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When trying to fix #210 I am seeing a lot of casting code which can be distracting and really not important. What if we use something like
https://numpy.org/doc/stable/reference/typing.html#number-precision
or even
from jaxtyping import Array
from https://docs.kidger.site/jaxtyping/ (despite the name of the package we can just use it for NumPy)
JAX has a nice array convention, but I do not see this in NumPy (ArrayLike, yes but not purely Array), see https://jax.readthedocs.io/en/latest/jep/12049-type-annotations.html
Thoughts?
The text was updated successfully, but these errors were encountered:
not sure which one is a better solution. But I agree with your diagnostics.
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Ok! Let me do some research these days to have better data and options 🤔
Actually, in dd6a6e8 I just removed the reference to the specific float precision (np.float64) and things look cleaner.
np.float64
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When trying to fix #210 I am seeing a lot of casting code which can be distracting and really not important. What if we use something like
https://numpy.org/doc/stable/reference/typing.html#number-precision
or even
from https://docs.kidger.site/jaxtyping/ (despite the name of the package we can just use it for NumPy)
JAX has a nice array convention, but I do not see this in NumPy (ArrayLike, yes but not purely Array), see https://jax.readthedocs.io/en/latest/jep/12049-type-annotations.html
Thoughts?
The text was updated successfully, but these errors were encountered: