[docs] Table of accepted image tensor dtypes for all transforms

[vadimkantorov]

📚 The doc issue

Many transforms support equally float32 and uint8, but it seems not documented. Or sometimes some image formats aren't supported but it's not clear why so: e.g. torchvision.transforms.functional.normalize throws when given a uint8 image, but there seems no big reason why it can't autocast uint8 inputs to float32 (just as most pytorch core ops do now).

Sometimes uint8 can be more convenient since it saves memory or sometimes even int16 is necessary: https://discuss.pytorch.org/t/colorjitter-transformation-for-16-bit-images/108897. Uint8 images are also more convenient for no-copy interop with OpenCV or PIL.

Suggest a potential alternative/fix

No response

[datumbox]

Good proposal. We will be revamping our documentation this half for models, so next we can definitely look into doing it for Transforms.

cc @NicolasHug @pmeier