Add argument average to MeanAveragePrecision

[SkafteNicki]

What does this PR do?

Fixes #2004

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📚 Documentation preview 📚: https://torchmetrics--2018.org.readthedocs.build/en/2018/

[codecov]

Codecov Report

Merging #2018 (75d6146) into master (eeb40e9) will decrease coverage by 49%.
Report is 1 commits behind head on master.
The diff coverage is 25%.

Additional details and impacted files

@@           Coverage Diff            @@
##           master   #2018     +/-   ##
========================================
- Coverage      87%     38%    -49%     
========================================
  Files         275     277      +2     
  Lines       15650   15733     +83     
========================================
- Hits        13567    5997   -7570     
- Misses       2083    9736   +7653     

[imatiach-msft]

Amazing!!!! Thank you!

[Advitya17]

Thank you very much @SkafteNicki for such a quick turnaround on the feature request! Please let us know when torchmetrics may be released with this aggregate suport on MAP for object detection, and we can add the aggregate method back on our side on the RAI toolbox repo :)

[SkafteNicki]

Thank you very much @SkafteNicki for such a quick turnaround on the feature request! Please let us know when torchmetrics may be released with this aggregate suport on MAP for object detection, and we can add the aggregate method back on our side on the RAI toolbox repo :)

@Advitya17 regarding release: so we just relased v1.1 of torchmetrics which this feature did not end up being part of. Therefore it may take some time before v1.2 is released. We do not really have fixed dates for released, but do it more dynamically based on when enough features have been added.

[Borda]

pls check the test_average_argument[False] for GPU tests...

[Borda]

@SkafteNicki shall we include it in 1.1.x bug-fix release?

[SkafteNicki]

@Borda fine by me. Do note it is not a bug-fix but a new feature as it has never been a feature of torchmetrics.

[Borda]

Do note it is not a bug-fix but a new feature as it has never been a feature of torchmetrics.

yes I know, but addressing an user issue 🦩