Add TorchTyping?

[GilesStrong]

Recently I attended the PyTorch Developer event and one of the posters advertised the torchtyping package which can be used to better type-hint tensors in the code, by showing the expected dimensions with string descriptions, e.g.:

def batch_outer_product(x:   TensorType["batch", "x_channels"],
                        y:   TensorType["batch", "y_channels"]
                        ) -> TensorType["batch", "x_channels", "y_channels"]:

    return x.unsqueeze(-1) * y.unsqueeze(-2)

The dimensions of tensors can also be checked at runtime.

This is potentially useful for both developers & power-users, due to more detailed type-hinting and better diagnostics when using custom modules.

However, it is not compatible with MyPy static type-checking, meaning that TensorType must be treated as Any:

from torchtyping import TensorType  # type: ignore

Whilst not essential, replacing the Tensor type-hints in the codebase with TensorType could be useful.