def METHOD_NAME(self):
    """Asserts works with both cuda and cpu input data"""
    dev = qml.device("default.qubit.torch", wires=1)
    x = torch.tensor(0.1, requires_grad=True, device=torch.device("cuda"))
    y = torch.tensor(0.2, requires_grad=True, device=torch.device("cpu"))
    with qml.queuing.AnnotatedQueue() as q:
        qml.RX(x, wires=0)
        qml.RY(y, wires=0)
        qml.expval(qml.PauliX(0))
    tape = qml.tape.QuantumScript.from_queue(q)
    res = dev.execute(tape)
    assert res.is_cuda
    assert "cuda" in dev._torch_device
    res.backward()
    assert x.grad.is_cuda
    # check that computing the gradient with respect to y works
    _ = y.grad