Validate that an MO acqf is used for MOO in MBM/Acquistion #2913
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Differential Revision: D64542424
Summary: > opt_config_metrics: A dictionary of metrics that are included in the optimization config. This change makes the field consistent with its docstring and helps simplify some code. Differential Revision: D64543635
…cquisition Summary: The previous logic relied on imperfect proxies for `is_moo`. This information is readily available on `TorchOptConfig`, so we can directly utilize it. Also simplified the function signature and updated the error message for robust optimization. Differential Revision: D64545104
Summary: This does not have any usage since the multi-fidelity acquisition class has been removed. This type of functionality is better served in the acquisition function input constructors, which is what superseeded the previous multi-fidelity functionality. Removing the method helps simplify the, admittedly very complex, Acquisition constructor. Differential Revision: D64556772
Summary: Legacy models have been deprecated for quite some time and are being cleaned up. If you're interested in using KG in Ax, you can pass in `botorch_acqf_class=qKnowledgeGradient` as part of the `model_kwargs` to MBM (`Models.BoTorch`). Differential Revision: D64561219
Summary: This diff adds a validation that botorch_acqf_class is an MO acqf when `TorchOptConfig.is_moo is True`. This should eliminate bugs like facebook#2519, which can happen since the downstream code will otherwise assume SOO. Note that this only solves MBM side of the bug. Legacy code will still have the buggy behavior. Differential Revision: D64563992
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Summary:
This diff adds a validation that botorch_acqf_class is an MO acqf when
TorchOptConfig.is_moo is True. This should eliminate bugs like #2519, which can happen since the downstream code will otherwise assume SOO.Note that this only solves MBM side of the bug. Legacy code will still have the buggy behavior.
Differential Revision: D64563992