Enable validation against numpy 2.0 release-candidates

[mlxd]

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Context: This Pr allows PennyLane to bee tested with an env-installed numpy 2.0 release candidate. Numpy 2.0 version strings are not compatible with semver, and require so preprocessing to enter the correct form. This will also enable testing against future numpy releases during the dev/rc/post cycles, if published to PyPI.

Description of the Change: As above.

Benefits: Enables testing against numpy dev and RC wheels (post also).

Possible Drawbacks:

Related GitHub Issues:

[github-actions[bot]]

Hello. You may have forgotten to update the changelog! Please edit doc/releases/changelog-dev.md with:

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[mlxd]

[sc-61408]

[codecov[bot]]

Codecov Report

Attention: Patch coverage is 66.66667% with 1 lines in your changes are missing coverage. Please review.

Project coverage is 99.66%. Comparing base (35de283) to head (22fd6bb). Report is 2 commits behind head on master.

Files	Patch %	Lines
pennylane/numpy/random.py	66.66%	1 Missing :warning:

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #5516      +/-   ##
==========================================
- Coverage   99.67%   99.66%   -0.01%     
==========================================
  Files         404      404              
  Lines       37858    37563     -295     
==========================================
- Hits        37734    37437     -297     
- Misses        124      126       +2     

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[mudit2812]

Probably a good idea to run this PR with the ci:run-full-test-suite label once ready for review.

[trbromley]

@mlxd is there anything more to change in this PR before we can look at the CI runs for testing against numpy 2.0?

[mlxd]

@mlxd is there anything more to change in this PR before we can look at the CI runs for testing against numpy 2.0?

Just an update to the CI when we want to start. Since a new RC dropped, I'd expect a release to be imminent, so this can be updated now to validate both versions. How we wish to test though is up for discussion, as splitting the entire pipeline into 2.0, and pre-2.0 will be very expensive. Any thoughts @trbromley

[mlxd]

Currently tensorflow restricts numpy to pre 2.0 in the released wheels (2.16.1). If we aim to install TF on any CI tests it will autodowngrade the version.

[mlxd]

In addition, we have packages such as https://pypi.org/project/osqp/#files which pin to older scipy, which also limits support for numpy 2.0, as the latest release is not compatible.