Resolve tests failures in rounding functions with numpy 2.0 #2589
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antonwolfy
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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. |
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LGTM
Thank you @antonwolfy !
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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
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…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".
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…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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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.