Clean up is_fully_bayesian #2108
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Summary: This attempts to clean up the usage of `is_fully_bayesian` and also separately treat fully Bayesian models from ensemble models. The main changes in diff are to: - Add an `_is_fully_bayesian` attribute to `Model`. This is `True` for fully Bayesian models that rely on Pyro/NUTS to be fitted (they need some special handling for fitting and `state_dict` loading/saving. - Add an `_is_ensemble` attribute to `Model`. This indicates whether the model is a collection of multiple models that are stored in an additional batch dimension. This is hopefully a better classification, but I'm open to a different name here. - Rename `FullyBayesianPosterior` to `GaussianMixturePosterior` since that is more descriptive and plays better with the other changes. Reviewed By: esantorella Differential Revision: D50884342
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Summary: X-link: pytorch/botorch#2108 This attempts to clean up the usage of `is_fully_bayesian` and also separately treat fully Bayesian models from ensemble models. The main changes in diff are to: - Add an `_is_fully_bayesian` attribute to `Model`. This is `True` for fully Bayesian models that rely on Pyro/NUTS to be fitted (they need some special handling for fitting and `state_dict` loading/saving. - Add an `_is_ensemble` attribute to `Model`. This indicates whether the model is a collection of multiple models that are stored in an additional batch dimension. This is hopefully a better classification, but I'm open to a different name here. - Rename `FullyBayesianPosterior` to `GaussianMixturePosterior` since that is more descriptive and plays better with the other changes. Reviewed By: esantorella Differential Revision: D50884342
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Summary: Pull Request resolved: #1992 X-link: pytorch/botorch#2108 This attempts to clean up the usage of `is_fully_bayesian` and also separately treat fully Bayesian models from ensemble models. The main changes in diff are to: - Add an `_is_fully_bayesian` attribute to `Model`. This is `True` for fully Bayesian models that rely on Pyro/NUTS to be fitted (they need some special handling for fitting and `state_dict` loading/saving. - Add an `_is_ensemble` attribute to `Model`. This indicates whether the model is a collection of multiple models that are stored in an additional batch dimension. This is hopefully a better classification, but I'm open to a different name here. - Rename `FullyBayesianPosterior` to `GaussianMixturePosterior` since that is more descriptive and plays better with the other changes. Reviewed By: esantorella Differential Revision: D50884342 fbshipit-source-id: 0ba603416c1823026c4fdf2e445cefdf8036cda8
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Summary:
This attempts to clean up the usage of
is_fully_bayesianand also separately treat fully Bayesian models from ensemble models.The main changes in diff are to:
_is_fully_bayesianattribute toModel. This isTruefor fully Bayesian models that rely on Pyro/NUTS to be fitted (they need some special handling for fitting andstate_dictloading/saving._is_ensembleattribute toModel. This indicates whether the model is a collection of multiple models that are stored in an additional batch dimension. This is hopefully a better classification, but I'm open to a different name here.FullyBayesianPosteriortoGaussianMixturePosteriorsince that is more descriptive and plays better with the other changes.Reviewed By: esantorella
Differential Revision: D50884342