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🐛 Fix the learning rate scale #60

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@o-laurent o-laurent commented Oct 27, 2023

Thanks again to @hanruisong00 for the remark. We have to discuss the best way to fix this scaling problem. The current solution is unsatisfactory as it scales all ensemble methods; however, BatchEnsembles and Masksembles should not be scaled according to their source code. Is the default automated scaling, and are BatchEnsembles/Masksembles anomalies? No, because MCDropout should not be scaled either. If it's 50/50, we could add a parameter to handle this question correctly.

Will resolve #59.

@o-laurent o-laurent marked this pull request as draft October 27, 2023 07:42
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codecov bot commented Oct 27, 2023

Codecov Report

All modified and coverable lines are covered by tests ✅

Comparison is base (5e67064) 98.39% compared to head (d6df25c) 98.39%.

Additional details and impacted files
@@           Coverage Diff           @@
##              dev      #60   +/-   ##
=======================================
  Coverage   98.39%   98.39%           
=======================================
  Files          71       71           
  Lines        3607     3608    +1     
  Branches      426      426           
=======================================
+ Hits         3549     3550    +1     
  Misses         22       22           
  Partials       36       36           
Flag Coverage Δ
cpu 98.39% <100.00%> (+<0.01%) ⬆️
pytest 98.39% <100.00%> (+<0.01%) ⬆️

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Files Coverage Δ
torch_uncertainty/routines/classification.py 98.29% <100.00%> (+<0.01%) ⬆️

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Co-authored-by: hanruisong00 <[email protected]>
Co-authored-by: Adrien Lafage <[email protected]>
@o-laurent o-laurent linked an issue Oct 27, 2023 that may be closed by this pull request
@o-laurent o-laurent added the bug Something isn't working label Nov 1, 2023
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🐛 about learning-rate
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