make benchmarks support additional models and include observation noise #3
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Summary: Refit the model after exceptions to address cases where model fitting suceeds, but an exception is raised at prediction time. This is not as clean as I would like, but this keeps any observed data such that the benchmarks reflect our ability to retry after exceptions without re-evaluating in a real optimization scenario. Differential Revision: D13560964 fbshipit-source-id: 5ab9bab50dbe9741e53b2162b1bc7aa9effc0342
…se (#3) Summary: Pull Request resolved: #3 Add ability to supply an arbitrary model to the benchmarks (so long as it has a likelihood so that we know how to refit it). Also, add support for observation noise. Reviewed By: Balandat Differential Revision: D13561279 fbshipit-source-id: 51a58b4429b3bb2fc25364e34e30fe0ce3727dd8
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…se (#3) Summary: Pull Request resolved: #3 Add ability to supply an arbitrary model to the benchmarks (so long as it has a likelihood so that we know how to refit it). Also, add support for observation noise. Reviewed By: Balandat Differential Revision: D13561279 fbshipit-source-id: 94bcf92819e9b6d0977b8a1f4ee43f6bce0c3e80
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Summary: Add ability to supply an arbitrary model to the benchmarks (so long as it has a likelihood so that we know how to refit it). Also, add support for observation noise.
Reviewed By: Balandat
Differential Revision: D13561279