def METHOD_NAME(self):
    input_size = (513, 513)
    crop_size = (512, 512)
    stride_size = (640, 640)
    model = DummyModel()
    input_tensor = torch.randn((1, 1) + input_size)
    with self.assertRaises(ValueError):
        forward_with_sliding_window_wrapper(model.forward, input_tensor, stride_size, crop_size, self.num_classes)