Fix _sync_dist for compositional metrics

[SkafteNicki]

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?

What does this PR do?

Fixes #438
self._sync_dist in compositional metrics have a different signature as the base class. Compare this:
https://github.com/PyTorchLightning/metrics/blob/1171a1f12507df5c8206475f3692b31ddab8d934/torchmetrics/metric.py#L216
to this:
https://github.com/PyTorchLightning/metrics/blob/1171a1f12507df5c8206475f3692b31ddab8d934/torchmetrics/metric.py#L666
which leads to the error:
TypeError: _sync_dist() got an unexpected keyword argument 'process_group'

This PR fixes it and add test.

PR review

Anyone in the community is free to review the PR once the tests have passed.
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[codecov]

Codecov Report

Merging #454 (35ac1df) into master (a2712eb) will increase coverage by 20.96%.
The diff coverage is 100.00%.

@@             Coverage Diff             @@
##           master     #454       +/-   ##
===========================================
+ Coverage   74.94%   95.90%   +20.96%     
===========================================
  Files         129      129               
  Lines        4227     4227               
===========================================
+ Hits         3168     4054      +886     
+ Misses       1059      173      -886     

Flag	Coverage Δ
Linux	74.94% <100.00%> (ø)
Windows	74.94% <100.00%> (ø)
cpu	74.94% <100.00%> (ø)
gpu	95.90% <100.00%> (?)
macOS	74.94% <100.00%> (ø)
pytest	95.90% <100.00%> (+20.96%)	⬆️

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

Impacted Files	Coverage Δ
torchmetrics/metric.py	95.78% <100.00%> (+38.85%)	⬆️
torchmetrics/regression/r2.py	94.28% <0.00%> (+2.85%)	⬆️
torchmetrics/regression/explained_variance.py	97.05% <0.00%> (+2.94%)	⬆️
torchmetrics/functional/regression/pearson.py	100.00% <0.00%> (+3.12%)	⬆️
torchmetrics/classification/average_precision.py	96.87% <0.00%> (+3.12%)	⬆️
...chmetrics/classification/precision_recall_curve.py	96.87% <0.00%> (+3.12%)	⬆️
torchmetrics/classification/roc.py	96.77% <0.00%> (+3.22%)	⬆️
torchmetrics/utilities/enums.py	100.00% <0.00%> (+3.44%)	⬆️
torchmetrics/regression/cosine_similarity.py	96.42% <0.00%> (+3.57%)	⬆️
torchmetrics/regression/spearman.py	100.00% <0.00%> (+3.84%)	⬆️
... and 78 more

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