Fix 2.4.1 warnings

test/test_a_memory_leak/util.py

@@ -23,6 +23,7 @@
 from __future__ import annotations
 
 import gc
+import warnings
 
 import torch
 
@@ -41,12 +42,17 @@ def garbage_collect() -> None:
 
 def _tensors_from_gc() -> Generator[Tensor, None, None]:
     # return [obj for obj in gc.get_objects() if isinstance(obj, Tensor)]
-    for obj in gc.get_objects():
-        try:
-            if isinstance(obj, Tensor):
-                yield obj
-        except Exception:  # nosec B112 pylint: disable=broad-exception-caught
-            continue
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore", FutureWarning)
+
+        for obj in gc.get_objects():
+            try:
+                if isinstance(obj, Tensor):
+                    yield obj
+            except (
+                Exception
+            ):  # nosec B112 pylint: disable=broad-exception-caught
+                continue
 
 
 @overload

test/test_hamiltonian/test_base.py

@@ -25,6 +25,7 @@
 
 import pytest
 import torch
+from tad_mctc._version import __tversion__
 
 from dxtb import GFN1_XTB as par
 from dxtb import IndexHelper
@@ -51,12 +52,16 @@ def test_write_to_pt() -> None:
     h = GFN1Hamiltonian(numbers, par, ihelp)
     h._matrix = torch.tensor([[1.0, 2.0], [3.0, 4.0]])
 
+    kwargs: dict = {"map_location": torch.device("cpu")}
+    if __tversion__ > (1, 12, 1):
+        kwargs["weights_only"] = True
+
     with td.TemporaryDirectory() as tmpdir:
         p_write = Path(tmpdir) / "test.pt"
         h.to_pt(p_write)
 
-        read_mat = torch.load(p_write)
-        assert pytest.approx(h._matrix.cpu()) == read_mat.cpu()
+        read_mat = torch.load(p_write, **kwargs)
+        assert pytest.approx(h._matrix.cpu()) == read_mat
 
     with td.TemporaryDirectory() as tmpdir:
         p_write = Path(tmpdir) / f"{h.label.casefold()}"
@@ -65,5 +70,5 @@ def test_write_to_pt() -> None:
         h.label = str(p_write)
         h.to_pt()
 
-        read_mat = torch.load(f"{p_write}.pt")
-        assert pytest.approx(h._matrix.cpu()) == read_mat.cpu()
+        read_mat = torch.load(f"{p_write}.pt", **kwargs)
+        assert pytest.approx(h._matrix.cpu()) == read_mat