Robin Cole

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@adamjstewart can confirm, but I assume we want to keep the current behaviour

This can be swapped for `X,y = shap.datasets.california()`

@adamjstewart not sure about this Also not sure why seeing this - have run `ruff format`

Updated ruff, no issues locally ``` Successfully installed ruff-0.14.6 ⚡ Update-seg-and-class-metrics ~/torchgeo ruff format torchgeo/trainers/segmentation.py 1 file left unchanged ⚡ Update-seg-and-class-metrics ~/torchgeo ruff check torchgeo/trainers/segmentation.py All checks passed! ``` confusing...

In use an error is raised since ClasswiseWrapper returns dicts: ``` ValueError: The `.compute()` return of the metric logged as 'val_Accuracy' must be a tensor. Found {'multiclassaccuracy_background': tensor(0.9996, device='cuda:0'), 'multiclassaccuracy_solar':...

@SkafteNicki thanks for clarifying, and yes ignoring these values in averages is the goal 👍