diff --git a/src/dxtb/_src/calculators/types/base.py b/src/dxtb/_src/calculators/types/base.py
index 37aed0de..e47c6b4c 100644
--- a/src/dxtb/_src/calculators/types/base.py
+++ b/src/dxtb/_src/calculators/types/base.py
@@ -53,7 +53,7 @@ class and implement the :meth:`calculate` method and the corresponding methods
 from dxtb._src.constants import defaults
 from dxtb._src.param import Param
 from dxtb._src.timing import timer
-from dxtb._src.typing import Any, Self, Tensor, get_default_dtype, override
+from dxtb._src.typing import Any, Self, Tensor, override
 from dxtb.config import Config
 from dxtb.integrals import Integrals
 from dxtb.typing import Tensor, TensorLike
diff --git a/test/test_calculator/test_dd.py b/test/test_calculator/test_dd.py
index 50d37d0f..a436e16b 100644
--- a/test/test_calculator/test_dd.py
+++ b/test/test_calculator/test_dd.py
@@ -26,18 +26,21 @@
 
 from dxtb import GFN1_XTB as par
 from dxtb import Calculator
-from dxtb._src.timing import timer
-from dxtb._src.typing import MockTensor
+from dxtb._src.typing import MockTensor, Tensor
 
 
 def test_fail_dtype() -> None:
-    numbers = torch.tensor([6, 1])
+    numbers = torch.tensor([3, 1])
     positions = torch.tensor([[0.0, 0.0, 0.0], [0.0, 0.0, 1.0]])
-    charge = torch.tensor([0.0])
-    spin = torch.tensor([0.0])
+    charge = torch.tensor(0.0)
+    spin = torch.tensor(0.0)
 
     calc = Calculator(numbers, par, opts={"verbosity": 0})
 
+    # same dtype works
+    e = calc.get_energy(positions, charge, spin)
+    assert isinstance(e, Tensor)
+
     with pytest.raises(DtypeError):
         calc.get_energy(positions.type(torch.double), charge, spin)
 
@@ -47,19 +50,20 @@ def test_fail_dtype() -> None:
     with pytest.raises(DtypeError):
         calc.get_energy(positions, charge, spin.type(torch.double))
 
-    # because of the exception, the timer for the setup is never stopped
-    timer.reset()
-
 
 def test_fail_device() -> None:
-    numbers = torch.tensor([6, 1])
+    numbers = torch.tensor([3, 1])
 
     _positions = torch.tensor([[0.0, 0.0, 0.0], [0.0, 0.0, 1.0]])
-    _charge = torch.tensor([0.0])
-    _spin = torch.tensor([0.0])
+    _charge = torch.tensor(0.0)
+    _spin = torch.tensor(0.0)
 
     calc = Calculator(numbers, par, opts={"verbosity": 0}, dtype=torch.float)
 
+    # same device works
+    e = calc.get_energy(_positions, _charge, _spin)
+    assert isinstance(e, Tensor)
+
     with pytest.raises(DeviceError):
         positions = MockTensor(_positions)
         positions.device = torch.device("cuda")
@@ -74,6 +78,3 @@ def test_fail_device() -> None:
         spin = MockTensor(_spin)
         spin.device = torch.device("cuda")
         calc.get_energy(_positions, _charge, spin)
-
-    # because of the exception, the timer for the setup is never stopped
-    timer.reset()