-
Notifications
You must be signed in to change notification settings - Fork 415
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Add **kwargs to MC and KG Acquisition Function Constructors #478
Conversation
This pull request was exported from Phabricator. Differential Revision: D22416290 |
) Summary: Pull Request resolved: pytorch#478 Different acquisition functions take different kwargs as inputs into their constructors. To standardize the inputs, we add `**kwargs` to the constructors, specifically for `qEI`, `qNEI`, `qKG`, and `qMFKG`. Reviewed By: Balandat, lena-kashtelyan Differential Revision: D22416290 fbshipit-source-id: 1f64efb6471ea7a43c2e3a057b407ef3b7331d4b
2a5c355
to
5dd7123
Compare
This pull request was exported from Phabricator. Differential Revision: D22416290 |
) Summary: Pull Request resolved: pytorch#478 Different acquisition functions take different kwargs as inputs into their constructors. To standardize the inputs, we add `**kwargs` to the constructors, specifically for `qEI`, `qNEI`, `qKG`, and `qMFKG`. Reviewed By: Balandat, lena-kashtelyan Differential Revision: D22416290 fbshipit-source-id: 08ba44314ed2aede00134c40e153c20c9eaeebc9
5dd7123
to
a2d5823
Compare
This pull request was exported from Phabricator. Differential Revision: D22416290 |
Codecov Report
@@ Coverage Diff @@
## master #478 +/- ##
=========================================
Coverage 100.00% 100.00%
=========================================
Files 84 84
Lines 5225 5225
=========================================
Hits 5225 5225
Continue to review full report at Codecov.
|
This pull request has been merged in f64e06a. |
Summary: #### New Features * Constrained Multi-Objective tutorial (#493) * Multi-fidelity Knowledge Gradient tutorial (#509) * Support for batch qMC sampling (#510) * New `evaluate` method for `qKnowledgeGradient` (#515) #### Compatibility * Require PyTorch >=1.6 (#535) * Require GPyTorch >=1.2 (#535) * Remove deprecated `botorch.gen module` (#532) #### Bug fixes * Fix bad backward-indexing of task_feature in `MultiTaskGP` (#485) * Fix bounds in constrained Branin-Currin test function (#491) * Fix max_hv for C2DTLZ2 and make Hypervolume always return a float (#494) * Fix bug in `draw_sobol_samples` that did not use the proper effective dimension (#505) * Fix constraints for `q>1` in `qExpectedHypervolumeImprovement` (c80c4fd) * Only use feasible observations in partitioning for `qExpectedHypervolumeImprovement` in `get_acquisition_function` (#523) * Improved GPU compatibility for `PairwiseGP` (#537) #### Performance Improvements * Reduce memory footprint in `qExpectedHypervolumeImprovement` (#522) * Add `(q)ExpectedHypervolumeImprovement` to nonnegative functions [for better initialization] (#496) #### Other changes * Support batched `best_f` in `qExpectedImprovement` (#487) * Allow to return full tree of solutions in `OneShotAcquisitionFunction` (#488) * Added `construct_inputs` class method to models to programmatically construct the inputs to the constructor from a standardized `TrainingData` representation (#477, #482, 3621198) * Acqusiition function constructors now accept catch-all `**kwargs` options (#478, e5b6935) * Use `psd_safe_cholesky` in `qMaxValueEntropy` for better numerical stabilty (#518) * Added `WeightedMCMultiOutputObjective` (81d91fd) * Add ability to specify `outcomes` to all multi-output objectives (#524) * Return optimization output in `info_dict` for `fit_gpytorch_scipy` (#534) * Use `setuptools_scm` for versioning (#539) Pull Request resolved: #542 Reviewed By: sdaulton Differential Revision: D23645619 Pulled By: Balandat fbshipit-source-id: 0384f266cbd517aacd5778a6e2680336869bb31c
Summary: Different acquisition functions take different kwargs as inputs into their constructors. To standardize the inputs, we add
**kwargs
to the constructors, specifically forqEI
,qNEI
,qKG
, andqMFKG
.Differential Revision: D22416290