Wire LearnedFeatureImputation and map_heterogeneous_to_full for MultiTaskGP (#3296)#3296
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (meta-pytorch#3296) Summary: X-link: facebook/Ax#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (meta-pytorch#3296) Summary: X-link: facebook/Ax#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (meta-pytorch#3296) Summary: X-link: facebook/Ax#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (meta-pytorch#3296) Summary: X-link: facebook/Ax#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (meta-pytorch#3296) Summary: X-link: facebook/Ax#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (meta-pytorch#3296) Summary: X-link: facebook/Ax#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (meta-pytorch#3296) Summary: X-link: facebook/Ax#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Reviewed By: saitcakmak Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Pull Request resolved: facebook#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Differential Revision: D101841497
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…TaskGP (facebook#5192) Summary: X-link: meta-pytorch/botorch#3296 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Reviewed By: saitcakmak Differential Revision: D101841497
…TaskGP (meta-pytorch#3296) Summary: X-link: facebook/Ax#5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Reviewed By: saitcakmak Differential Revision: D101841497
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…TaskGP (#5192) Summary: X-link: meta-pytorch/botorch#3296 Pull Request resolved: #5192 Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration. Reviewed By: saitcakmak Differential Revision: D101841497 fbshipit-source-id: b7769f7606eb163f0b448745b4a598dfaa97f870
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Summary:
X-link: facebook/Ax#5192
Automatically configures learned feature imputation for models that pad heterogeneous per-task data to the full joint feature space. Models with native heterogeneity support are excluded from this automatic configuration.
Reviewed By: saitcakmak
Differential Revision: D101841497