That is, classes supporting the __torch_function__ protocol.
This shouldn't be too difficult -- most of the necessary work has already been done.
There's some places where we have torch.Tensor hardcoded, for example in instance checks and some type annotations, that would need adjusting to accept tensor-likes.
TensorTypeMixin would need exposing as a public part of the interface.
The documentation needs updating to show how this is possible. Once the above changes are made it should just be:
from torchtyping import TensorTypeMixin
class TensorLike:
...
class TensorLikeType(TensorLike, TensorTypeMixin):
base_cls = TensorLike
That is, classes supporting the
__torch_function__protocol.This shouldn't be too difficult -- most of the necessary work has already been done.
torch.Tensorhardcoded, for example in instance checks and some type annotations, that would need adjusting to accept tensor-likes.TensorTypeMixinwould need exposing as a public part of the interface.