Fix MetricCollection dict keys when used with ClasswiseWrapper

[sup3rgiu]

What does this PR do?

When a ClasswiseWrapper is inserted into a MetricCollection, the resulting output dictionary does not take into account the specified name.

from torchmetrics import MetricCollection
from torchmetrics.wrappers import ClasswiseWrapper
from torchmetrics.classification import MulticlassAccuracy, MulticlassRecall
labels = ["horse", "fish", "dog"]
metric = MetricCollection(
    {'my/name/': ClasswiseWrapper(MulticlassAccuracy(num_classes=3, average=None), labels, prefix='accuracy_'),
    'my/other_name/': ClasswiseWrapper(MulticlassRecall(num_classes=3, average=None), labels, prefix='recall_')}
)
preds = torch.randn(10, 3).softmax(dim=-1)
target = torch.randint(3, (10,))
metric(preds, target)  

The previous code produces the following output:

{'accuracy_horse': tensor(0.5000),
 'accuracy_fish': tensor(0.2500),
 'accuracy_dog': tensor(0.5000),
 'recall_horse': tensor(0.5000),
 'recall_fish': tensor(0.2500),
 'recall_dog': tensor(0.5000)}

While with proposed fix, the output is the following:

{'my/name/accuracy_horse': tensor(0.5000),
 'my/name/accuracy_fish': tensor(0.2500),
 'my/name/accuracy_dog': tensor(0.5000),
 'my/other_name/recall_horse': tensor(0.5000),
 'my/other_name/recall_fish': tensor(0.2500),
 'my/other_name/recall_dog': tensor(0.5000)}

Before submitting

• Was this discussed/agreed 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?

PR review

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📚 Documentation preview 📚: https://torchmetrics--2361.org.readthedocs.build/en/2361/

[Borda]

@sup3rgiu please see the failing doctest, seems that chnege does not work as intended yet...

[Borda]

@sup3rgiu let's turn it to draft until failing tests are addressed 🦩

[Borda]

@SkafteNicki, what is missing here to make it land? 🐿️