Use hypervolume difference as upperbound of contribs in HSSP #6131
+10
−0
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
not522
added
the
enhancement
nabenabe0928
reviewed
Jun 5, 2025
optuna/_hypervolume/hssp.py
Outdated
| # Note: H(T v {j}) - H(T) <= H({t} v {j}) - H({t}) = H({j}) - H({t} ^ {j}). | ||
| # Here, t is the last selected point and j is the candidate. The inequality comes from | ||
| # submodularity and the equality comes from the inclusion-exclusion principle. | ||
| single_volume = np.abs(np.prod(pareto_loss_values - reference_point[np.newaxis, :], axis=1)) |
There was a problem hiding this comment.
We could precompute single_volume if necessary.
It is an implicit assumption, but the compute_hypervolume function internally checks np.all(pareto_loss_values <= reference_point[np.newaxis, :]), so np.prod(reference_point[np.newaxis, :] - pareto_loss_values, axis=1) is equivalent.
Note
r - a is quicker than r[np.newaxis, :] - a.
In [1]: import numpy as np
...:
...:
...: a = np.random.random((30, 3))
...: r = np.ones(3)
...: %timeit r - a
...: %timeit r[np.newaxis, :] - a
...: assert np.allclose(r - a, r[np.newaxis, :] - a)
708 ns ± 8.28 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)
887 ns ± 10.7 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)
|
I confirmed the reproducibility with the following! contribs = np.minimum(
contribs,
(
np.prod(reference_point - pareto_loss_values, axis=1)
- np.prod(reference_point - np.maximum(selected_vecs[-2], pareto_loss_values), axis=1)
),
) |
Co-authored-by: Shuhei Watanabe <[email protected]>
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## master #6131 +/- ##
==========================================
+ Coverage 88.29% 88.42% +0.13%
==========================================
Files 207 207
Lines 14034 14043 +9
==========================================
+ Hits 12391 12418 +27
+ Misses 1643 1625 -18 ☔ View full report in Codecov by Sentry. |
Co-authored-by: Shuhei Watanabe <[email protected]>
nabenabe0928
reviewed
Jun 6, 2025
Co-authored-by: Shuhei Watanabe <[email protected]>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Motivation
Since
contribsin HSSP manages the upper bound of contribution for each point, it can be updated by the difference HV with the last selected point and the next candidate. This reduces the number of points that actually require hypervolume calculation.Description of the changes
Benchmark