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@antonwolfy antonwolfy commented Sep 24, 2025

There is data type mismatch in result returned for the rounding functions, because numpy.ceil, numpy.floor, numpy.trunc, and numpy.fix always returns floating dtype for "numpy < 2.1.0".

The dpnp behavior is aligned with "numpy >= 2.1.0", so this PR adds a missing fixture to run the test depending on minimum required numpy version.

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@antonwolfy antonwolfy changed the title Resolve tests failures with rounding functions towards numpy 2.0 Resolve tests failures in rounding functions with numpy 2.0 Sep 24, 2025
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github-actions bot commented Sep 24, 2025

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

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Array API standard conformance tests for dpnp=0.19.0dev5=py313h509198e_3 ran successfully.
Passed: 1227
Failed: 0
Skipped: 9

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LGTM
Thank you @antonwolfy !

@antonwolfy antonwolfy merged commit bea5156 into master Sep 24, 2025
106 of 110 checks passed
@antonwolfy antonwolfy deleted the fix-round-func-tests-with-numpy-2.0 branch September 24, 2025 14:18
github-actions bot added a commit that referenced this pull request Sep 24, 2025
There is data type mismatch in result returned for the rounding
functions, because numpy.ceil, numpy.floor, numpy.trunc, and numpy.fix
always returns floating dtype for "numpy < 2.1.0".

The dpnp behavior is aligned with "numpy >= 2.1.0", so this PR adds a
missing fixture to run the test depending on minimum required numpy
version. bea5156
antonwolfy added a commit that referenced this pull request Sep 24, 2025
…2590)

The PR is follow of #2589 to address remaining issue observing on
Windows only.

There is data type mismatch in result returned for numpy.power,
numpy.floor_divide, numpy.fmod, and numpy.remainder for "numpy < 2.1.0".
They return int32, but expected int64.
Where dpnp behavior is aligned with "numpy >= 2.1.0".
github-actions bot added a commit that referenced this pull request Sep 24, 2025
…2590)

The PR is follow of #2589 to address remaining issue observing on
Windows only.

There is data type mismatch in result returned for numpy.power,
numpy.floor_divide, numpy.fmod, and numpy.remainder for "numpy < 2.1.0".
They return int32, but expected int64.
Where dpnp behavior is aligned with "numpy >= 2.1.0". 222b50f
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2 participants