves:
-        return (torch.tensor([]), _unravel_empty)
+        return (torch.zeros(0), _unravel_empty)
     if not all(torch.is_tensor(leaf) for leaf in leaves):
         raise ValueError('All leaves must be tensors.')
 

tests/helpers.py

@@ -43,7 +43,8 @@ def parametrize(**argvalues):
     argvalues = list(itertools.product(*tuple(map(argvalues.get, arguments))))
 
     ids = tuple(
-        '-'.join(f'{arg}({val!r})' for arg, val in zip(arguments, values)) for values in argvalues
+        '-'.join(f'{arg}({value!r})' for arg, value in zip(arguments, values))
+        for values in argvalues
     )
 
     return pytest.mark.parametrize(arguments, argvalues, ids=ids)