[antonwolfy]

NumPy 2.6 defines numpy.positive and the unary + operator for boolean arrays: they return a boolean copy of the input instead of raising TypeError. This PR aligns dpnp.positive and + on dpnp.ndarray with that behavior.

>>> import dpnp as np
>>> x = np.array([True, False])
>>> +x
array([ True, False])

dpnp.tensor.positive has no boolean loop, so for boolean input dpnp.positive runs the dpnp.tensor abs kernel, which returns boolean values unchanged. NumPy reuses its absolute loop for this case the same way. Other dtypes still use the positive kernel. dpnp.tensor.positive and + on usm_ndarray are unchanged.

The acceptance function that raised TypeError for boolean input is removed, since boolean input now has its own loop and never goes through type promotion.

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• Have you tested your changes locally for CPU and GPU devices?
• Have you made sure that new changes do not introduce compiler warnings?
• Have you checked performance impact of proposed changes?
• Have you added documentation for your changes, if necessary?
• Have you added your changes to the changelog?

[github-actions]

View rendered docs @ https://intelpython.github.io/dpnp/index.html

[coveralls]

coverage: 82.649% (+0.004%) from 82.645% — support-boolean-positive into master

[ndgrigorian]

We recently had the issues with casting to and from bool with non-zero bytes and alignment with NumPy (#3055), will it be an issue here?

[antonwolfy]

No, it shouldn't be an issue.

The boolean input is dispatched to the abs kernel, and since #3055 every path AbsFunctor<bool> can take (contiguous sub-group, scalar fallback and strided) reads the input through normalize_bool, so any non-zero byte is treated as True and the result always holds a canonical 0x00/0x01 byte.

I also checked it with bytes [0, 1, 2, 255, 0x80, 0x10, 0, 3] viewed as bool, for contiguous, strided, reversed and in-place (out=) inputs, and the result bytes matched NumPy's in every case.

[ndgrigorian]

If it's verified there is no problem with the previous comment, LGTM

[github-actions]

Array API standard conformance tests for dpnp=0.21.0dev16=np2py314h8d9cdd5_14 ran successfully.
Passed: 1491
Failed: 0
Skipped: 6