cleaning & prune re-definine

[Borda]

Before submitting

• Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
• Did you read the contributor guideline, Pull Request section?
• Did you make sure to update the docs?
• Did you write any new necessary tests?
• Does this PR contains any breaking changes ? Yes
• Does this PR provides user warning for depreciation ! Yes !

Breaking Changes:

• Rename r2score >> r2_score and kldivergence >> kl_divergence in torchmetrics.functional.

What does this PR do?

normalise some functional metrics names to be consistent
prune some redefinition

PR review

Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.

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[codecov]

Codecov Report

Merging #371 (382a57f) into master (7c9b572) will decrease coverage by 0.01%.
The diff coverage is 97.43%.

@@            Coverage Diff             @@
##           master     #371      +/-   ##
==========================================
- Coverage   96.44%   96.42%   -0.02%     
==========================================
  Files         112      112              
  Lines        3655     3665      +10     
==========================================
+ Hits         3525     3534       +9     
- Misses        130      131       +1     

Flag	Coverage Δ
Linux	76.39% <89.74%> (+<0.01%)	⬆️
Windows	76.39% <89.74%> (+<0.01%)	⬆️
cpu	95.66% <97.43%> (-0.73%)	⬇️
gpu	96.34% <97.43%> (-0.02%)	⬇️
macOS	95.66% <97.43%> (-0.73%)	⬇️
pytest	96.42% <97.43%> (-0.02%)	⬇️
python3.6	?
python3.8	95.60% <97.43%> (-0.79%)	⬇️
python3.9	?
torch1.3.1	?
torch1.4.0	95.60% <97.43%> (-0.02%)	⬇️
torch1.9.0	?

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
torchmetrics/classification/kl_divergence.py	87.87% <ø> (ø)
torchmetrics/functional/classification/accuracy.py	92.95% <0.00%> (-1.33%)	⬇️
torchmetrics/retrieval/mean_average_precision.py	100.00% <ø> (ø)
...hmetrics/classification/binned_precision_recall.py	100.00% <100.00%> (ø)
torchmetrics/functional/__init__.py	100.00% <100.00%> (ø)
torchmetrics/functional/classification/__init__.py	100.00% <100.00%> (ø)
torchmetrics/functional/classification/auc.py	90.62% <100.00%> (ø)
...metrics/functional/classification/kl_divergence.py	90.62% <100.00%> (+1.33%)	⬆️
torchmetrics/functional/regression/__init__.py	100.00% <100.00%> (ø)
torchmetrics/functional/regression/psnr.py	96.96% <100.00%> (ø)
... and 3 more

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