Avoid duplications in _log_gauss_mass evaluations#6202
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nabenabe0928 merged 10 commits intooptuna:masterfrom Jul 25, 2025
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@not522 @kAIto47802 |
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Important 49% Speedup 🚀 Benchmarking Codeimport optuna
def objective(trial: optuna.Trial) -> float:
f1 = sum(trial.suggest_float(f"x{i}", -5, 5)**2 for i in range(5))
f2 = sum(trial.suggest_float(f"x{i+5}", -5, 5, step=0.5)**2 for i in range(5))
return f1 + f2
sampler = optuna.samplers.TPESampler(seed=0, multivariate=True)
study = optuna.create_study(sampler=sampler)
study.optimize(objective, n_trials=1000)
print((study.trials[-1].datetime_complete - study.trials[0].datetime_start).total_seconds()) |
…licated-eval-of-log-gauss-mass
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kAIto47802
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Jul 25, 2025
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kAIto47802
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LGTM!
I confirmed that the benchmark code you provided produces exactly the same output on the branch in this PR (8ff8e8f510725eb7f7789eefe01c729f91944fac) and the current master branch (49b26b384774e96243c6115423a9e16ac9802183) using the following code:
#!/bin/bash
git switch master
master=$(git rev-parse HEAD)
python benckmark.py > ${master}.txt
git switch nabenabe0928/enhance/avoid-duplicated-eval-of-log-gauss-mass
refactor=$(git rev-parse HEAD)
python benckmark.py > ${refactor}.txt
if cmp -s ${master}.txt ${refactor}.txt; then
echo "Both branches produce the same output."
exit 0
else
echo "The outputs differ between the branches."
exit 1
fi
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Motivation
This PR speeds up
_log_gauss_massevaluations forTPESampler.Description of the changes
np.unique_inverseequivalent operation to avoid duplicationsnp.unique_inversefor speedup_truncnorm._log_gauss_masswith the new implementation