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For larger projects, TensorType[T.BATCH] (where T is an enum) can be better than TensorType["batch"], as it enables standard naming conventions & additional code hints.
It would be great to support this out of the box.
The text was updated successfully, but these errors were encountered:
In practice though, TorchTyping is now semi-deprecated in favour of jaxtyping. (Which supports PyTorch too, despite the name.)
It also supports static type checkers etc., doesn't do crazy monkey-patching of typeguard, etc, which is the reason I'm trying to transition people over to it.
In terms of this suggestion: jaxtyping does go all-in on using a string-based DSL. I imagine you could accomplish something similar to this suggestion by simply passing around strings.
For larger projects,
TensorType[T.BATCH]
(whereT
is an enum) can be better thanTensorType["batch"]
, as it enables standard naming conventions & additional code hints.It would be great to support this out of the box.
The text was updated successfully, but these errors were encountered: