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And note that the name is now historical – it also supports PyTorch/TensorFlow/NumPy, and has no JAX dependency.
There are a few places where I can imagine this to be helpful, e.g. returns from infer that are one-element tensors (where users might expect floats) or predictions from batched models.
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Summary
Type information that includes tensor shapes could be a powerful way of extended validation (including runtime via
typeguard
/beartype
). The https://github.com/google/jaxtyping project looks rather promising for this. See also https://kidger.site/thoughts/jaxtyping/, specifically:There are a few places where I can imagine this to be helpful, e.g. returns from
infer
that are one-element tensors (where users might expect floats) or predictions from batched models.Additional Information
n/a
Code of Conduct
The text was updated successfully, but these errors were encountered: