PairwiseGP modularization and PairwiseLogitLikelihood #1193
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood Differential Revision: D35921953 fbshipit-source-id: 08138ed8ab69a27d092608ee55a818b58f54bd58
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood Differential Revision: D35921953 fbshipit-source-id: f11ca11ab0362f8b789505db4777981441c0a6a3
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood Reviewed By: Balandat Differential Revision: D35921953 fbshipit-source-id: f98b2de32b49027590fb3c2a553de5f5d264a0eb
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Codecov Report
@@ Coverage Diff @@
## main #1193 +/- ##
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Coverage 100.00% 100.00%
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Files 118 120 +2
Lines 10386 10436 +50
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+ Hits 10386 10436 +50
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood Reviewed By: Balandat Differential Revision: D35921953 fbshipit-source-id: d96acaddafb4574c4cb72445b1b04201aff77991
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood. Fixed PairwiseGP's conditioning gradient issue. Reviewed By: Balandat Differential Revision: D35921953 fbshipit-source-id: f7ad615b5825bac47d9606d75539719c3a771341
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood. Fixed PairwiseGP's conditioning gradient issue. Reviewed By: Balandat Differential Revision: D35921953 fbshipit-source-id: 4222b16cdbb99f670ee7b8bf95569b8227883a30
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood. Fixed PairwiseGP's conditioning gradient issue. Reviewed By: Balandat Differential Revision: D35921953 fbshipit-source-id: f90f2a88c0cb0aa949882bb71d42eec8099cf368
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ItsMrLin
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood. Fixed PairwiseGP's conditioning gradient issue. Reviewed By: Balandat Differential Revision: D35921953 fbshipit-source-id: 254ced42cd8fc4b22f731e19d9f04e96d4ac4bdd
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood. Fixed PairwiseGP's conditioning gradient issue. Reviewed By: Balandat Differential Revision: D35921953 fbshipit-source-id: ff121f654b7e0e2fabb67ec002b2e88481a575c9
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Summary: Pull Request resolved: pytorch#1193 Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood. Fixed PairwiseGP's conditioning gradient issue. Reviewed By: Balandat Differential Revision: D35921953 fbshipit-source-id: a15dbd903f478e40ff32fda07d74325f38a3e849
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Summary: X-link: facebook/Ax#1193 Pull Request resolved: #1445 We commonly see issues with users running into numerical errors when using float inputs. This adds a dtype check in `_validate_tensor_args`, which is used in the constructor of a large number of models, warning the users if they're not using double, and pointing them to #1444. Feel free to edit & add more details / examples to the discussion! Reviewed By: Balandat Differential Revision: D40199087 fbshipit-source-id: 137bb551ba846831e4df1c3e381fe6ac35512fc2
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Summary: Modularize PairwiseGP's likelihood and add logit likelihood support in addition to the original probit likelihood
Differential Revision: D35921953