🐛 Describe the bug

We should make sure the following works:

        import torch

        dtype = torch.float8_e8m0fnu
        device = "cuda"

        def foo(x0):
            x1 = x0 + 1
            x2 = x1.view(dtype)
            return x2

        x0 = torch.randint(0, 255, (16, 16), device=device, dtype=torch.uint8)
        foo_c = torch.compile(foo, backend="inductor", fullgraph=True)

        with torch.no_grad():
            y_c = foo_c(x0)

• Today, this fails with the following error message: https://gist.github.com/vkuzo/d2f560d34b7c68fc89671fa8f80f6294
• A failing, skipped test case for this behavior is being added in add pt2 testing for torch.float8_e8m0fnu #147770

This is important for the PT2 support of MX workflows (tracked in pytorch/ao#556). Specifically, once this functionality exists, a user would be able to write a scaling+casting kernel for MX and output the scales directly in the e8m0 dtype, instead of having to output in uint8 and view as e8m0 afterwards.

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