[te] Ban uint8 tensors from fusion groups (#49247)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49247
uint8's expose all kind of corner cases in type promotion. As an example, consider:
```
>>> torch.tensor([1], dtype=torch.uint8).lt(-1)
tensor([True])
>>> torch.tensor([1], dtype=torch.uint8).lt(torch.tensor(-1))
tensor([True])
>>> torch.tensor([1], dtype=torch.uint8).lt(torch.tensor([-1]))
tensor([False])
```
the difference is how promotions involving scalars (or 0-dim tensors, which are treated like scalars) are prioritized compared to tensor dtypes.
Per eellison, the order is something like:
1. Tensor FP types
2. Scalar FP types
3. Tensor Int types
4. Scalar Int types
The logic for this is here: https://github.com/pytorch/pytorch/blob/c73e97033a3aef97a5685588ea014d54a5cc11cc/aten/src/ATen/native/TypeProperties.cpp#L93
AFAICT the effects are mainly visible for the unsigned byte type (the only unsigned type, besides bool) since the others degrade more or less gracefully.
It's hard to re-use this logic as is in TensorIterator/TypeProperties, and it's complicated enough that it's not worth re-implementing in TE unless there's evidence that it matters for real models.
ghstack-source-id: 118555597
Test Plan: `buck test //caffe2/test:jit`
Reviewed By: eellison
Differential Revision: D25489035
fbshipit-source-id: db3ab84286d472fd8a247aeb7b36c441293aad85
