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Make NotInitializedError a subclass of NotFittedError #859

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timokau opened this issue May 23, 2022 · 2 comments
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Make NotInitializedError a subclass of NotFittedError #859

timokau opened this issue May 23, 2022 · 2 comments
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@timokau
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timokau commented May 23, 2022

Hi,

currently calling predict on an uninitialized estimator throws a NotInitializedError instead of scikit-learn's NotFittedError. This is problematic in cases where we want to be able to handle different kinds of estimators while providing some kind of fallback behavior. Currently we need

try:
    prediction = estimator.predict(X)
except (NotFittedError, NotInitializedError):
    # some fallback behavior

I think it would be better if NotInitializedError was a subclass of NotFittedError. In that case we could treat an skorch estimator like a regular scikit-learn estimator and simply catch NotFittedError.

Would a PR in that direction be welcome?
@BenjaminBossan
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Thanks for the suggestion, sounds indeed like a good idea. PR is welcome.

timokau added a commit to timokau/skorch that referenced this issue May 24, 2022
@timokau
Make NotInitializedError compatible with sklearn
62f9a1b 
This ensures that a user can catch the sklearn `NotFittedError`, just as
they can with regular sklearn estimators. As discussed in [1].

[1] skorch-dev#859
@timokau timokau mentioned this issue May 24, 2022
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@timokau
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timokau commented May 24, 2022

Great :) See #860.

@timokau timokau closed this as completed May 24, 2022
BenjaminBossan pushed a commit that referenced this issue May 24, 2022
@timokau
NotInitializedError inherits from NotFittedError (#860)
297349d 
This ensures that a user can catch the sklearn `NotFittedError`, just as
they can with regular sklearn estimators. As discussed in [1].

[1] #859
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@timokau @BenjaminBossan