Work around CV errors due to insufficient data #4123
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Summary: It is possible to fit a TorchAdapter with only one data point but it is not possible to run cross validation with it. This can lead to errors since we rely on CV statistics in `BestModelSelector`, which is used in BOTL. This diff gracefully handles such errors rather than erroring out in the experiment. Differential Revision: D79915007
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Summary: It is possible to fit a TorchAdapter with only one data point but it is not possible to run cross validation with it. This can lead to errors since we rely on CV statistics in `BestModelSelector`, which is used in BOTL. This diff gracefully handles such errors rather than erroring out in the experiment. Reviewed By: esantorella Differential Revision: D79915007
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Summary: Pull Request resolved: facebook#4123 It is possible to fit a TorchAdapter with only one data point but it is not possible to run cross validation with it. This can lead to errors since we rely on CV statistics in `BestModelSelector`, which is used in BOTL. This diff gracefully handles such errors rather than erroring out in the experiment. Reviewed By: esantorella Differential Revision: D79915007
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #4123 +/- ##
=======================================
Coverage 96.08% 96.08%
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Files 566 566
Lines 57205 57219 +14
=======================================
+ Hits 54965 54979 +14
Misses 2240 2240 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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This pull request has been merged in 1964c45. |
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Summary: It is possible to fit a TorchAdapter with only one data point but it is not possible to run cross validation with it. This can lead to errors since we rely on CV statistics in
BestModelSelector, which is used in BOTL. This diff gracefully handles such errors rather than erroring out in the experiment.Differential Revision: D79915007