Skip fixed feature enumerations in optimize_acqf_mixed that can't satisfy the parameter constraints #2614
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…isfy the parameter constraints (pytorch#2614) Summary: Pull Request resolved: pytorch#2614 When using `optimize_acqf_mixed`, some combinations of fixed features may result in the parameter constraints being impossible to satisfy. This causes `optimize_acqf` to error out. This diff skips the combinations of fixed features where the parameter constraints are impossible to satisfy. Differential Revision: D65514819
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #2614 +/- ##
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Coverage 99.98% 99.98%
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Files 196 196
Lines 17359 17369 +10
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+ Hits 17357 17367 +10
Misses 2 2 ☔ View full report in Codecov by Sentry. |
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…isfy the parameter constraints (pytorch#2614) Summary: When using `optimize_acqf_mixed`, some combinations of fixed features may result in the parameter constraints being impossible to satisfy. This causes `optimize_acqf` to error out. This diff skips the combinations of fixed features where the parameter constraints are impossible to satisfy. Reviewed By: saitcakmak, esantorella Differential Revision: D65514819
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This pull request was exported from Phabricator. Differential Revision: D65514819 |
…isfy the parameter constraints (pytorch#2614) Summary: When using `optimize_acqf_mixed`, some combinations of fixed features may result in the parameter constraints being impossible to satisfy. This causes `optimize_acqf` to error out. This diff skips the combinations of fixed features where the parameter constraints are impossible to satisfy. Reviewed By: saitcakmak, esantorella Differential Revision: D65514819
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This pull request was exported from Phabricator. Differential Revision: D65514819 |
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This pull request has been merged in cd657d9. |
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Summary: When using
optimize_acqf_mixed, some combinations of fixed features may result in the parameter constraints being impossible to satisfy. This causesoptimize_acqfto error out. This diff skips the combinations of fixed features where the parameter constraints are impossible to satisfy.Differential Revision: D65514819