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This PR adds a function that creates a mask from strings that represent a regex. I also add a aliases for a few frequent use cases:
Masks are returned as boolean
np.ndarray
, and can thus be combined using|
(logical or) and&
(logical and):I originally used
torch.tensor
s but decided to usenumpy.ndarray
s in the end. While this could allow supporting models written with different frameworks, I am still wondering if the conversion to and from the frameworks would slow down the generation due to copying the content of the arrays.In the Numpy-> Framework direction,
jax.numpy.asarray
does not copy the input is anumpy.ndarray
, and neither doestorch.from_numpy
. So we should be able to return NumPy arrays here without adding any overhead.