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Hi @an1lam, |
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We've been using torchmetrics internally and enjoying it, but two things we've had to work around are:
SpearmanCorrcoef
don't support multioutput mode (unlikeR2Score
for example).NaN
labels for certain features is our use-case).As a simple solution to this, we've implemented a
MultioutputWrapper
class (similar toBootstrapAggregator
) that takes abase_metric
and copies itnum_outputs
times, updating each underlying on each metric call. While we've tried to make our internal version as generic as possible, we've admittedly only tested it with the metrics we currently use. Examples includeR2Score
,SpearmanCorrcoef
, andAccuracy
with (N, C, O) (where O is number of outputs/tasks) dimensional predictions and (N, O) dimensional labels.Since we've found this wrapper quite helpful, we'd like to contribute it back to the base package so others can use it. However, we expect it'll take a little work/feedback from the maintainers to get it in a place where it's ready for merging. For that reason, before even creating an issue/PR, I wanted to feel out whether this sort of class seems worth having in the base package and makes sense conceptually.
Thanks in advance!
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