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Feature/yardstick #12

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Feature/yardstick #12

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dfalbel
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@dfalbel dfalbel commented May 13, 2021

@mattwarkentin I have played with the idea we discussed in #6 using yardstick here.

The problems I see are:

  • for example: accuracy in yardstick expects factors while torch don't know about factors at all.
  • Matrixes are not supported, while it's quite common that your model returns (batch_size, 1) predictions. I think this enough for us to re-implement stuff in luz.

I tried to fix these by allowing a transform function that is called before trying to apply the metrics, so the user has control on how to transform predictions and targets before passing to yardstick.

What do you think?

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