change LinearRegressionUCB forward pass logic to make it more tracing-friendly#682
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alexnikulkov wants to merge 1 commit intofacebookresearch:mainfrom
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change LinearRegressionUCB forward pass logic to make it more tracing-friendly#682alexnikulkov wants to merge 1 commit intofacebookresearch:mainfrom
alexnikulkov wants to merge 1 commit intofacebookresearch:mainfrom
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…-friendly Summary: The "if" statement in the forward pass causes a warning during tracing. It will be safer to use a separate `_forward_no_coefs_check()` method for the forward pass of a trained model. In this method we don't check the validity of coefficients, instead the coefficients are assumed to be valid because we compute them at the end of the training epoch The behavior of existing methods/properties should remain unchanged. Differential Revision: D39692331 fbshipit-source-id: bbc4e9a1c50721f46a3cd210c42001a0871bdecd
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This pull request was exported from Phabricator. Differential Revision: D39692331 |
Codecov ReportBase: 87.52% // Head: 87.52% // Decreases project coverage by
Additional details and impacted files@@ Coverage Diff @@
## main #682 +/- ##
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- Coverage 87.52% 87.52% -0.01%
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Files 366 366
Lines 23443 23448 +5
Branches 44 44
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+ Hits 20519 20523 +4
- Misses 2898 2899 +1
Partials 26 26
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xuruiyang
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…-friendly (#682) Summary: Pull Request resolved: #682 The "if" statement in the forward pass causes a warning during tracing. It will be safer to use a separate `_forward_no_coefs_check()` method for the forward pass of a trained model. In this method we don't check the validity of coefficients, instead the coefficients are assumed to be valid because we compute them at the end of the training epoch The behavior of existing methods/properties should remain unchanged. Reviewed By: czxttkl Differential Revision: D39692331 fbshipit-source-id: bcb2a705345ad34e7ab1574c21955dd111267de9
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Summary:
The "if" statement in the forward pass causes a warning during tracing. It will be safer to use a separate
_forward_no_coefs_check()method for the forward pass of a trained model. In this method we don't check the validity of coefficients, instead the coefficients are assumed to be valid because we compute them at the end of the training epochThe behavior of existing methods/properties should remain unchanged.
Differential Revision: D39692331