DynamicShape[__main__](float32_0<1,3,128,128>) -> float32_10<1,16,86,86>
 │  Conv2d[torch.nn.modules.conv](float32_0<1,3,128,128>) -> float32_3<1,16,128,128>
 │   └· conv2d[torch.nn.functional](float32_0<1,3,128,128>, float32_1<16,3,1,1>, float32_2<16>, (1, 1), (0, 0), (1, 1), 1) -> float32_3<1,16,128,128>
 │  shape[nobuco.funcs](float32_3<1,16,128,128>) -> (int32_4<>, int32_5<>, int32_6<>, int32_7<>)
 │  __floordiv__[torch.Tensor](int32_6<>, 3) -> int32_8<>
 │   └· floor_divide[torch](int32_6<>, 3) -> int32_8<>
 │  __floordiv__[torch.Tensor](int32_7<>, 3) -> int32_9<>
 │   └· floor_divide[torch](int32_7<>, 3) -> int32_9<>
 └· __getitem__[torch.Tensor](float32_3<1,16,128,128>, (:, :, int32_8<>:, int32_9<>:)) -> float32_10<1,16,86,86>