Remove more mocks from MBM Surrogate tests #3256
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Summary: * Use of TypeVars: A `TypeVar` indicates that multiple objects (e.g. an argument and a return type) are the same type. Using `TypeVar`s with functions that work with either numpy arrays or torch tensors indicates that either everything is a numpy array or everything is a tensor. Otherwise, Pyre has no idea whether arrays might be randomly turning into tensors and vice versa. * Added more detailed comments on tensor shapes * Used `Sequence` instead of `list` Reviewed By: saitcakmak Differential Revision: D68332888
Summary: * In `test_fit_model_reuse`, `test_fit_multiple_model_configs`, `test_fit_model_selection_metric_to_model_configs_multiple_metrics`, `test_predict`, remove mocks or use them with `wraps`, and use `mock_botorch_optimize` where not already used. In `test_best_in_sample_point`: * Make data and TorchOptConfig work with 2 outcomes, as they previously did not. * Once I did that, the test was failing because there were no points inside the search space, so I added a case where they all are and a case where one is. Reviewed By: saitcakmak Differential Revision: D68333000
Summary: I'm hoping the code is self-explanatory. I reorganized test_fit to make it clearer. Differential Revision: D68358008
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This pull request was exported from Phabricator. Differential Revision: D68358008 |
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #3256 +/- ##
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- Coverage 95.87% 95.87% -0.01%
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Files 513 513
Lines 51710 51701 -9
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- Hits 49579 49570 -9
Misses 2131 2131 ☔ View full report in Codecov by Sentry. |
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This pull request has been merged in b2d01c1. |
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Summary: I'm hoping the code is self-explanatory. I reorganized test_fit to make it clearer.
Differential Revision: D68358008