AutoSampler: Automatic Selection of Optimization Algorithms
AutoSampler automatically selects a sampler from those implemented in Optuna, depending on the situation. Using AutoSampler, as in the code example below, users can achieve optimization performance equal to or better than Optuna's default without being aware of which optimization algorithm to use.
$ pip install optunahub cmaes torch scipy
import optuna
import optunahub
auto_sampler_module = optunahub.load_module("samplers/auto_sampler")
study = optuna.create_study(sampler=auto_sampler_module.AutoSampler())
This release incorporates comprehensive performance tuning on Optuna’s RDBStorage, leading to significant performance improvements. The table below shows the comparison results of execution times between versions 4.0 and 4.1.
# trials
v4.0.0
v4.1.0
Diff
1000
72.461 sec (±1.026)
59.706 sec (±1.216)
-17.60%
10000
1153.690 sec (±91.311)
664.830 sec (±9.951)
-42.37%
50000
12118.413 sec (±254.870)
4435.961 sec (±190.582)
-63.39%
For fair comparison, all experiments were repeated 10 times, and the mean execution time was compared. Additional detailed benchmark settings include the following:
Objective Function: Each trial consists of 10 parameters and 10 user attributes
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Bumps optuna from 4.0.0 to 4.1.0.
Release notes
Sourced from optuna's releases.
... (truncated)
Commits
f8e1e6d
Merge pull request #5751 from c-bata/bump-up-to-v4.1.0604d45e
Bump the version up to v4.1.0d9327ca
Merge pull request #5741 from porink0424/fix/introduce-upsert-in-set_trial_sy...2af7c61
Resolve a small linting problemd834afb
Merge pull request #5745 from y0z/feature/update-docsd44be32
Merge pull request #5744 from nzw0301/update-actions/upload-artifact5d678de
Merge upstream4689713
Add link to the autosampler article8b648e9
Update docs/source/reference/samplers/index.rst3eadc92
Add information about AutoSampler to the docs.Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
@dependabot rebase
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