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MIT License | ||
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Copyright (c) 2024 Preferred Networks, Inc. | ||
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Permission is hereby granted, free of charge, to any person obtaining a copy | ||
of this software and associated documentation files (the "Software"), to deal | ||
in the Software without restriction, including without limitation the rights | ||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
copies of the Software, and to permit persons to whom the Software is | ||
furnished to do so, subject to the following conditions: | ||
|
||
The above copyright notice and this permission notice shall be included in all | ||
copies or substantial portions of the Software. | ||
|
||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
SOFTWARE. |
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--- | ||
author: 'Optuna team' | ||
title: 'Grid Search' | ||
description: 'Sampler using grid search.' | ||
tags: ['sampler', 'built-in'] | ||
optuna_versions: ['3.6.1'] | ||
license: 'MIT License' | ||
--- | ||
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## Class or Function Names | ||
- GridSampler | ||
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## Example | ||
```python | ||
import optuna | ||
import optunahub | ||
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def objective(trial): | ||
x = trial.suggest_float("x", -100, 100) | ||
y = trial.suggest_int("y", -100, 100) | ||
return x**2 + y**2 | ||
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search_space = {"x": [-50, 0, 50], "y": [-99, 0, 99]} | ||
mod = optunahub.load_module("samplers/grid_search") | ||
sampler = mod.GridSampler(search_space) | ||
study = optuna.create_study(sampler=sampler) | ||
study.optimize(objective) | ||
``` | ||
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## Others | ||
See the [documentation](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.GridSampler.html) for more details. |
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from optuna.samplers import GridSampler | ||
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__all__ = ["GridSampler"] |
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MIT License | ||
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||
Copyright (c) 2024 Preferred Networks, Inc. | ||
|
||
Permission is hereby granted, free of charge, to any person obtaining a copy | ||
of this software and associated documentation files (the "Software"), to deal | ||
in the Software without restriction, including without limitation the rights | ||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
copies of the Software, and to permit persons to whom the Software is | ||
furnished to do so, subject to the following conditions: | ||
|
||
The above copyright notice and this permission notice shall be included in all | ||
copies or substantial portions of the Software. | ||
|
||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
SOFTWARE. |
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--- | ||
author: 'Optuna team' | ||
title: 'Random Search' | ||
description: 'Sampler using random sampling.' | ||
tags: ['sampler', 'built-in'] | ||
optuna_versions: ['3.6.1'] | ||
license: 'MIT License' | ||
--- | ||
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## Class or Function Names | ||
- RandomSampler | ||
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## Example | ||
```python | ||
import optuna | ||
import optunahub | ||
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def objective(trial): | ||
x = trial.suggest_float("x", -5, 5) | ||
return x**2 | ||
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mod = optunahub.load_module("samplers/random_search") | ||
sampler = mod.RandomSampler() | ||
study = optuna.create_study(sampler=sampler) | ||
study.optimize(objective, n_trials=10) | ||
``` | ||
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## Others | ||
See the [documentation](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.RandomSampler.html) for more details. | ||
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from optuna.samplers import RandomSampler | ||
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__all__ = ["RandomSampler"] |
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MIT License | ||
|
||
Copyright (c) 2024 Preferred Networks, Inc. | ||
|
||
Permission is hereby granted, free of charge, to any person obtaining a copy | ||
of this software and associated documentation files (the "Software"), to deal | ||
in the Software without restriction, including without limitation the rights | ||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
copies of the Software, and to permit persons to whom the Software is | ||
furnished to do so, subject to the following conditions: | ||
|
||
The above copyright notice and this permission notice shall be included in all | ||
copies or substantial portions of the Software. | ||
|
||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
SOFTWARE. |
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--- | ||
author: 'Optuna team' | ||
title: 'TPE Sampler' | ||
description: 'Sampler using TPE (Tree-structured Parzen Estimator) algorithm.' | ||
tags: ['sampler', 'built-in'] | ||
optuna_versions: ['3.6.1'] | ||
license: 'MIT License' | ||
--- | ||
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## Class or Function Names | ||
- TPESampler | ||
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## Example | ||
```python | ||
import optuna | ||
import optunahub | ||
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def objective(trial): | ||
x = trial.suggest_float("x", -10, 10) | ||
return x**2 | ||
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mod = optunahub.load_module("samplers/tpe") | ||
sampler = mod.TPESampler() | ||
study = optuna.create_study(sampler=sampler) | ||
study.optimize(objective, n_trials=10) | ||
``` | ||
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## Others | ||
See the [documentation](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.TPESampler.html) for more details. |
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from optuna.samplers import TPESampler | ||
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__all__ = ["TPESampler"] |
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