Deprecate weights argument of risk measures in favor of a preprocessing_function.
#1400
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Balandat
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Sep 14, 2022
botorch/acquisition/risk_measures.py
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| if weights is not None: | ||
| warnings.warn( | ||
| "`weights` argument of risk measures is deprecated and will be removed " | ||
| " in a future version. Use a `preprocessing_function` instead.", |
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| " in a future version. Use a `preprocessing_function` instead.", | |
| "in a future version. Use a `preprocessing_function` instead.", |
| @@ -498,7 +518,7 @@ def test_set_baseline_Y(self): | |||
| mars.set_baseline_Y(model=model, X_baseline=X_baseline) | |||
| self.assertTrue(torch.equal(mars.baseline_Y, torch.tensor([[-0.5, -0.5]]))) | |||
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| def test_get_Y_normalization_bounds(self): | |||
| def fest_get_Y_normalization_bounds(self): | |||
…ssing_function`. (pytorch#1400) Summary: Pull Request resolved: pytorch#1400 Deprecates the `weights` argument of risk measures in favor of a `preprocessing_function`. This is superior in that it allows better modification of the samples before computing the risk measures. This supports use cases such as filtering non-objective outcomes or applying feasibility weighting all within the risk measure itself. As a result, it helps avoid a number of if/else blocks when implementing robust optimization support in Ax. Reviewed By: Balandat Differential Revision: D39493308 fbshipit-source-id: 1278cfe01031a45ebf71876dbbd0cce80b23fea0
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This pull request was exported from Phabricator. Differential Revision: D39493308 |
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…ssing_function`. (pytorch#1400) Summary: Pull Request resolved: pytorch#1400 Deprecates the `weights` argument of risk measures in favor of a `preprocessing_function`. This is superior in that it allows better modification of the samples before computing the risk measures. This supports use cases such as filtering non-objective outcomes or applying feasibility weighting all within the risk measure itself. As a result, it helps avoid a number of if/else blocks when implementing robust optimization support in Ax. Differential Revision: https://internalfb.com/D39493308 fbshipit-source-id: 072d0a4c54de854106fa74db5e2ca2efa55d445a
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…ureMCObjective` and `squeeze_last_dim` (#1994) Summary: ## Motivation * `utils.transforms.squeeze_last_dim` was deprecated prior to 0.7.0 (#487 ), so since we are at 0.9.2 it can be deleted. * The `weights` argument of `acquisition.risk_measures.RiskMeasureMCObjective` was deprecated in 0.7.2 (#1400 ). Technically, the deprecation message only says that `weights` should be None rather than that it should not be passed, but I think it's okay to just remove it. Where it was not the last argument, I added a `*` to require that subsequent arguments be keyword-only. * ### Have you read the [Contributing Guidelines on pull requests](https://github.com/pytorch/botorch/blob/main/CONTRIBUTING.md#pull-requests)? Yes Pull Request resolved: #1994 Test Plan: Existing units ## Related PRs #487, #1400 Reviewed By: Balandat Differential Revision: D48738152 Pulled By: esantorella fbshipit-source-id: 55bee2937e55b4d993c8d1cfc68330e1eb54a8ea
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Summary:
Deprecates the
weightsargument of risk measures in favor of apreprocessing_function. This is superior in that it allows better modification of the samples before computing the risk measures.This supports use cases such as filtering non-objective outcomes or applying feasibility weighting all within the risk measure itself. As a result, it helps avoid a number of if/else blocks when implementing robust optimization support in Ax.
Differential Revision: D39493308