fix bug where input transforms are not applied in fully Bayesian models in train mode #2859
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…ls in train mode (meta-pytorch#2859) Summary: This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in `train` mode. Reviewed By: saitcakmak Differential Revision: D74827275
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…ls in train mode (meta-pytorch#2859) Summary: Pull Request resolved: meta-pytorch#2859 This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in `train` mode. Reviewed By: saitcakmak Differential Revision: D74827275
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…ls in train mode (meta-pytorch#2859) Summary: This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in `train` mode. Reviewed By: saitcakmak Differential Revision: D74827275
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…ls in train mode (meta-pytorch#2859) Summary: This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in `train` mode. Reviewed By: saitcakmak Differential Revision: D74827275
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…ls in train mode (meta-pytorch#2859) Summary: Pull Request resolved: meta-pytorch#2859 This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in `train` mode. Reviewed By: saitcakmak Differential Revision: D74827275
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Summary: see title Differential Revision: D74824675
Summary: see title. Differential Revision: D74826655
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…ls in train mode (meta-pytorch#2859) Summary: This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in `train` mode. Reviewed By: saitcakmak Differential Revision: D74827275
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…ls in train mode (meta-pytorch#2859) Summary: This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in `train` mode. Reviewed By: saitcakmak Differential Revision: D74827275
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This pull request was exported from Phabricator. Differential Revision: D74827275 |
…ls in train mode (meta-pytorch#2859) Summary: Pull Request resolved: meta-pytorch#2859 This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in `train` mode. Reviewed By: saitcakmak Differential Revision: D74827275
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Summary: This fixes a bug where input transforms were not applied to fully Bayesian GPs in training mode. This only affects computing MLL, AIC, and BIC (which previously where computing without applying normalization/warping) for fully Bayesian GPs. We don't evaluate fully Bayesian models in
trainmode.Reviewed By: saitcakmak
Differential Revision: D74827275