add mixed optimization for list optimization #1342
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Thanks for putting this together and sorry for the late review!
Re testing: You can mock out optimize_acqf and optimize_acqf_mixed, and check that the correct one was called with the correct arguments. Here's an example from tests that mock gen_candidates_scipy and gen_batch_initial_conditions. You can then check call_args / call_args_list of the mock object to assert that it got called with the correct arguments. Lmk if you need more specific examples.
botorch/optim/optimize.py
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| fixed_features: A map `{feature_index: value}` for features that | ||
| should be fixed to a particular value during generation. | ||
| fixed_features_list: A list of maps `{feature_index: value}`. The i-th | ||
| item represents the fixed_feature for the i-th optimization. If | ||
| `fixed_features_list` is provided, `optimize_acqf_mixed` is invoked | ||
| and the `fixed_features` argument is ignored. |
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If both are provided, let's throw an informative error rather than silently ignoring one.
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I changed the behavior according to your suggestion.
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@saitcakmak: I implemented the test according to how I understood your suggestion. Can you have a look? |
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@saitcakmak has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator. |
Motivation
As outlined in issue #1272,
optimize_acqf_listcannot be used to optimize over mixed domains. For this reason, this PR introduces the argumentfixed_features_listforòptimize_acqf_list. Callingoptimize_acqf_listwith a list of fixed features invokesoptimize_acqf_mixedinstead ofoptimize_acqfunder the hood.Have you read the Contributing Guidelines on pull requests?
Yes.
Test Plan
In principle unit tests, but I had problems to understand how the tests of the different optimisation functions work, perhaps @Balandat or @saitcakmak can help me here ;)
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