allow numpy integers for partition functions for backwards compatibility

[hjtran]

Followup to #35881 (comment)

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[hjtran]

R: @liferoad

[gemini-code-assist]

Summary of Changes

Hello @hjtran, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses a compatibility issue where Apache Beam's Partition transform would incorrectly raise a ValueError when a PartitionFn returned a NumPy integer type instead of a standard Python int. The changes allow NumPy integer types to be accepted, ensuring that existing codebases using NumPy integers for partitioning continue to function correctly without modification.

Highlights

• NumPy Integer Compatibility: Modified the PartitionFn to correctly recognize and accept NumPy integer types (e.g., numpy.int32) as valid partition values, preventing ValueError exceptions.
• Backwards Compatibility: This change ensures backward compatibility for users who might be providing NumPy integer types to partition functions, aligning with expected behavior.
• Test Coverage: Added a new test case to verify that the Partition transform correctly handles numpy.int32 inputs, ensuring the fix works as intended.

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[hjtran]

Ah! Looks like @liferoad already simultaneously wrote up a fix in #36044 . I'll close this in favor of that PR since those changes look a bit more thorough