def METHOD_NAME(self):
    input_size = (13, 13)
    crop_size = (3, 3)
    stride_size = (2, 2)
    model = DummyModel()
    input_tensor = torch.randn((1, 1) + input_size)
    reconstructed_input = forward_with_sliding_window_wrapper(model.forward, input_tensor, stride_size, crop_size, self.num_classes)
    self._assert_tensors_equal(input_tensor, reconstructed_input)